modern technology research paper

• Previous Article
• Next Article

Promises and Pitfalls of Technology

Politics and privacy, private-sector influence and big tech, state competition and conflict, author biography, how is technology changing the world, and how should the world change technology.

[email protected]

• Split-Screen
• Article contents
• Figures & tables
• Supplementary Data
• Peer Review
• Open the PDF for in another window
• Guest Access
• Get Permissions
• Cite Icon Cite
• Search Site

Josephine Wolff; How Is Technology Changing the World, and How Should the World Change Technology?. Global Perspectives 1 February 2021; 2 (1): 27353. doi: https://doi.org/10.1525/gp.2021.27353

Download citation file:

• Ris (Zotero)
• Reference Manager

Technologies are becoming increasingly complicated and increasingly interconnected. Cars, airplanes, medical devices, financial transactions, and electricity systems all rely on more computer software than they ever have before, making them seem both harder to understand and, in some cases, harder to control. Government and corporate surveillance of individuals and information processing relies largely on digital technologies and artificial intelligence, and therefore involves less human-to-human contact than ever before and more opportunities for biases to be embedded and codified in our technological systems in ways we may not even be able to identify or recognize. Bioengineering advances are opening up new terrain for challenging philosophical, political, and economic questions regarding human-natural relations. Additionally, the management of these large and small devices and systems is increasingly done through the cloud, so that control over them is both very remote and removed from direct human or social control. The study of how to make technologies like artificial intelligence or the Internet of Things “explainable” has become its own area of research because it is so difficult to understand how they work or what is at fault when something goes wrong (Gunning and Aha 2019) .

This growing complexity makes it more difficult than ever—and more imperative than ever—for scholars to probe how technological advancements are altering life around the world in both positive and negative ways and what social, political, and legal tools are needed to help shape the development and design of technology in beneficial directions. This can seem like an impossible task in light of the rapid pace of technological change and the sense that its continued advancement is inevitable, but many countries around the world are only just beginning to take significant steps toward regulating computer technologies and are still in the process of radically rethinking the rules governing global data flows and exchange of technology across borders.

These are exciting times not just for technological development but also for technology policy—our technologies may be more advanced and complicated than ever but so, too, are our understandings of how they can best be leveraged, protected, and even constrained. The structures of technological systems as determined largely by government and institutional policies and those structures have tremendous implications for social organization and agency, ranging from open source, open systems that are highly distributed and decentralized, to those that are tightly controlled and closed, structured according to stricter and more hierarchical models. And just as our understanding of the governance of technology is developing in new and interesting ways, so, too, is our understanding of the social, cultural, environmental, and political dimensions of emerging technologies. We are realizing both the challenges and the importance of mapping out the full range of ways that technology is changing our society, what we want those changes to look like, and what tools we have to try to influence and guide those shifts.

Technology can be a source of tremendous optimism. It can help overcome some of the greatest challenges our society faces, including climate change, famine, and disease. For those who believe in the power of innovation and the promise of creative destruction to advance economic development and lead to better quality of life, technology is a vital economic driver (Schumpeter 1942) . But it can also be a tool of tremendous fear and oppression, embedding biases in automated decision-making processes and information-processing algorithms, exacerbating economic and social inequalities within and between countries to a staggering degree, or creating new weapons and avenues for attack unlike any we have had to face in the past. Scholars have even contended that the emergence of the term technology in the nineteenth and twentieth centuries marked a shift from viewing individual pieces of machinery as a means to achieving political and social progress to the more dangerous, or hazardous, view that larger-scale, more complex technological systems were a semiautonomous form of progress in and of themselves (Marx 2010) . More recently, technologists have sharply criticized what they view as a wave of new Luddites, people intent on slowing the development of technology and turning back the clock on innovation as a means of mitigating the societal impacts of technological change (Marlowe 1970) .

At the heart of fights over new technologies and their resulting global changes are often two conflicting visions of technology: a fundamentally optimistic one that believes humans use it as a tool to achieve greater goals, and a fundamentally pessimistic one that holds that technological systems have reached a point beyond our control. Technology philosophers have argued that neither of these views is wholly accurate and that a purely optimistic or pessimistic view of technology is insufficient to capture the nuances and complexity of our relationship to technology (Oberdiek and Tiles 1995) . Understanding technology and how we can make better decisions about designing, deploying, and refining it requires capturing that nuance and complexity through in-depth analysis of the impacts of different technological advancements and the ways they have played out in all their complicated and controversial messiness across the world.

These impacts are often unpredictable as technologies are adopted in new contexts and come to be used in ways that sometimes diverge significantly from the use cases envisioned by their designers. The internet, designed to help transmit information between computer networks, became a crucial vehicle for commerce, introducing unexpected avenues for crime and financial fraud. Social media platforms like Facebook and Twitter, designed to connect friends and families through sharing photographs and life updates, became focal points of election controversies and political influence. Cryptocurrencies, originally intended as a means of decentralized digital cash, have become a significant environmental hazard as more and more computing resources are devoted to mining these forms of virtual money. One of the crucial challenges in this area is therefore recognizing, documenting, and even anticipating some of these unexpected consequences and providing mechanisms to technologists for how to think through the impacts of their work, as well as possible other paths to different outcomes (Verbeek 2006) . And just as technological innovations can cause unexpected harm, they can also bring about extraordinary benefits—new vaccines and medicines to address global pandemics and save thousands of lives, new sources of energy that can drastically reduce emissions and help combat climate change, new modes of education that can reach people who would otherwise have no access to schooling. Regulating technology therefore requires a careful balance of mitigating risks without overly restricting potentially beneficial innovations.

Nations around the world have taken very different approaches to governing emerging technologies and have adopted a range of different technologies themselves in pursuit of more modern governance structures and processes (Braman 2009) . In Europe, the precautionary principle has guided much more anticipatory regulation aimed at addressing the risks presented by technologies even before they are fully realized. For instance, the European Union’s General Data Protection Regulation focuses on the responsibilities of data controllers and processors to provide individuals with access to their data and information about how that data is being used not just as a means of addressing existing security and privacy threats, such as data breaches, but also to protect against future developments and uses of that data for artificial intelligence and automated decision-making purposes. In Germany, Technische Überwachungsvereine, or TÜVs, perform regular tests and inspections of technological systems to assess and minimize risks over time, as the tech landscape evolves. In the United States, by contrast, there is much greater reliance on litigation and liability regimes to address safety and security failings after-the-fact. These different approaches reflect not just the different legal and regulatory mechanisms and philosophies of different nations but also the different ways those nations prioritize rapid development of the technology industry versus safety, security, and individual control. Typically, governance innovations move much more slowly than technological innovations, and regulations can lag years, or even decades, behind the technologies they aim to govern.

In addition to this varied set of national regulatory approaches, a variety of international and nongovernmental organizations also contribute to the process of developing standards, rules, and norms for new technologies, including the International Organization for Standardization­ and the International Telecommunication Union. These multilateral and NGO actors play an especially important role in trying to define appropriate boundaries for the use of new technologies by governments as instruments of control for the state.

At the same time that policymakers are under scrutiny both for their decisions about how to regulate technology as well as their decisions about how and when to adopt technologies like facial recognition themselves, technology firms and designers have also come under increasing criticism. Growing recognition that the design of technologies can have far-reaching social and political implications means that there is more pressure on technologists to take into consideration the consequences of their decisions early on in the design process (Vincenti 1993; Winner 1980) . The question of how technologists should incorporate these social dimensions into their design and development processes is an old one, and debate on these issues dates back to the 1970s, but it remains an urgent and often overlooked part of the puzzle because so many of the supposedly systematic mechanisms for assessing the impacts of new technologies in both the private and public sectors are primarily bureaucratic, symbolic processes rather than carrying any real weight or influence.

Technologists are often ill-equipped or unwilling to respond to the sorts of social problems that their creations have—often unwittingly—exacerbated, and instead point to governments and lawmakers to address those problems (Zuckerberg 2019) . But governments often have few incentives to engage in this area. This is because setting clear standards and rules for an ever-evolving technological landscape can be extremely challenging, because enforcement of those rules can be a significant undertaking requiring considerable expertise, and because the tech sector is a major source of jobs and revenue for many countries that may fear losing those benefits if they constrain companies too much. This indicates not just a need for clearer incentives and better policies for both private- and public-sector entities but also a need for new mechanisms whereby the technology development and design process can be influenced and assessed by people with a wider range of experiences and expertise. If we want technologies to be designed with an eye to their impacts, who is responsible for predicting, measuring, and mitigating those impacts throughout the design process? Involving policymakers in that process in a more meaningful way will also require training them to have the analytic and technical capacity to more fully engage with technologists and understand more fully the implications of their decisions.

At the same time that tech companies seem unwilling or unable to rein in their creations, many also fear they wield too much power, in some cases all but replacing governments and international organizations in their ability to make decisions that affect millions of people worldwide and control access to information, platforms, and audiences (Kilovaty 2020) . Regulators around the world have begun considering whether some of these companies have become so powerful that they violate the tenets of antitrust laws, but it can be difficult for governments to identify exactly what those violations are, especially in the context of an industry where the largest players often provide their customers with free services. And the platforms and services developed by tech companies are often wielded most powerfully and dangerously not directly by their private-sector creators and operators but instead by states themselves for widespread misinformation campaigns that serve political purposes (Nye 2018) .

Since the largest private entities in the tech sector operate in many countries, they are often better poised to implement global changes to the technological ecosystem than individual states or regulatory bodies, creating new challenges to existing governance structures and hierarchies. Just as it can be challenging to provide oversight for government use of technologies, so, too, oversight of the biggest tech companies, which have more resources, reach, and power than many nations, can prove to be a daunting task. The rise of network forms of organization and the growing gig economy have added to these challenges, making it even harder for regulators to fully address the breadth of these companies’ operations (Powell 1990) . The private-public partnerships that have emerged around energy, transportation, medical, and cyber technologies further complicate this picture, blurring the line between the public and private sectors and raising critical questions about the role of each in providing critical infrastructure, health care, and security. How can and should private tech companies operating in these different sectors be governed, and what types of influence do they exert over regulators? How feasible are different policy proposals aimed at technological innovation, and what potential unintended consequences might they have?

Conflict between countries has also spilled over significantly into the private sector in recent years, most notably in the case of tensions between the United States and China over which technologies developed in each country will be permitted by the other and which will be purchased by other customers, outside those two countries. Countries competing to develop the best technology is not a new phenomenon, but the current conflicts have major international ramifications and will influence the infrastructure that is installed and used around the world for years to come. Untangling the different factors that feed into these tussles as well as whom they benefit and whom they leave at a disadvantage is crucial for understanding how governments can most effectively foster technological innovation and invention domestically as well as the global consequences of those efforts. As much of the world is forced to choose between buying technology from the United States or from China, how should we understand the long-term impacts of those choices and the options available to people in countries without robust domestic tech industries? Does the global spread of technologies help fuel further innovation in countries with smaller tech markets, or does it reinforce the dominance of the states that are already most prominent in this sector? How can research universities maintain global collaborations and research communities in light of these national competitions, and what role does government research and development spending play in fostering innovation within its own borders and worldwide? How should intellectual property protections evolve to meet the demands of the technology industry, and how can those protections be enforced globally?

These conflicts between countries sometimes appear to challenge the feasibility of truly global technologies and networks that operate across all countries through standardized protocols and design features. Organizations like the International Organization for Standardization, the World Intellectual Property Organization, the United Nations Industrial Development Organization, and many others have tried to harmonize these policies and protocols across different countries for years, but have met with limited success when it comes to resolving the issues of greatest tension and disagreement among nations. For technology to operate in a global environment, there is a need for a much greater degree of coordination among countries and the development of common standards and norms, but governments continue to struggle to agree not just on those norms themselves but even the appropriate venue and processes for developing them. Without greater global cooperation, is it possible to maintain a global network like the internet or to promote the spread of new technologies around the world to address challenges of sustainability? What might help incentivize that cooperation moving forward, and what could new structures and process for governance of global technologies look like? Why has the tech industry’s self-regulation culture persisted? Do the same traditional drivers for public policy, such as politics of harmonization and path dependency in policy-making, still sufficiently explain policy outcomes in this space? As new technologies and their applications spread across the globe in uneven ways, how and when do they create forces of change from unexpected places?

These are some of the questions that we hope to address in the Technology and Global Change section through articles that tackle new dimensions of the global landscape of designing, developing, deploying, and assessing new technologies to address major challenges the world faces. Understanding these processes requires synthesizing knowledge from a range of different fields, including sociology, political science, economics, and history, as well as technical fields such as engineering, climate science, and computer science. A crucial part of understanding how technology has created global change and, in turn, how global changes have influenced the development of new technologies is understanding the technologies themselves in all their richness and complexity—how they work, the limits of what they can do, what they were designed to do, how they are actually used. Just as technologies themselves are becoming more complicated, so are their embeddings and relationships to the larger social, political, and legal contexts in which they exist. Scholars across all disciplines are encouraged to join us in untangling those complexities.

Josephine Wolff is an associate professor of cybersecurity policy at the Fletcher School of Law and Diplomacy at Tufts University. Her book You’ll See This Message When It Is Too Late: The Legal and Economic Aftermath of Cybersecurity Breaches was published by MIT Press in 2018.

Recipient(s) will receive an email with a link to 'How Is Technology Changing the World, and How Should the World Change Technology?' and will not need an account to access the content.

Subject: How Is Technology Changing the World, and How Should the World Change Technology?

(Optional message may have a maximum of 1000 characters.)

Citing articles via

Email alerts, affiliations.

• Special Collections
• Review Symposia
• Info for Authors
• Info for Librarians
• Editorial Team
• Emerging Scholars Forum
• Open Access
• Online ISSN 2575-7350
• Copyright © 2024 The Regents of the University of California. All Rights Reserved.

Stay Informed

Disciplines.

• Ancient World
• Anthropology
• Communication
• Criminology & Criminal Justice
• Film & Media Studies
• Food & Wine
• Browse All Disciplines
• Browse All Courses
• Book Authors
• Booksellers
• Instructions
• Journal Authors
• Journal Editors
• Media & Journalists
• Planned Giving

About UC Press

• Press Releases
• Seasonal Catalog
• Acquisitions Editors
• Customer Service
• Exam/Desk Requests
• Media Inquiries
• Print-Disability
• Rights & Permissions
• UC Press Foundation
• © Copyright 2024 by the Regents of the University of California. All rights reserved. Privacy policy    Accessibility

This Feature Is Available To Subscribers Only

Sign In or Create an Account

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals

Technology articles from across Nature Portfolio

Cryogenic optical data link for superconducting circuits

An optical fibre-fed superconducting electro-optic modulator with gigahertz bandwidth and attojoule per bit electric power consumption offers a fast, efficient means to connect superconducting circuits to the room temperature environment.

• Paolo Pintus
• Galan Moody

Latest Research and Reviews

The Plegma dataset: Domestic appliance-level and aggregate electricity demand with metadata from Greece

• Sotirios Athanasoulias
• Fernanda Guasselli
• Vladimir Stankovic

brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

brainlife.io is a one-stop cloud platform for data management, visualization and analysis in human neuroscience. It is web-based and provides access to a variety of tools in a reproducible and reliable manner.

• Soichi Hayashi
• Bradley A. Caron
• Franco Pestilli

Standardised Versioning of Datasets: a FAIR–compliant Proposal

• Alba González–Cebrián
• Michael Bradford
• Horacio González–Vélez

Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation

• Elizabeth C. Stade
• Shannon Wiltsey Stirman
• Johannes C. Eichstaedt

A vision for sustainable additive manufacturing

Additive manufacturing is gaining growing attention as an alternative to conventional methods, but it can support more-sustainable manufacturing processes if developed through a system-level approach. This Perspective discusses how to achieve such a holistic development of additive manufacturing systems for sustainability.

• Serena Graziosi
• Jeremy Faludi
• David W. Rosen

Orbital Reef and commercial low Earth orbit destinations—upcoming space research opportunities

• Erika Wagner

News and Comment

Innovative dietary fat production.

Fats and oils are crucial dietary supplements for human health. However, animal fats and palm oil dominate the food industry, with concerns over health and the environment that call for the development of fat alternatives. The fat industry offers a vast market potential, with several startups pioneering new technical solutions and attracting venture capital interest.

• Enrico Costanzo
• Giorgia Spigno

This water bottle purifies your drink with energy from your steps

Static electricity generated by the foot striking the ground can be captured to kill pathogens.

How to break big tech’s stranglehold on AI in academia

• Michał Woźniak
• Paweł Ksieniewicz

Use fines from EU social-media act to fund research on adolescent mental health

• Christian Montag
• Benjamin Becker

A call for responsible quantum technology

The time has come to consider appropriate guardrails to ensure quantum technology benefits humanity and the planet. With quantum development still in flux, the science community shares a responsibility in defining principles and practices.

• Eline De Jong
• Mauritz Kop

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

SYSTEMATIC REVIEW article

The effects of technological developments on work and their implications for continuous vocational education and training: a systematic review.

• Faculty of Human Sciences, University of Regensburg, Regensburg, Germany

Technology is changing the way organizations and their employees need to accomplish their work. Empirical evidence on this topic is scarce. The aim of this study is to provide an overview of the effects of technological developments on work characteristics and to derive the implications for work demands and continuous vocational education and training (CVET). The following research questions are answered: What are the effects of new technologies on work characteristics? What are the implications thereof for continuous vocational education and training? Technologies, defined as digital, electrical or mechanical tools that affect the accomplishment of work tasks, are considered in various disciplines, such as sociology or psychology. A theoretical framework based on theories from these disciplines (e.g., upskilling, task-based approach) was developed and statements on the relationships between technology and work characteristics, such as complexity, autonomy, or meaningfulness, were derived. A systematic literature review was conducted by searching databases from the fields of psychology, sociology, economics and educational science. Twenty-one studies met the inclusion criteria. Empirical evidence was extracted and its implications for work demands and CVET were derived by using a model that illustrates the components of learning environments. Evidence indicates an increase in complexity and mental work, especially while working with automated systems and robots. Manual work is reported to decrease on many occasions. Workload and workflow interruptions increase simultaneously with autonomy, especially with regard to digital communication devices. Role expectations and opportunities for development depend on how the profession and the technology relate to each other, especially when working with automated systems. The implications for the work demands necessary to deal with changes in work characteristics include knowledge about technology, openness toward change and technology, skills for self- and time management and for further professional and career development. Implications for the design of formal learning environments (i.e., the content, method, assessment, and guidance) include that the work demands mentioned must be part of the content of the trainings, the teachers/trainers must be equipped to promote those work demands, and that instruction models used for the learning environments must be flexible in their application.

Introduction

In the face of technology-driven disruptive changes in societal and organizational practices, continuous vocational education and training (CVET) lacks information on how the impact of technologies on work must be considered from an educational perspective ( Cascio and Montealegre, 2016 ). Research on workplace technologies, i.e., tools or systems that have the potential to replace or supplement work tasks, typically are concerned with one out of two areas of interest: First, economic and sociological research repeatedly raises the question on technological mass-unemployment and societal inequality as a result of technological advances ( Brynjolfsson and McAfee, 2014 ; Ford, 2015 ; Frey and Osborne, 2017 ). And second, management literature questions the suitability of prevailing organizational structures in the face of the so-called “fourth industrial revolution” ( Schwab, 2017 ), taking visionary leaps into a fully automated future of digital value creation ( Roblek et al., 2016 ).

Many of the contributions of scholars discuss the enormous potential of new technologies for work and society at a hypothetical level, which led to a large number of position papers. Moreover, the question on what consequences recent developments, such as working with robots, automated systems or artificial intelligence will have for different professions remain largely unclear. By examining what workplace technologies actually “do” in the work environment, it was suggested that work tasks change because of technological developments ( Autor et al., 2003 ; Autor, 2015 ). This is due to technologies substituting different operations or entire tasks and thus leave room for other activities. Jobs are defined by the work tasks and the conditions under which the tasks have to be performed. This in turn defines the necessary competences, that is the potential capacity to carry out a job (e.g., Ellström, 1997 ). Therefore, CVET needs to be informed on the changes that technology causes in work tasks and the consequential characteristics of work. Only then CVET is able to derive the required competences of employees and organize learning environments that foster the acquirement of these competences. These insights can be used to determine the implications thereof for the components of formal learning environments: content, didactics, trainer behavior, assessment, and resources (e.g., Mulder et al., 2015 ).

The aim of this systematic literature review is to get insight into the effects of new technological developments on work characteristics in order to derive the necessary work demands and their implications for the design of formal learning environments in CVET.

Therefore, the following research questions will be answered:

RQ 1 : What are the effects of new technologies on work characteristics?

RQ 2 : What are the implications thereof for continuous vocational education and training?

Theoretical considerations on the relationships between technology and work characteristics are presented before the methods for searching, selecting and analyzing suitable studies are described. Regarding the results section, the structure is based on the three main steps of analyzing the included studies: First, the variables identified within the selected studies are clustered and defined in terms of work characteristics. Second, a comprehensive overview of evidence on the relationships between technologies and work characteristics is displayed. Third, the evidence is evaluated regarding the work demands that result from technologies changing work characteristics. Finally, the implications for CVET and future research as well as the limitations of this study will be discussed.

Theoretical Framework

In this section, a conceptualization of technology and theoretical assumptions on relationships between technology and work characteristics will be outlined. Research within various disciplines, such as sociology, management, economics, educational science, and psychology was considered to inform us on the role of technology within work. Completing this section, an overview of the various components of learning environments is provided to be used as a basis for the analyses of the empirical evidence.

Outlining Technology and Recent Technological Developments

A clear definition of technology often lacks in studies, what may be due to the fact that the word itself is an “equivoque” ( Weick, 1990 , p. 1) and a “repository of overlapping inconsistent meanings” ( McOmber, 1999 , p. 149). A suitable definition can be provided by analyzing what technologies actually “do” ( Autor et al., 2003 , p. 1,280). The primary goal of technology at work is to save or enhance labor in the form of work tasks, defined as “a unit of work activity that produces output” ( Autor, 2013 , p. 186). Technology can therefore be defined as mechanical or digital devices, tools or systems. These are used to replace work tasks or complement the execution of work tasks (e.g., McOmber, 1999 ; Autor et al., 2003 ). According to this view, technology is conceptualized according to “its status as a tool” (“instrumentality”; McOmber, 1999 , p. 141). Alternatively, technology is understood as “the product of a specific historical time and place,” reflecting a stage of development within a predefined historical process (“industrialization”; McOmber, 1999 , p. 143) or as the “newest or latest instrumental products of human imagination” (“novelty”; McOmber, 1999 , p. 143), reflecting its nature that is rapidly replacing and “outdating” its predecessors. The definition according to “instrumentality” is particularly suitable for this research, as the interest focuses on individual-level effects of technologies and its use for accomplishing work. Therefore, the technology needs to be mentioned explicitly (e.g., “robot” instead of “digital transformation”) and described specifically in the form with which the employee is confronted at the workplace. Different definitions may reflect different perspectives on the role of technology for society and work. These perspectives in the form of paradigmatic views ( Liker et al., 1999 ) include philosophical and cultural beliefs as well as ideas on organizational design and labor relations. They differ with regard to the complexity in which the social context is believed to determine the impact of technology on society. Listed in accordance to increasing social complexity, the impact may be determined by technology itself (i.e., “technological determinism”), established power relations (i.e., “political interest”), managerial decisions (i.e., “management of technology”), or the interaction between technology and its social context (i.e., “interpretivist”) ( Liker et al., 1999 ). Later research added an even more complex perspective, according to which the effects of technology on society and organizations are determined by the relations between the actors themselves (i.e., “sociomateriality”; Orlikowski and Scott, 2008 ). Paradigmatic views may guide research in terms of content, purpose and goals, which in turn is likely to affect the methods and approach to research and may be specific to disciplines. For instance, Marxist sociological research following the view of “political interest” or research in information systems following the view of “management of technology.”

New technological developments are widely discussed in various disciplines. For instance, Ghobakhloo (2018) summarizes the expected areas of application of various technological concepts within the “smart factory” in the manufacturing industry: The internet of things as an umbrella term for independent communication of physical objects, big data as procedure to analyse enormous amounts of data to predict the consequences of operative, administrative, and strategic actions, blockchain as the basis for independent, transparent, secure, and trustworthy transaction executed by humans or machines, and cloud computing as an internet-based flexible infrastructure to manage all these processes simultaneously ( Cascio and Montealegre, 2016 ; Ghobakhloo, 2018 ). The central question to guide the next section is to what extent these new technologies, and also well-established technologies such as information and communication technologies (ICT), which are constantly being expanded with new functions, could influence work characteristics on a theoretical basis.

Theories on the Relationships Between Technology and Work Characteristics

A central discussion on technology can be found in the sociological literature on deskilling vs. upgrading ( Heisig, 2009 ). The definition of “skill” in empirical studies on this subject varies regarding its content by describing either the level of complexity that an employee is faced with at work, or the level of autonomy that employees are able to make use of Spenner (1990) . Theories advocating the deskilling of work (e.g., labor process theory; Braverman, 1998 ) propose that technology is used to undermine workers' skill, sense of control, and freedom. Employees need to support a mechanized workflow under constant surveillance in order to maximize production efficiency ( Braverman, 1998 ). Other authors, advocating “upskilling” ( Blauner, 1967 ; Bell, 1976 ; Zuboff, 1988 ), propose the opposite by claiming that technology frees employee's from strenuous tasks, leaving them with more challenging and fulfilling tasks ( Francis, 1986 ). In addition, issues of identity at work were raised by Blauner (1967) who acknowledged that employees may feel “alienated” as soon as technologies change or substitute work that is meaningful to them, leaving them with a feeling of powerlessness, meaninglessness, or self-estrangement ( Shepard, 1977 ). In sum, sociological theories suggest that technology has an impact on the level of freedom, power and privacy of employees, determining their identity at work and the level of alienation they experience.

According to contingency theories ( Burns and Stalker, 1994 ; Liker et al., 1999 ) technology is a means to reduce uncertainty and increase competitiveness for organizations ( Parker et al., 2017 ). Therefore, the effects of technology on the employee depend on strategic decisions that fit the organizational environment best. When operational uncertainty is high, organizations get more competitive by using technology to enhance the flexibility of employees in order to enable a self-organized adaption to the changing environment ( Cherns, 1976 ). This increases employee's flexibility by allowing them to identify and decide on new ways to add value to the organization (“organic organization”; Burns and Stalker, 1994 ). When operational uncertainty is low, organizations formalize and standardize procedures in order to optimize the workflow and make outputs more calculable (“mechanistic organization”; Burns and Stalker, 1994 ). This leads to less opportunities for individual decision-making and less flexibility for the employees. In sum, contingency theories suggest, that the effects of technology depend on the uncertainty and competitiveness in the external environment and may increase or decrease employee's flexibility and opportunities for decision-making and self-organization.

Economic research following the task-based approach from Autor et al. (2003) suggests, that technology substitutes routine tasks and complements complex (or “non-routine”) ones. Routine manual and cognitive tasks usually follow a defined set of explicit rules, which makes them susceptible to automation. By analyzing qualification requirements in relation to employment rates and wage development, it was argued that workplace automation substitutes routine and low-skill tasks and thus favors individuals who can carry out high-skilled complex work due to their education and cognitive abilities ( Card and DiNardo, 2002 ; Autor et al., 2003 ). This means, that the accomplishment of tasks “demanding flexibility, creativity, generalized problem-solving, and complex communications” ( Autor et al., 2003 , p. 1,284) becomes more important. Complex tasks, so far, posed a challenge for automation, because they required procedural and often implicit knowledge ( Polanyi, 1966 ; Autor, 2015 ). However, recent technological developments such as machine learning, are capable of delivering heuristic responses to complex cognitive tasks by applying inductive thinking or big data analysis ( Autor, 2015 ). Regarding complex manual tasks, mobile robots are increasingly equipped with advanced sensors which enable them to navigate through dynamic environments and interactively collaborate with human employees ( Cascio and Montealegre, 2016 ). In sum, economic research following the task-based approach argues that technology affects the routineness and complexity of work by substituting routine tasks. However, new technologies may be able to increasingly substitute and complement not only routine tasks, but complex tasks as well. According to the theories, this will again increase the complexity of work by creating new demands for problem-solving and reviewing the technology's activity.

Useful insights can be gained from psychological theories that explicitly take the role of work characteristics into account. Work characteristics are often mentioned by for instance sociological theories (e.g., autonomy and meaningfulness) without clearly defining the concepts. Particularly the job characteristics model of Hackman and Oldham (1975) and the job-demand-control model of Karasek (1979) and Karasek et al. (1998) are consulted to further clarify the meaning of autonomy and meaningfulness at work. With regard to autonomy, Hackman and Oldham's model 1975 conceptualizes autonomy as a work characteristic, defined as “the degree to which the job provides substantial freedom, independence, and discretion to the employee in scheduling the work and in determining the procedures to be used in carrying it out” ( Hackman and Oldham, 1975 , p. 162). According to the authors, autonomy facilitates various work outcomes, such as motivation and performance. In a similar vein, Karasek et al. (1998) stress the role of autonomy in the form of “decision authority” that interacts with more demanding work characteristics, such as workload or frequent interruptions and therefore enables a prediction of job strain and stress ( Karasek et al., 1998 ). With regard to meaningfulness, Hackman and Oldham (1975) clarify that different core job dimensions, such as the significance of one's own work results for the work and lives of other people, the direct contribution to a common goal with visible outcomes, and the employment of various skills, talents and activities all enhance the perception of meaningfulness at work. In sum, psychological theories on employee motivation and stress clarify the concepts of autonomy and meaningfulness by illustrating the factors that contribute to their experience in relation to challenging and rewarding aspects of work.

Components of CVET

In order to formulate the implications for CVET of the studied effects of technology on work characteristics, a framework with the different components of CVET is needed. The objective of the VET system and continuous education is to qualify people by supporting the acquirement of required competences, for instance by providing training. Competences refer to the potential capacity of an individual in order to successfully carry out work tasks ( Ellström, 1997 ). They contain various components such as work-related knowledge and social skills (e.g., Sonntag, 1992 ). Competences are considered here as “the combination of knowledge, skills and attitude, in relation to one another and in relation to (future) jobs” ( Mulder and Baumann, 2005 , p. 106; e.g., Baartman and de Bruijn, 2011 ).

Participants in CVET enter the system with competences, such as prior knowledge, motivation, and expectations. It is argued that these have to be considered when designing learning environments for CVET. Next to making the distinction between the different components of learning environments content, guidance, method, and assessment, it is considered important that these components are coherent and consistent ( Mulder et al., 2015 ). For instance, the content of the training needs to fit to the objectives and the background of the participants. The same goes for the method or didactics used (e.g., co-operative learning, frontal instruction) and the guidance of teachers, mentors or trainers. In addition, assessment needs to be consistent with all these components. For instance, problem based learning or competence based training requires other forms of assessment than more classical teacher centered forms of didactics, which makes a classic multiple choice test not fitting ( Gulikers et al., 2004 ). Figure 1 contains an overview of the components of learning environments for CVET.

Figure 1 . Components of CVET learning environments (adapted from Mulder et al., 2015 , p. 501).

Three steps are necessary to answer the research questions. Firstly, a systematic search and review of empirical studies reporting evidence on the direct relationships between new technologies and work characteristics. Secondly, an analysis of the evidence with regard to its implications for work demands. Thirdly, deriving the work demands and their implications for CVET.

Systematic Search Strategy

Due to the interdisciplinary nature of our research, specific databases were selected for each of the disciplines involved: Business Source Premier (business and management research) and PsycArticles (psychology) were searched via EBSCOhost, and ERIC (educational science), and Sociological Abstracts (sociology) were searched via ProQuest.

Identifying suitable keywords for technological concepts is challenging due to the rapidly changing and inconsistent terminology and the nested nature of technological concepts ( Huang et al., 2015 ). Therefore, technological terms were systematically mapped by using the different thesauri provided by each of the chosen databases. After exploding a basic term within a thesaurus, the resulting narrower terms and related terms were documented and examined within the following procedure: (a) Checking the compatibility with our definition of technology reflecting its instrumentality, (b) Adjustment of keywords that are too broad or too narrow, (c) Disassembling nested concepts. The procedure was repeated stepwise for each of the databases. Finally, 45 terms that reflect new technologies were documented and used for the database search.

Keywords reflecting work characteristics are derived from the theoretical conceptualizations previously outlined. Synonyms for different concepts within the relevant theories were identified and included. In order to narrow our search results, additionally operators for empirical studies conducted in a workplace setting were added.

In order to avoid unnecessary redundancy, the use of asterisks was carefully considered, provided that the search results did not lose significantly in precision or the number of hits did not grow to an unmanageable number of studies. The final search string is shown in Table 1 .

Table 1 . Final search string.

Eligibility Criteria and Study Selection

Technical criteria included methodological adequacy. This was ensured by only including studies published in peer-reviewed journals. In addition, the studies had to provide quantitative or qualitative data on relationships between technology and work characteristics. Only English-language studies were considered, because most of the studies are published in English and therefore the most complete overview of the existing knowledge on this topic can be obtained. This also enables as many readers as possible to have access to the original studies and analyse the findings of the empirical studies themselves.

Concerning technology, variables had to express the direct consequence or interaction with a certain technology (e.g., the amount of computer-use or experience with robots in the workplace) and indirect psychological states that conceptually resulted from the presence of the technology (e.g., a feeling of increased expectations concerning availability). Regarding work characteristics, variables had to describe work-related aspects associated with our conceptualization of work characteristics (e.g., a change in flexibility or the perception of complexity).

Regarding the direction of effects, only studies that focused on the implementation or use of technologies for work-related purposes were included. Studies were excluded, if they (a) tested particular designs or features of technologies and evaluated them without considering effects on work characteristics, (b) regarded technology not as a specific tool but an abstract process (e.g., “digital transformation”), (c) were published before 1990 due to the fact that the extent of usability and usefulness of technologies before that time should be substantially limited compared to today (e.g., Gattiker et al., 1988 ), and (d) investigated the impact of technologies on society in general without a specific relation to professional contexts (e.g., McClure, 2018 ).

Studies that were found but that did not report empirical findings on the relationships between technology and work characteristics, but rather on the relationships between technology and work demands (e.g., specific knowledge or skills) or work outcomes (e.g., performance, job satisfaction) were documented. Since the aim for this study was to derive the work demands from the work characteristics in any case, the studies that reported a direct empirical relationship between technology and work demands were analyzed separately ( N = 7).

Data Extraction

The variables expressing technology and work characteristics were listed in a table, including the quantitative or qualitative data on the relationships. Pearson's r correlations were preferred over regression results to ensure comparability. For qualitative data, the relevant passages documenting data were included. Finally, methodological information as well as sample characteristics and size are listed.

Analysis of the Results

Firstly, the variables containing work-related aspects are clustered thematically into a comprehensive final set of work characteristics. This is necessary to reduce complexity due to variations in naming, operationalization and measurement and to make any patterns in the data more visible. Deviations from the theoretically expected clusters are noted and discussed before synthesizing the evidence narratively in accordance to the research questions ( Rodgers et al., 2009 ). As proposed, the evidence on changing work characteristics is analyzed with respect to the resulting work demands in the sense of knowledge, skills, attitude and behavior, which in turn are used to determine the implications for the different components of CVET.

Figure 2 depicts a flowchart documenting the literature search. In sum, 21 studies providing evidence on relationships between technology and work characteristics were included. In addition, seven supplementary studies containing empirical evidence on relationships between technology and specific work demands were identified. These studies are taken into account when deriving the work requirements. Next, the descriptive characteristics of the included studies will be reported. After that, the evidence on relationships between technologies and work characteristics of the 21 included studies will be summarized, before finally deriving the work demands based on the evidence found.

Figure 2 . Flowchart of literature search process.

Characteristics of Studies

Table 2 contains an overview of the characteristics of selected studies. Most of the studies were published between 2015 and 2019 (52%). Nearly half of the studies were conducted in Europe (48%), followed by North America (33%). Most of the studies reported qualitative data collected with methods such as interviews (62%).

Table 2 . Characteristics of the studies.

The studies investigated a variety of technologies, such as computers (1, 7), various forms of Information and Communication technologies (ICTs; 2, 3, 17, 18, 21) in a broad sense, including specific examples of work-extending technologies and other tools for digital communication, information technology (IT) systems supporting information dissemination and retrieval within organizations (4, 9), automated systems supporting predominantly physical work procedures (5, 6, 11, 12, 13, 14, 20), robots (15, 19), social media enabling professional networking and participation in organizational and societal practices (8, 16), and more domain-specific technologies such as clinical technology supporting professional decisions (9) and field technology for labor management (10).

Relationships Between Technology and Work Characteristics

In sum, nine work characteristics were identified and defined distinctively. Table 3 contains the operational definitions of the final work characteristics and the work-related aspects they consist of. The final work characteristics are: Workflow interruptions, workload, manual work, mental work, privacy, autonomy, complexity, role expectations, and opportunities for development.

Table 3 . Overview for final work characteristics and the exemplary work-related aspects assigned to them.

The complete overview of the selected studies and results for the relationships between technology and work characteristics is provided in Table 4 (for quantitative data) and Table 5 (for qualitative data). To further increase comprehensibility, the variables within the tables were labeled according to their function in the respective study (e.g., independent variable, mediating variable, dependent variable; see notes).

Table 4 . Studies providing quantitative evidence for the relationship between technology and work-related aspects.

Table 5 . Studies providing qualitative evidence for the relationship between technology and work-related aspects.

There is quantitative evidence on positive relationships between IT system use and complexity reported by two studies (4, 9). On a similar note, qualitative evidence suggests lower situational awareness within automated systems indicating an increase in complexity (12), and clinical technology being associated with an increase in complexity for nurses (9).

There is mixed quantitative evidence on the relationships between computer work and autonomy (1). The amount of computer work is positively related to autonomy, while technological pacing is negatively related to autonomy. Working within automated systems is negatively (5, 6) or not related (6) to different measures of autonomy. ICT use shows mixed relationships with job decision latitude (3) depending on ICT features that describe negative or positive effects of use. Evidence indicates a positive relationship between social media use and autonomy. Qualitative evidence suggests that ICT use increases autonomy (21) and flexibility (17, 18, 21).

Quantitative studies indicate strong positive relationships between computer work (1) and ICT use (2) and workload. The relationships are not consistent due to the fact that certain ICT features differ in their effects on workload. ICT characteristics such as presenteeism and pace of change are positively related to feelings of increasing workload, while a feeling of anonymity is negatively associated with workload. Evidence indicates positive relationships between time or workload pressure in the context of computer work (7), working in an automated system (5), as well as social media use (8) and provide evidence for positive relationships between various technologies and workload. Qualitative studies report similar outcomes. ICT use (18), automated systems (12, 13) as well as clinical technology (9) are reported to increase the workload.

Workflow Interruptions

Quantitative evidence indicates positive relationships between computer work and increasing levels of interruptions as well as an increasing demand for multitasking (7). Qualitative evidence suggests that ICT use is positively associated with an increased level of interruptions on the one hand and workflow support on the other hand (21). Further qualitative evidence suggests that robots at the workplace have positive effects on workflow support (19), and automated systems seem to increase the level of multitasking required in general (12).

Manual Work

Qualitative evidence suggests a decrease in the amount of physically demanding tasks when working with automated systems (11) and robots (15). In one study, qualitative evidence suggests an increase in manual work for technical jobs where automated systems are used (14).

Mental Work

Quantitative evidence indicates no relationships between monitoring tasks or problem-solving demands for technical jobs within automated systems (6). Qualitative evidence however suggests positive relationships between work within automated systems and various cognitive tasks and demands, such as problem-solving and monitoring (11, 13), while working with robots increases the amount of new and challenging mental tasks (15).

Quantitative evidence indicates that different ICT characteristics show different relationships with invasion of privacy (2). Some features are negatively related to invasion of privacy (anonymity) and others are positively related to it (presenteeism, pace of change). Qualitative evidence suggests that IT systems are not related to the perception of managerial surveillance (9), while social media is positively related to peer-monitoring (16), and field technology is negatively related to employee data control (10).

Role Expectations

Quantitative evidence indicates that ICT use is inconsistently related to role ambiguity depending on specific characteristics of the technology (2). Regarding automated systems, quantitative evidence indicates no relationship between working in an automated system and opportunities for role expansion in the form of an increased perceived responsibility (6). Qualitative evidence suggests that ICT use increases the expectations for availability and connectivity (21), and social media positively affects networking pressure (16). Qualitative evidence suggests that IT systems (9) decrease meaningful job content and role expansion. Qualitative evidence suggests that automated systems vary with regard to enhancing meaningfulness at work, dependent on whether the work tasks are complemented by the system or revolve around maintaining the system (20).

Opportunities for Development

Qualitative evidence suggests that ICT use (12) as well as working with an automated system (17) increase the demands for continuing qualification. Qualitative evidence suggests that opportunities for learning and development are prevalent with clinical technology (9) and absent when working with robots (19). Mixed qualitative evidence regarding automated systems and learning opportunities suggests that the effects depend on the differences in work roles in relation to being supported by the system or supporting the system (20).

A comprehensive summary of the outcomes can be found in Table 6 . The information in this table gives a summary of the evidence found for the different technologies and their relationships to work characteristics, more specifically to work related aspects. Important distinctive characteristics such as sample characteristics are listed in Tables 4 , 5 .

Table 6 . Overview over identified relationships between technology and work characteristics.

Subsequently, the results shown are now used as a basis for the identification of work demands that lead to the need for adapting to changes in work characteristics.

Relationships Between Technologies and Work Demands

Three sources are considered for the identification of work demands: Work demands mentioned in the studies on technology and work characteristics, work demands mentioned by the supplementary studies found during the database search ( N = 7), and work demands analytically derived from the results.

Some studies that examined the effects of technology on work characteristics also reported concrete work demands. Regarding the increasing complexity and the associated mental work, qualitative evidence suggests an increasing demand for cognitive as well as digital skills (11) in automated systems. With regard to IT systems, quantitative evidence indicates positive relationships with computer literacy (9), and analytical skills (4). With regard to the increase in workflow interruptions and the role expectations for constant availability and connectivity, time and attention management strategies are proposed in order to cope with the intrusive features of technology (2). Other strategies mentioned in the studies include self-discipline for disengaging from the ubiquitous availability resulting from mobile communication devices (18, 8) as well as the need for reflecting on individual responsiveness when working overtime due to self-imposed pressure to be available at all times (18, 21). Concerning opportunities for development, the willingness and ability to learn and adapt to technological changes and the associated changes in work (15, 4, 12) is emphasized. Moreover, employability is facilitated by using technological tools for professional networking (16).

The supplementary studies provide evidence on the direct relationships between technologies and work demands without the mediating consideration of work characteristics. This evidence is listed in Table 7 .

Table 7 . Supplementary studies on the relationship between technology and work-related demands.

There is quantitative evidence for positive relationships between the perception of controllability and exploratory use of computers (22), first-hand experience with robots and readiness for robotization (23, 24), and perceived usefulness and positive attitudes toward telemedicine technology (25), blockchain technology (26), and IT systems in general (27). Further quantitative evidence indicates mixed effects of perceived ease of use. Evidence indicates a positive relationship between perceived ease of use and perceived technological control with regard to telemedicine (25), no relationship between ease of use and attitude regarding blockchain technology (26), and a positive relationship between ease of use and attitude toward using IT systems (27). Quantitative evidence indicates that information processing enabled by technology is positively related to an increasing demand of cognitive skills (e.g., synthesizing and interpreting data) and interpersonal skills (e.g., coordinating and monitoring other people), but not related to an increasing demand in psychomotor skills (e.g., manual producing and precise assembling) (28). The level of standardization of work is positively related to interpersonal skills, but not related to cognitive and psychomotor skills (28). A high variety of tasks is positively related to the demand for cognitive skills and interpersonal skills and not related to psychomotor skills (28).

By analyzing the evidence on relationships between technology and work characteristics, further work demands can be derived. Knowledge about the specific technology at hand may be useful to decrease the perception of complexity as new technologies are introduced. This seems evident when comparing the effects of a simple computer with the effects of work within an automated system. For instance, while evidence indicates no relationship between computer work and complexity (6), work within an automated system is suggested to be associated with increasing complexity (12). Moreover, problem-solving skills (13) and cognitive skills such as diagnosing and monitoring (11, 15) increase when employees work within automated systems. Increasing autonomy suggests the need for personal skills regarding self-organizing and self-management due to greater flexibility and the associated possibilities for structuring work in many ways, particularly when working with ICTs (18, 21). Workflow interruptions and an increasing workload also increases the importance of communication skills for explicating the boundaries of one's own engagement to colleagues and leaders (17, 18, 21). Furthermore, reflecting the professional role at work may be critical due to changes in role expectations. The example of self-imposed need for availability underlines this argument (21). All this has implications for self-regulatory activities, such as reflection, and could benefit from experimenting and monitoring one's own strategies for time and attention management.

Implications for CVET: Objectives and Characteristics

The aforementioned studies describe several required behavioral aspects that are considered important due to technology at work. Emphasized is the need for components related to the organization of one's own work, namely self-discipline and time and attention management.

The identified need for reflection on one's own professional actions, for experimentation, and also for professional networking (for instance by using tools) can be seen as parts of further professional development by oneself or in interaction with others. In addition, the need for demonstrating employability is mentioned. From all these professional and career development aspects can be derived that problem-solving skills, self-regulation skills, and communication skills are required as well as proactive work behavior and coping and reflection strategies.

Various relevant skills, such as psychomotor skills, analytical skills, management skills, and interpersonal skills are mentioned. In addition, the need for diagnostic and monitoring skills as well as digital skills is emphasized. All these components can be used in relation to two explicitly mentioned needs: ability to learn and computer literacy. The demand for generic and transferable skills is emphasized. As a basis for the skills, knowledge is required, for instance on the technology itself, although not explicitly discussed in the studies. In contrast, several components of attitude are explicitly mentioned and considered to be a requirement for the ability to deal with challenges caused by new technologies at work. Firstly, the more generic willingness to learn, adaptability, and perceived behavioral control. Secondly, attitudes that are directly linked to technology, namely a positive attitude and trust, especially toward technology (e.g., robots), and technological readiness and acceptance.

Next to the opportunity of acquiring the mentioned components of competences at work, CVET can organize training interventions in the form of adequate learning environments to foster these. The ability of employees to carry out, develop and use the mentioned behavioral aspects, skills, knowledge, and attitudes, can be considered as required objectives of CVET and have concrete consequences for the characteristics of the learning environments.

As for the content of the learning environments, derived from the aforementioned requirements, it can be argued that attention should be paid to different categories of learning objectives: acquiring knowledge about and learning how to use technology, how to manage work and oneself, and how to continue one's own professional development. In addition, the relevance of attitude tells us that these components need to be fostered in the training and therefore need to be part of the content of the learning environments as well.

In relation to the methods or the didactics, only one study explicitly mentioned a suggestion, namely experience based learning for fostering adaptability (12). In relation to the guidance of trainers or teachers no suggestions are provided. The same goes for assessment, diagnoses or monitoring, and the coherence of components of the learning environments.

This systematic literature review aimed at identifying effects of new technological developments on work characteristics, identifying associated work demands, and determining their implications for the design of formal CVET learning environments.

Effects of New Technologies on Work Characteristics and Word Demands

Based on a systematic review focusing on empirical evidence, several effects of technology on work characteristics were found, thus answering RQ 1. Evidence suggests that complexity and mental work increases with ongoing automation and robotization of work, for instance due to the automatization of procedures which “hides” certain processes from employees. The automatization of tasks introduces new mental tasks, such as monitoring the machine's activities and solving problems. A decrease in manual work depends on the relation between the job and the technology in use (supporting vs. being supported).

Workload and workflow interruptions increase as a general consequence of the ubiquity of technology, mainly due to a higher level of job speed and the associated time and workload pressure. A higher level of autonomy seems to be associated with a higher workload and more workflow interruptions. This applies in particular to work with ICTs and domain-specific technologies, such as field technology.

Role expectations and opportunities for development depend on the relation between the job and the technology in use (supporting vs. being supported). With regard to role expectations, the need for being available or connected via digital devices and a new division of responsibilities between employees and technology are repeatedly mentioned in the studies. This applies particularly to work with automated systems, robots, and domain-specific technologies such as clinical technology.

With regard to work demands, employees need strategies to deal with higher levels of workload, autonomy, and complexity. Required skill demands contain mental, analytical, cognitive, and self-regulatory demands. In addition, opportunities for role expansion and learning, which do not seem to automatically result from the implementation and use of new technologies, need to be created (pro)actively by the employees. Employees need to take more responsibility with regard to their own development and professional work identity (for instance considering the pressure for constant availability). They need to be able to effectively deal with a high workload and number of interruptions, increasing flexibility, complexity, and autonomy, a demand for constant availability, changes in meaningfulness of tasks, changes in work roles, and the need to create and use learning opportunities. In the light of ongoing changes and challenges, skills to further develop and adapt one's own skills gain in importance. Regarding attitudes, the willingness to learn, adapt and experiment may be a central work demand.

Implications for the Practice of CVET

Various required objectives of CVET can be concluded from the reported results. For instance, developing the ability of employees to carry out the mentioned behaviors, as well as the skills, knowledge and attitudes that are necessary for those behaviors. These objectives have consequences for the content of CVET learning environments. From the empirical studies on the relationships between technology and work, we derived the need for employees to organize their own work, for instance through time management. Furthermore, many issues relating to own professional development and career development are important, to acquire individually and independently as well as by interacting with others. Ultimately, this refers to the skills of self-initiated learning and development. With regard to fostering helpful attitudes, raising awareness of the relevance of trust or training the social skills to promote trust in the workplace can be included in the content of CVET learning environments. In research on creating trust within organizations, regularly giving and receiving relevant information was shown to be important for creating trust toward co-workers, supervisors and top-management, which in turn fostered the perception of organizational openness and employee involvement as a result ( Thomas et al., 2009 ). In the research on creating trust in virtual teams, the importance of frequent interaction was important to develop trust on a cognitive as well as an affective level (e.g., Germain, 2011 ). These research results however need to be adapted to the context of technology at work.

Although there is no information provided on the guidance of employees, informal guidance through leadership ( Bass and Avolio, 1994 ) as well as formal guidance by trainers and teachers during interventions contain possibilities for fostering the required competences. Attention should be paid not only to acquiring relevant knowledge (digital literacy), but also to skills in applying the knowledge and therefore dealing with technology. Even more challenging might be the task of supporting attitude development (e.g., technological acceptance and openness to changes), fostering transfer of skills, and preparation for future development. Especially future professional development, which includes the ability to learn in relation to current and future changes, needs to be focused on. Teachers, trainers and mentors need to be equipped to be able to foster these competences.

In relation to the use of didactical methods, methods that do not merely focus on knowledge acquisition but also provide opportunities for skill acquisition and changes in attitude need to be applied. For example, one study explicitly suggested experience based learning for fostering the adaptability of employees when faced with ongoing technological developments. Other solutions for instruction models as a profound basis for learning environments may be found in more flexible approaches, for instance according to the cognitive flexibility theory ( Spiro et al., 2003 ), where learners are meant to find their own learning paths in ill-structured domains. By applying such models, that are often based on constructivist learning theories, in a coherent way, the development of strategies for self-organizing and self-regulation may be facilitated.

Furthermore, the use of technology within learning environments may have the potential to increase participants interactions, which are focused in for instance collaborative and co-operative learning ( Dillenbourg et al., 2009 ). Next to increasing interactions in learning and being able to co-operate, technology in learning environments can used to foster the other required competences, if adequately designed ( Vosniadou et al., 1996 ; Littlejohn and Margaryan, 2014 ).

When keeping in mind, that the coherence of components is an important requirement for the design of learning environments ( Mulder et al., 2015 ), the component that describes assessment needs further attention. There is evidence supporting the idea, that the type of assessment has an impact on how learning takes place ( Gulikers et al., 2004 ; Dolmans et al., 2005 ). Therefore, it can be used to deliberatively support and direct learning processes.

Only when all these aspects are considered can CVET interventions effectively and sustainably foster the mentioned objectives, such as promoting a willingness to change in relation to technologies, the effective use of technology, and personal development in the context of technological developments.

Limitations and Implications for Future Research

Regarding the search methods, the use of databases is challenging when investigating technologies ( Huang et al., 2015 ). Technological and technical terms are widespread outside the research in which they are regarded as the object of investigation. Therefore, it produces a large amount of studies that concern technology with diverse research objectives that can be difficult to sort. An interesting focus for future research would be the systematic mapping of journals dealing specifically with technology in order to identify research that could complement the results of the present study as well as consider specificities regarding the domains in which the data is collected and disciplines by which the research is conducted. For instance, domain-specific databases from healthcare or manufacturing might provide additional insights into the effects of technology on work. Another limitation is the absence of innovative new technologies, such as artificial intelligence, blockchain, or the internet of things as object of investigation. Broad technological categories, such as ICTs and social media have received some attention in research, especially in relation to questions beyond the scope of this review. Newer technological developments as discussed by Ghobakhloo (2018) are virtually not present in current research. This gap in empirical research needs to be filled. In addition, future research should ensure that it does not miss opportunities for research where effects of these innovative technologies can be examined in detail, for instance by conducting an accompanying case study of the implementation process. Research investigating changes over time regarding the use of technology and its effects is needed. In doing so, research could capture the actual dynamics of change and development of processes as they happen in order to inform truly effective interventions in practice. Moreover, a classification of technological characteristics according to their effects may be valuable by enabling a more in-depth analysis of new technologies and their effects on specific groups of employees and different types of organizations. These analyses will also allow a breakdown of effects in relation to differences in jobs, hierarchy levels and levels of qualification, which could be very important for organizations and employers in order to adapt the CVET strategy to the specific demands of specific groups of employees. The present review takes a first step in this direction by identifying work characteristics that are affected by different technologies. In addition, future research could also take into account non-English language research, which might increase insight in for instance cultural differences in the use and the effects of technology at work.

Regarding theory, some of the relevant theories considering technology stem from sociology (e.g., Braverman, 1998 ) or economics ( Autor et al., 2003 ). For instance, the task-based approach ( Autor et al., 2003 ) showed some explanatory value by suggesting that complexity may increase as a consequence of technology. Furthermore, it suggested that this effect may depend on job specifics. Those propositions are reflected in the aforementioned empirical evidence. Psychological theories on work characteristics do not conceptualize technology explicitly (e.g., Hackman and Oldham, 1975 ; Karasek, 1979 ). As of the present study, the large variation regarding the concepts and variables derived from theory might limit the comparability of results. To foster systematic research, further theory development needs to more explicitly consider the role of technology at multiple levels (i.e., individual level, team level, organizational level) and with regard to the characteristics and demands of work. In the context of theory, the paradigmatic views also deserve attention (e.g., Liker et al., 1999 ; Orlikowski and Scott, 2008 ). These views could be reflected in the subject of research, as exemplified for instance in the study of field technologies and its effects on privacy from a managerial control and power perspective, potentially reflecting the view of political interest ( Tranvik and Bråten, 2017 ). Most of the studies, however, do not take a clear stand on what exactly they mean when they investigate technology. This complicates interdisciplinary inquiry and integration, as it is not always clear which understanding of technology is prevalent. We therefore encourage future research to explicitly define technology, for instance as in the present paper using the proposed framework of McOmber (1999) . In doing so, characteristics of technology may be defined more clearly and distinctive which in turn would enable the formation of the strongly needed categorization of technologies, as was proposed earlier.

And, although there are theories and models on the use of technology in education (e.g., E-Learning, Technology enhanced learning), they are not focussing on fostering the competences required to deal with new technologies in a sustainable manner. In general, the same gap needs to be filled for instruction models and instructional design models, for instance to promote changes in attitude and professional development. In addition, there is hardly any attention for the consequences of new technologies at work for CVET yet ( Harteis, 2017 ). All this requires more systematic evaluation studies. The research gaps identified need to be filled in order to provide evidence-based support to employees in dealing with new technologies at work in a sustainable manner, taking charge of their own performance and health, as well as seeking and using opportunities for their own professional and career development.

Data Availability Statement

All datasets generated for this study are included in the article/supplementary material.

Author Contributions

PB and RM have jointly developed the article, and to a greater or lesser extent both have participated in all parts of the study (design, development of the theoretical framework, search, analyses, and writing). The authors approved this version and take full responsibility for the originality of the research.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

* Amick, B. C., and Celentano, D. D. (1991). Structural determinants of the psychosocial work environment: introducing technology in the work stress framework. Ergonomics 34, 625–646. doi: 10.1080/00140139108967341

PubMed Abstract | CrossRef Full Text | Google Scholar

Autor, D. H. (2013). The “task approach” to labor markets: an overview. J. Labour Market Res. 46, 185–199. doi: 10.1007/s12651-013-0128-z

CrossRef Full Text | Google Scholar

Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. J. Econ. Perspect. 29, 3–30. doi: 10.1257/jep.29.3.3

Autor, D. H., Levy, F., and Murnane, R. J. (2003). The skill content of recent technological change: an empirical exploration. Q. J. Econ. 118, 1279–1333. doi: 10.1162/003355303322552801

* Ayyagari, R., Grover, V., and Purvis, R. (2011). Technostress: technological antecedents and implications. MIS Q. 35, 831–858. doi: 10.2307/41409963

Baartman, L. K. J., and de Bruijn, E. (2011). Integrating knowledge, skills and attitudes: conceptualising learning processes towards vocational competence. Educ. Res. Rev. 6, 125–134. doi: 10.1016/j.edurev.2011.03.001

Bass, B. M., and Avolio, B. J. (1994). Transformational leadership and organizational culture. Int. J. Public Administr. 17, 541–554. doi: 10.1080/01900699408524907

Bell, D. (1976). The coming of the post-industrial society. Educ. Forum 40, 574–579. doi: 10.1080/00131727609336501

Blauner, R. (1967). Alienation and Freedom: The Factory Worker and His Industry. Oxford: Chicago University of Press.

Google Scholar

* Bordi, L., Okkonen, J., Mäkiniemi, J.-P., and Heikkilä-Tammi, K. (2018). Communication in the digital work environment: implications for wellbeing at work. NJWLS 8, 29–48. doi: 10.18291/njwls.v8iS3.105275

Braverman, H. (1998). Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century. New York, NY: Monthly Review Press.

Brynjolfsson, E., and McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York, NY: Norton.

Burns, T., and Stalker, G. M. (1994). The Management of Innovation. Oxford: Oxford University Press.

* Calitz, A. P., Poisat, P., and Cullen, M. (2017). The future African workplace: the use of collaborative robots in manufacturing. SA J. Hum. Resour. Manag. 15, 1–11. doi: 10.4102/sajhrm.v15i0.901

Card, D., and DiNardo, J. E. (2002). Skill-biased technological change and rising wage inequality: some problems and puzzles. J. Labor Econ. 20, 733–783. doi: 10.1086/342055

Cascio, W. F., and Montealegre, R. (2016). How technology is changing work and organizations. Annu. Rev. Organ. Psychol. Organ. Behav. 3, 349–375. doi: 10.1146/annurev-orgpsych-041015-062352

** Chau, P. Y.K., and Hu, P. J.-H. (2002). Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories. Inform. Manage. 39, 297–311. doi: 10.1016/S0378-7206(01)00098-2

* Chen, W., and McDonald, S. (2015). Do networked workers have more control? The implications of teamwork, telework, ICTs, and social capital for job decision latitude. Am. Behav. Sci. 59, 492–507. doi: 10.1177/0002764214556808

Cherns, A. (1976). The principles of sociotechnical design. Hum. Relations 29, 783–792. doi: 10.1177/001872677602900806

* Chesley, N. (2014). Information and communication technology use, work intensification and employee strain and distress. Work Employ. Soc. 28, 589–610. doi: 10.1177/0950017013500112

** Chow, S. K., Chin, W.-Y., Lee, H.-Y., Leung, H.-C., and Tang, F.-H. (2012). Nurses' perceptions and attitudes towards computerisation in a private hospital. J. Clin. Nurs. 21, 1685–1696. doi: 10.1111/j.1365-2702.2011.03905.x

Dillenbourg, P., Järvela, S., and Fischer, F. (2009). “The evolution of research on computer-supported collaborative learning: from design to orchestration,” in Technology-Enhanced Learning , ed N. Balacheff, S. Ludvigsen, T. de Jong, A. Lazonder, and S. Barnes (Dordrecht: Springer Netherlands), 3–19.

Dolmans, D. H., De Grave, W., Wolfhagen, I. H., and van der Vleuten, C. P. (2005). Problem-based learning: future challenges for educational practice and research. Med. Educ. 39, 732–741. doi: 10.1111/j.1365-2929.2005.02205.x

* Dvash, A., and Mannheim, B. (2001). Technological coupling, job characteristics and operators' well-being as moderated by desirability of control. Behav. Inform. Technol. 20, 225–236. doi: 10.1080/01449290116930

Ellström, P.-E. (1997). The many meanings of occupational competence and qualification. J. Euro Industr. Train. 21, 266–273. doi: 10.1108/03090599710171567

* Findlay, P., Lindsay, C., McQuarrie, J., Bennie, M., Corcoran, E. D., and van der Meer, R. (2017). Employer choice and job quality. Work Occupat. 44, 113–136. doi: 10.1177/0730888416678038

Ford, M. (2015). Rise of the Robots: Technology and the Threat of a Jobless Future. New York, NY: Basic Books.

Francis, A. (1986). New Technology at Work. Oxford: Clarendon Press.

Frey, C. B., and Osborne, M. A. (2017). The future of employment: how susceptible are jobs to computerisation? Technol. Forecast. Soc. Change 114, 254–280. doi: 10.1016/j.techfore.2016.08.019

Gattiker, U. E., Gutek, B. A., and Berger, D. E. (1988). Office technology and employee attitudes. Soc. Sci. Comp. Rev. 6, 327–340. doi: 10.1177/089443938800600301

* Gekara, V. O., and Thanh Nguyen, V.-X. (2018). New technologies and the transformation of work and skills: a study of computerisation and automation of Australian container terminals. N. Technol. Work Employ. 33, 219–233. doi: 10.1111/ntwe.12118

Germain, M.-L. (2011). Developing trust in virtual teams. Perf. Improvement Q. 24, 29–54. doi: 10.1002/piq.20119

** Ghani, J. A., and Deshpande, S. P. (1994). Task characteristics and the experience of optimal flow in human—computer interaction. J. Psychol. 128, 381–391. doi: 10.1080/00223980.1994.9712742

Ghobakhloo, M. (2018). The future of manufacturing industry: a strategic roadmap toward industry 4.0. J. Manuf. Tech. Manage. 29, 910–936. doi: 10.1108/JMTM-02-2018-0057

* Gough, R., Ballardie, R., and Brewer, P. (2014). New technology and nurses. Labour Industry 24, 9–25. doi: 10.1080/10301763.2013.877118

Gulikers, J. T. M., Bastiaens, T. J., and Kirschner, P. A. (2004). A five-dimensional framework for authentic assessment. ETR&D 52, 67–86. doi: 10.1007/BF02504676

Hackman, J. R., and Oldham, G. R. (1975). Development of the job diagnostic survey. J. Appl. Psychol. 60, 159–170. doi: 10.1037/h0076546

Harteis, C. (2017). “Machines, change and work: an educational view on the digitalization of work,” in The Impact Digitalization in the Workplace: An Educational View , ed C. Harteis (New York: Springer), 1–10.

Heisig, U. (2009). “The deskilling and upskilling debate,” in International Handbook of Education for the Changing World of Work: Bridging Academic and Vocational Learning , ed R. Maclean and D. Wilson (Dordrecht: Springer Netherlands), 1639–1651.

* Holden, R. J., Rivera-Rodriguez, A. J., Faye, H., Scanlon, M. C., and Karsh, B.-T. (2013). Automation and adaptation: Nurses' problem-solving behavior following the implementation of bar coded medication administration technology. Cognition Technol. Work 15, 283–296. doi: 10.1007/s10111-012-0229-4

Huang, Y., Schuehle, J., Porter, A. L., and Youtie, J. (2015). A systematic method to create search strategies for emerging technologies based on the Web of Science: illustrated for ‘Big Data’. Scientometrics 105, 2005–2022. doi: 10.1007/s11192-015-1638-y

* James, K. L., Barlow, D., Bithell, A., Hiom, S., Lord, S., Oakley, P., et al. (2013). The impact of automation on pharmacy staff experience of workplace stressors. Int. J. Pharm. Pract. 21, 105–116. doi: 10.1111/j.2042-7174.2012.00231.x

** Kamble, S., Gunasekaran, A., and Arha, H. (2019). Understanding the Blockchain technology adoption in supply chains-Indian context. Int. J. Product. Res. 57, 2009–2033. doi: 10.1080/00207543.2018.1518610

Karasek, R., Brisson, C., Kawakami, N., Houtman, I., Bongers, P., and Amick, B. (1998). The Job Content Questionnaire (JCQ): an instrument for internationally comparative assessments of psychosocial job characteristics. J. Occupat. Health Psychol. 3, 322–355. doi: 10.1037/1076-8998.3.4.322

Karasek, R. A. (1979). Job demands, job decision latitude, and mental strain: implications for job redesign. Administr. Sci. Q. 24, 285–308. doi: 10.2307/2392498

* Körner, U., Müller-Thur, K., Lunau, T., Dragano, N., Angerer, P., and Buchner, A. (2019). Perceived stress in human-machine interaction in modern manufacturing environments-results of a qualitative interview study. Stress Health 35, 187–199. doi: 10.1002/smi.2853

* Kraan, K. O., Dhondt, S., Houtman, I. L.D., Batenburg, R. S., Kompier, M. A.J., and Taris, T. W. (2014). Computers and types of control in relation to work stress and learning. Behav. Inform. Technol. 33, 1013–1026. doi: 10.1080/0144929X.2014.916351

Liker, J. K., Haddad, C. J., and Karlin, J. (1999). Perspectives on technology and work organization. Annu. Rev. Sociol. 25, 575–596. doi: 10.1146/annurev.soc.25.1.575

Littlejohn, A., and Margaryan, A., (eds.). (2014). Technology-Enhanced Professional Learning: Processes, Practices and Tools. New York, NY: Routledge.

* Marler, J. H., and Liang, X. (2012). Information technology change, work complexity and service jobs: a contingent perspective. N. Technol. Work Employ. 27, 133–146. doi: 10.1111/j.1468-005X.2012.00280.x

McClure, P. K. (2018). ‘You're Fired,’ says the robot: the rise of automation in the workplace, technophobes, and fears of unemployment. Soc. Sci. Comput. Rev. 36, 139–156. doi: 10.1177/0894439317698637

McOmber, J. B. (1999). Technological autonomy and three definitions of technology. J. Commun. 49, 137–153. doi: 10.1111/j.1460-2466.1999.tb02809.x

Mulder, R. H., and Baumann, S. (2005). “Competencies of in-company trainers,” in Bridging Individual, Organisational, and Cultural Aspects of Professional Learning , eds H. Gruber, C. Harteis, R. H. Mulder, and M. Rehrl (Regensburg: S. Roderer Verlag), 105–109.

Mulder, R. H., Messmann, G., and König, C. (2015). Vocational education and training: researching the relationship between school and work. Eur. J. Educ. 50, 497–512. doi: 10.1111/ejed.12147

* Ninaus, K., Diehl, S., Terlutter, R., Chan, K., and Huang, A. (2015). Benefits and stressors - perceived effects of ICT use on employee health and work stress: an exploratory study from Austria and Hong Kong. Int. J. Qual. Stud. Health Well Being 10:28838. doi: 10.3402/qhw.v10.28838

Orlikowski, W. J., and Scott, S. V. (2008). 10 sociomateriality: challenging the separation of technology, work and organization. ANNALS 2, 433–474. doi: 10.1080/19416520802211644

Parker, S. K., van den Broeck, A., and Holman, D. (2017). Work design influences: a synthesis of multilevel factors that affect the design of jobs. Acad. Manage. Ann. 11, 267–308. doi: 10.5465/annals.2014.0054

Polanyi, M. (1966). The Tacit Dimension. New Work, NY: Doubleday.

Roblek, V., Meško, M., and KrapeŽ, A. (2016). A complex view of industry 4.0. SAGE Open 6:215824401665398. doi: 10.1177/2158244016653987

Rodgers, M., Sowden, A., Petticrew, M., Arai, L., Roberts, H., Britten, N., and Popay, J. (2009). Testing methodological guidance on the conduct of narrative synthesis in systematic reviews. Evaluation 15, 49–73. doi: 10.1177/1356389008097871

Schwab, K. (2017). The Fourth Industrial Revolution. London: Portfolio Penguin.

Shepard, J. M. (1977). Technology, alienation, and job satisfaction. Ann. Rev. Sociol. 3, 1–21.

Sonntag, K. (1992). Personalentwicklung in Organisationen [Human Resource Development in Companies. Psychological Basics, Methods, and Strategies]. Göttingen: Verlag für Psychologie.

** Spell, C. S. (2001). Organizational technologies and human resource management. Hum. Relat. 54, 193–213. doi: 10.1177/0018726701542003

Spenner, K. I. (1990). Skill: meanings, methods, and measures. Work Occupat. 17, 399–421. doi: 10.1177/0730888490017004002

Spiro, R. J., Collins, B. P., Thota, J. J., and Feltovich, P. J. (2003). Cognitive flexibility theory: hypermedia for complex learning, adaptive knowledge application, and experience acceleration. Educ. Technol. 43, 5–10. Available online at: https://www.jstor.org/stable/44429454 (accessed April 28, 2020).

Thomas, G. F., Zolin, R., and Hartman, J. L. (2009). The central role of communication in developing trust and its effect on employee involvement. J. Bus. Commun. 46, 287–310. doi: 10.1177/0021943609333522

* Towers, I., Duxbury, L., Higgins, C., and Thomas, J. (2006). Time thieves and space invaders: technology, work and the organization. J. Org. Change Manage. 19, 593–618. doi: 10.1108/09534810610686076

* Tranvik, T., and Bråten, M. (2017). The visible employee - technological governance and control of the mobile workforce. Socio Econ. Stud. 28, 319–337. doi: 10.5771/0935-9915-2017-3-319

** Turja, T., and Oksanen, A. (2019). Robot acceptance at work: a multilevel analysis based on 27 EU countries. Int. J. Soc. Robot. 11, 679–689. doi: 10.1007/s12369-019-00526-x

** Turja, T., Taipale, S., Kaakinen, M., and Oksanen, A. (2019). Care workers' readiness for robotization: identifying psychological and socio-demographic determinants. Int. J. Soc. Robot. 4:67. doi: 10.1007/s12369-019-00544-9

* van Zoonen, W., and Rice, R. E. (2017). Paradoxical implications of personal social media use for work. N. Technol. Work Employ. 32, 228–246. doi: 10.1111/ntwe.12098

Vosniadou, S., Corte, E. de, Glaser, R., and Mandl, H., (eds.). (1996). International Perspectives on the Design of Technology-Supported Learning Environments. Mahwah, NJ: Erlbaum.

* Walden, J. A. (2016). Integrating social media into the workplace: a study of shifting technology use repertoires. J. Broadcast. Electr. Med. 60, 347–363. doi: 10.1080/08838151.2016.1164163

Weick, K. E. (1990). “Technology as equivoque,” in Technology and Organizations , ed P. S. Goodman and L. Sproull (San Francisco, CA: Jossey-Bass), 1–44.

Zuboff, S. (1988). In the Age of the Smart Machine: The Future of Work and Power. New York, NY: Basic Books.

* Zubrycki, I., and Granosik, G. (2016). Understanding therapists' needs and attitudes towards robotic support. The roboterapia project. Int. J. Soc. Robot. 8, 553–563. doi: 10.1007/s12369-016-0372-9

* Studies included in the systematic review.

** Supplementary studies.

Keywords: technology, work characteristics, continuous vocational education and training, automation, work demands, systematic review

Citation: Beer P and Mulder RH (2020) The Effects of Technological Developments on Work and Their Implications for Continuous Vocational Education and Training: A Systematic Review. Front. Psychol. 11:918. doi: 10.3389/fpsyg.2020.00918

Received: 14 February 2020; Accepted: 14 April 2020; Published: 08 May 2020.

Reviewed by:

Copyright © 2020 Beer and Mulder. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Patrick Beer, patrick.beer@ur.de

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

• Machine learning
• Social justice
• Black holes
• Classes and programs

Departments

• Aeronautics and Astronautics
• Brain and Cognitive Sciences
• Architecture
• Political Science
• Mechanical Engineering

Centers, Labs, & Programs

• Abdul Latif Jameel Poverty Action Lab (J-PAL)
• Picower Institute for Learning and Memory
• Lincoln Laboratory
• School of Architecture + Planning
• School of Engineering
• School of Humanities, Arts, and Social Sciences
• Sloan School of Management
• School of Science
• MIT Schwarzman College of Computing

A comprehensive study of technological change

Press contact :.

Previous image Next image

The societal impacts of technological change can be seen in many domains, from messenger RNA vaccines and automation to drones and climate change. The pace of that technological change can affect its impact, and how quickly a technology improves in performance can be an indicator of its future importance. For decision-makers like investors, entrepreneurs, and policymakers, predicting which technologies are fast improving (and which are overhyped) can mean the difference between success and failure.

New research from MIT aims to assist in the prediction of technology performance improvement using U.S. patents as a dataset. The study describes 97 percent of the U.S. patent system as a set of 1,757 discrete technology domains, and quantitatively assesses each domain for its improvement potential.

“The rate of improvement can only be empirically estimated when substantial performance measurements are made over long time periods,” says Anuraag Singh SM ’20, lead author of the paper. “In some large technological fields, including software and clinical medicine, such measures have rarely, if ever, been made.”

A previous MIT study provided empirical measures for 30 technological domains, but the patent sets identified for those technologies cover less than 15 percent of the patents in the U.S. patent system. The major purpose of this new study is to provide predictions of the performance improvement rates for the thousands of domains not accessed by empirical measurement. To accomplish this, the researchers developed a method using a new probability-based algorithm, machine learning, natural language processing, and patent network analytics.

Overlap and centrality

A technology domain, as the researchers define it, consists of sets of artifacts fulfilling a specific function using a specific branch of scientific knowledge. To find the patents that best represent a domain, the team built on previous research conducted by co-author Chris Magee, a professor of the practice of engineering systems within the Institute for Data, Systems, and Society (IDSS). Magee and his colleagues found that by looking for patent overlap between the U.S. and international patent-classification systems, they could quickly identify patents that best represent a technology. The researchers ultimately created a correspondence of all patents within the U.S. patent system to a set of 1,757 technology domains.

To estimate performance improvement, Singh employed a method refined by co-authors Magee and Giorgio Triulzi, a researcher with the Sociotechnical Systems Research Center (SSRC) within IDSS and an assistant professor at Universidad de los Andes in Colombia. Their method is based on the average “centrality” of patents in the patent citation network. Centrality refers to multiple criteria for determining the ranking or importance of nodes within a network.

“Our method provides predictions of performance improvement rates for nearly all definable technologies for the first time,” says Singh.

Those rates vary — from a low of 2 percent per year for the “Mechanical skin treatment — Hair removal and wrinkles” domain to a high of 216 percent per year for the “Dynamic information exchange and support systems integrating multiple channels” domain. The researchers found that most technologies improve slowly; more than 80 percent of technologies improve at less than 25 percent per year. Notably, the number of patents in a technological area was not a strong indicator of a higher improvement rate.

“Fast-improving domains are concentrated in a few technological areas,” says Magee. “The domains that show improvement rates greater than the predicted rate for integrated chips — 42 percent, from Moore’s law — are predominantly based upon software and algorithms.”

TechNext Inc.

The researchers built an online interactive system where domains corresponding to technology-related keywords can be found along with their improvement rates. Users can input a keyword describing a technology and the system returns a prediction of improvement for the technological domain, an automated measure of the quality of the match between the keyword and the domain, and patent sets so that the reader can judge the semantic quality of the match.

Moving forward, the researchers have founded a new MIT spinoff called TechNext Inc. to further refine this technology and use it to help leaders make better decisions, from budgets to investment priorities to technology policy. Like any inventors, Magee and his colleagues want to protect their intellectual property rights. To that end, they have applied for a patent for their novel system and its unique methodology.

“Technologies that improve faster win the market,” says Singh. “Our search system enables technology managers, investors, policymakers, and entrepreneurs to quickly look up predictions of improvement rates for specific technologies.”

Adds Magee: “Our goal is to bring greater accuracy, precision, and repeatability to the as-yet fuzzy art of technology forecasting.”

Share this news article on:

Related links.

• Sociotechnical Systems Research Center
• Institute for Data, Systems, and Society (IDSS)

Related Topics

• Technology and society
• Innovation and Entrepreneurship (I&E)

Related Articles

Shaping technology’s future

Tackling society’s big problems with systems theory

Patents forecast technological change

Previous item Next item

More MIT News

Featured video: Moooving the needle on methane

Read full story →

The many-body dynamics of cold atoms and cross-country running

Heather Paxson named associate dean for faculty of the School of Humanities, Arts, and Social Sciences

Preparing MIT’s campus for cardiac emergencies

Researching extreme environments

To build a better AI helper, start by modeling the irrational behavior of humans

• More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

• Map (opens in new window)
• Events (opens in new window)
• People (opens in new window)
• Careers (opens in new window)
• Accessibility
• Social Media Hub
• MIT on Facebook
• MIT on YouTube
• MIT on Instagram

• Research Article
• Open access
• Published: 03 April 2022

Young people’s technological images of the future: implications for science and technology education

• Tapio Rasa   ORCID: orcid.org/0000-0003-1315-5207 1 &
• Antti Laherto   ORCID: orcid.org/0000-0001-5062-7571 2  

European Journal of Futures Research volume  10 , Article number:  4 ( 2022 ) Cite this article

12k Accesses

12 Citations

3 Altmetric

Metrics details

Modern technology has had and continues to have various impacts on societies and human life in general. While technology in some ways defines the ‘digital age’ of today, discourses of ‘technological progress’ may dominate discussions of tomorrow. Conceptions of technology and futures seem to be intertwined, as technology has been predicted by experts to lead us anywhere between utopia and extinction within as little as a century. Understandably, hopes and fears regarding technology may also dominate images of the future for our current generation of young people. Meanwhile, global trends in science and technology education have increasingly emphasised goals such as agency, anticipation and active citizenship. As one’s agency is connected to one’s future perceptions, young people’s views of technological change are highly relevant to these educational goals. However, students’ images of technological futures have not yet been used to inform the development of science and technology education. We set out to address this issue by investigating 58 secondary school students’ essays describing a typical day in 2035 or 2040, focusing on technological surroundings. Qualitative content analysis showed that students’ images of the future feature technological changes ranging from improved everyday devices to large-scale technologisation. A variety of effects was attributed to technology, relating to convenience, environment, employment, privacy, general societal progress and more. Technology was discussed both in positive and negative terms, as imagined technological futures were problematised to differing extents. We conclude by discussing the potential implications of the results for the development of future-oriented science and technology education.

Introduction

Modern technology has had and continues to have an impact on human life and civilisation that is hard to overstate. While technology in some ways defines the ‘digital age’ of today, discourses of ‘technological progress’ may dominate discussions of tomorrow. Meanwhile, predicting the ‘real future’ and figuring out how to do it well is a field in itself, and experts within and outside specific technological fields project a wide range of predictions for the coming decades: technology has been predicted to lead us anywhere between human extinction [ 10 ] and planet-sized self-aware computers [ 32 ] within the timescale of a century, with more cautious predictions forecasting a ‘third industrial revolution’ by 2030 ([ 16 ], p. 33). Understandably, hopes and fears regarding technology may also dominate the images of the future for our current generation of young people (see, e.g. [ 3 , 36 ]).

Obviously, the fact that developments in science and technology can have great desirable and undesirable societal implications is reflected in science education. This element is central to research currents such as STSE (science, technology, society, environment—see, e.g. [ 6 ]), SSI (socioscientific issues—e.g. [ 49 ]) and the various visions of scientific literacy (e.g. [ 45 ]). Interestingly, however, these socioscientific leanings rarely address explicitly the temporal aspects of socioscientific thinking. Thus, even if local and global SSIs ‘are all related to important aspects of our future’ ([ 44 ], pp. 2–3) and environmental education should address ‘Where do we want to go?—knowledge about alternatives and visions’ ([ 28 ], p. 331), the connection to futures thinking is often unaddressed when contextualising science as societally relevant. For example, the focus of STSE has been applying science and technology in social (more or less real-world) contexts, understanding the sociocultural embeddedness of such activity and exploring holistic, value-centred approaches to evaluating technoscientific issues [ 39 ]. These aspects of scientific literacy certainly have a ‘time component’, but seem to lack a more nuanced relationship with futures. This oversight seems to reflect a general pattern in education (see, e.g. [ 24 ]).

Understandably this ‘blind spot’ has been criticised in the futures field: according to Gidley & Hampson [ 22 ],

[s]chool education seems to be mostly stuck in an outdated industrial era worldview, unable to sufficiently address the significance and increasing rapidity of changes to humanity that are upon us. An integrated forward-looking view should, now more than ever, be of central importance in how we educate. Yet there is little sign that – unlike corporations – school systems are recognising the true value of futures studies.

While the field of science education has seen some recent initiatives for developing students’ futures thinking [ 29 , 34 , 35 , 36 , 38 , 41 ], much work remains to be done in communicating between the two fields. One approach to strengthening the foothold of futures thinking in schools may be identifying practical contexts for future-oriented education and joining with natural ‘allies’ within the range of educational fields [ 23 ], or formalising the concept of ‘futures literacy’ in education, eliciting students’ images of the future, and supporting their agency [ 24 ]. A further goal may be formalising relevant capacities to also enable evaluation of learning processes and outcomes, where constructions such as ‘futures consciousness’ [ 1 ] may prove useful.

Meanwhile, young people’s future thinking has been analysed in several studies (e.g. [ 3 , 15 , 43 ]), revealing both pessimistic and optimistic future outlooks. Such studies also support the notion that technology is strongly associated with imagined future worlds—a connection embodied in science fiction, which arguably could also be called ‘technology fiction’ or ‘future fiction’, demonstrating a strong association between the concepts. Within futures studies, this link may seem obvious (see, e.g. the role of technology in the ‘future archetypes’ of [ 27 ]), but it is underrepresented in science education literature; students’ hopes, fears and expectations regarding the future are rarely addressed.

There may also exist a discontinuity between the approaches taken when addressing socioscientific thinking within education, and those taken when studying young people’s perceptions of the future. Namely, societally oriented science education research and practice may tend to be based on individual issues [ 6 ] and case studies, while research on young people’s perceptions of technology may look at technology more generally [ 7 ].

Thus our goal in this paper is to explore the following question:

What kinds of technology and what desirable and undesirable impacts of technology are present in upper-secondary school students’ images of the future?

Specifically, we examine a set of Finnish upper secondary school students’ essays that describe imagined future worlds, set in years 2035 and 2040. We analyse what technologies are present in these essays, what aspects of the world and human life are affected by technology and whether these effects are framed as positive, negative or in neutral or conflicted terms.

Our goal is to diversify the meaning of the term ‘technology’ in (young) people’s futures thinking by providing an exploratory study on expectations, hopes and fears associated with specific envisioned technological developments or the processes of technologisation in general. Finally, we conclude by discussing potential implications of the results for the development of science and technology education, and the potential of using socioscientific and sociotechnical issues as a context for futures thinking in education.

Definitions and rationale

In this paper, we examine the role of technology in upper-secondary school students’ images of the future. By images of the future we mean ‘snapshots of the major features of interest at various points in time’ ([ 42 ], p. 14). Images of the future do not necessarily contain ‘an account of the flow of events leading to such future conditions’ (Ibid., p. 14); this temporal perspective would turn an image into a scenario (which are more commonly explored in futures studies and also in future-oriented science education—see, e.g. [ 35 ]).

Images of the future are widely addressed in futures studies. However, as they exist in people’s imaginations and are by nature complex, they are difficult to fully pin down. Perceptions about the future are an integral part of one’s worldview [ 36 ], and at least in the case of nonexpert futures thinking, they can be expected to lack some systematicity. Imagined futures are often inconsistent [ 30 ] and can perhaps be better understood as reflecting the present [ 9 ]. An example of inconsistency is the common finding of a disconnection between optimistic personal and gloomy global futures [ 15 , 43 , 47 ].

In the case of images of technological futures, one’s understanding of technology is naturally a component, but only one of many. To quote Zeidler et al. [ 49 ], p. 360, ‘knowledge and understanding of the interconnections among science, technology, society, and the environment (...) do not exist independently of students’ personal beliefs’. For our purposes, no attempt to separate these components is necessary: our goal is to give voice to the image that emerges from these influences.

Defining technology is something of an arduous task, partly because the meaning of the word seems to vary greatly between contexts—it is a ‘slippery term’ ([ 5 ], p. 7). Thus for example the ‘T’ of STS (Science and technology studies) may be different from the ‘T’ of STEM (science, technology, engineering and mathematics). The students who wrote the essays that form the dataset for our study were asked to address the role of technology in their image of the future, and no theoretical definition was provided with this prompt. We expect students to have relied on some commonsense meaning of the word, and for the purposes of our study, we consider technology to be related to artefacts, tools, methods and systems that are based on the application of knowledge specific to STEM subjects. We expect this meaning to correspond to some extent with students’ thinking.

This study uses a unified view of science and technology education, or scientific and technological literacy (see, e.g. [ 33 ]) that is typical in current trends of interdisciplinary and societally oriented science education, or STEM education (see, e.g. [ 12 ]). As a clarification, we do not wish to convey the idea that the relationship between science and technology is obvious and uncomplicated (see, e.g. [ 4 ]). However, this is a context-dependent issue: firstly, technology experts and technologically literate citizens are expected to gain much of their education within science education, and secondly, the boundary between science and technology tends to disappear (or lose some of its meaning) in societal and future-oriented contexts [ 26 ]. Thus, studies of students’ images of technological futures can be expected to provide insight into the expectations, opportunities and sociotechnical thinking that will eventually be reflected in both the practice of technology experts and the actions of nonexpert citizens [ 31 ].

Perceptions of (technological) futures

Research on young people’s futures thinking has shown that science and technology are typical ingredients in young people’s dystopian views [ 13 ] but also central to their hopes of sustainable or otherwise progressive futures [ 15 , 36 ]. According to Cook ([ 15 ], p. 528), young people may generally feel ‘a loss of faith in the notion that humanity is progressing towards a positive future’—and thus society is ‘due for another break through’ with the help of technology.

Similarly, according to a study by Heikkilä et al. [ 25 ], Finnish people aged 16-20 seem to feel positively about technology amid a general trajectory of societal decline—while being reserved towards many areas of technology or new technologies in general, and feeling mostly optimistic about their own futures. In their study, young people’s images of the future involved robots, entertainment technology, home automation and new ways to travel, but also considerations against using robots as workforce, and in favour of ecological energy production and general ‘high technology’. It is notable that while such attitudes towards technology may be vague and inconsistent, they are nearly universal: in a nationwide survey, the increasing significance of technology was the most common future belief for Finnish 15- to 29-year-olds [ 37 ].

In Angheloiu et al.’s [ 3 ] paper, young people (ages 16-17) were found to mostly see an optimistic future where technology is strongly embedded in people’s daily lives, improving their quality of life and creating sustainability. However, optimism was not universal: some youth were found to e.g. fear environmental or health crises that would give rise to totalitarian regimes. In fact, the authors (p. 5) recognised the motif of “trade-offs between tech that makes our lives convenient at the price of ‘ethics and morals’”. This corresponds with the common discourses of technology as a ‘double-edged sword’ or ‘Faustian bargain’ (see, e.g. [ 14 ]). Across many outlooks, young people in Angheloiu et al.’s [ 3 ] study shared worries of accelerating inequality and increasing social isolation, also caused largely by technology, with similar findings reported by e.g. Kaboli & Tapio [ 30 ].

At a population-wide scale, van der Duin et al. [ 48 ] analysed Dutch adults’ views of the year 2040 (similarly to the present paper). They focused especially on societal, economical, environmental and technological issues. In the last category, questions of robotisation, digitisation and biotechnology were specifically addressed in both likelihood and desirability. Perhaps unsurprisingly, Dutch people (88%) believe science and technology to greatly advance in the next few decades, while their attitude towards technology was almost evenly split between positive, neutral and negative. Expectations of ‘making life easier’ and ‘having a positive impact’ were reported: examples include electric transport and automatised household tasks, but to a lesser extent also advances such as teleportation and colonisation of other planets. The respondents’ technological worries related to cybersecurity, privacy, behaviour prediction systems, robotisation, diminishing human contact and ‘unnatural’ outcomes, among others.

At an even wider scope, Special Eurobarometer 419 [ 18 ] found that Finnish people and Europeans in general (aged 15 and over) expect technology (or ‘science and innovation’) to contribute to many important issues in the near future. These included health, jobs, education, skills, environment, energy supply, security and inequality. Interestingly, with the exception of inequality, in all of these issues, Europeans expect ‘science and innovation’ to contribute more to progress than ‘people’s actions’. In a similar manner, general opinion on futures was more divided than the role of technology in futures, which was seen in mostly positive light (opinions were most divided on cybersecurity). This connects well with Cook’s [ 15 ] notion of technology as a ‘refuge of hope’.

More recently, in Standard Eurobarometer 94 [ 19 ] it was found that Europeans’ general future perspectives are somewhat gloomy, even if inconsistent: future generations are expected to face more difficulties, and nations are seen as going downhill, even if these feelings coexist with ‘confidence in the future’ (p. T118 in Data Annex).

Most people indeed believe that ‘science has a positive impact on society’, and especially young people feel informed with technological developments ([ 17 ], p.5). Technology is expected to make life easier, more comfortable and healthier, even if the rapid pace of development is perceived somewhat negatively by the majority. However, as Kerschner & Ehlers [ 31 ] have pointed out, these attitudes seem to be diversifying, and Eurobarometer surveys may address this issue too superficially. To quote Kerschner & Ehlers (p. 139):

In the past any diversion from unquestioned optimism was interpreted as a bad sign and attributed to the public's ignorance. Today it is often welcomed as a sign of an increasingly emancipated public.

Accordingly, we emphasise the point that critical attitudes are not simply ‘luddite pessimism’, nor are hopeful attitudes always ‘sci-fi romanticism’—and attempt in this paper to give adequate voice to both critical and enthusiastic views.

Some scholars have also argued that attitudes towards technology may be different from attitudes towards any specific area of technology [ 7 ], or that there is no single direction in which sociotechnical transitions can take us, or metric by which to judge them [ 46 ]. In this paper, we address both general and specific views of future technology with the explicit intention of diversifying discourses of sociotechnical conceptions.

Thus there is considerable even if in some ways limited literature on how people perceive technology and technological futures. Similar questions have been a matter of some discourse in educational research as well, even if not as exhaustively. For instance, Clough [ 14 ] has noted that the pedagogies around the nature of technology should address how technology may impact behaviour, thinking, privacy and values among other facets of life, Hodson [ 26 ] has discussed connections between technological and scientific literacy and sociopolitical action, and Aikenhead & Ryan [ 2 ] have long before suggested researching students’ conceptions on the many impacts technology has. Equipping students with tools to understand how socioscientific and sociotechnical issues shape their lives is certainly one of the goals of modern science education. However, as Facer ([ 20 ], p. 99) has argued,

[r]hetoric about young people’s ‘ownership’ of future socio-technical change is a familiar part of much educational and political discourse. This does not, however, translate in practice into a meaningful dialogue with young people about the sorts of futures they might wish to see emerge.

We wish to argue that while emphasising the societal relevance of science and allowing students to practice socioscientific argumentation in the classroom is worthwhile, these questions should be adequately linked to students’ perceptions of the future, and specifically their own future.

Data collection

The data for this paper consists of 58 student essays. These were collected from 57 Finnish upper-secondary students from schools in the Helsinki region. 20 essays were collected in 2018 with the title ‘A typical summer day in 2035’ and 38 in 2019 with the title ‘A typical summer day in 2040’. One student wrote two different essays in two consecutive years.

In addition to the topic, students were given the instruction to describe what kind of general and technological environment they would like to live in (i.e. a preferable future—see, e.g. [ 8 ]). They were prompted to approach this task by addressing the topics of what one’s life is like, the problems one and one’s communities face, the opportunities one perceives, what items and objects are present, what kind of the city or country lives in and the social life one leads. Finally, they were asked to fill in sentences beginning with ‘my dream is’, ‘my dream place is/has’, ‘my ideal world is/has’, and ‘my biggest fears and concerns are’.

The data collection took part within the European Erasmus+ project ‘I SEE’ (2016-2019) [ 35 ]. The essays were collected as prerequisites for volunteers attending experimental courses, i.e. before any teaching intervention took place. All essays were translated into English before analysis, with student names replaced with pseudonyms. All these students (or with underage students, also their guardian) gave written consent to participate in the research.

In order to analyse what technologies and effects of technology are present in students’ images of the future, we employed thematic analysis [ 11 ] with inductive coding. We began by cataloguing passages in the essays based on the subject matter. A total of 385 passages relating to technology were identified, forming the set of our analysis units. Typically, an analysis unit would be one to five sentences long, and describe one (although sometimes more) technology, and one (or more) effects of the technology in one continuous argument. Many passages were also found to discuss technology generally without further specification.

The effects of technology were identified strictly by what was addressed in the essays. For example, a unit that mentioned ‘greener air travel’ was seen as discussing ‘transportation technology’ with effects relating to ‘the environment’ while another passage that described casual commuting between Finland and Italy was seen linking transportation technology to increased mobility. As these examples also demonstrate, by ‘effect of technology’ we mean aspects of life, society and the world that are influenced in some way by technology or technological change. The focus on ‘technology’ and ‘effect’ is employed here for analytic simplicity: for some students, technology seemed to drive change, but for some, expectations of sociotechnical transformation were also drivers of technology. Thus ‘effect’ covers a range of causal systems. By definition, every unit of analysis discusses either one or more specific technologies or technology in general. However, in some cases, no clear effects were addressed within the text. An example is the short unit ‘I own an electric car’.

These categories were formed inductively based on multiple rounds of coding, which included some redefinition, combination and subdivision of initial coding categories. The specificity of each technology or effect (e.g. coding both greener aeroplanes and electric cars under the technology code ‘transportation’) was done by the authors with the intention of creating codes with meaningfully different contents.

Finally, we separated the analysis units into three categories, based on whether the effects of the technology were phrased in terms that convey these effects as desirable, undesirable or whether they are discussed in neutral terms. To be precise, we checked each unit against the following criteria:

Positive: Changes described or framed as mostly positive—improvement, desirable effects, solved problems

Neutral: indifference; neutral descriptions; positive and negative aspects balance out

Negative: Changes described or framed as mostly negative—problems, reluctance, disequilibration

The authors negotiated codes for unclear units until consensus was found. In addition, every unit was checked against coding criteria to eliminate mistakes and inconsistencies. The codes with less than eight occurrences were also merged with other, similar codes. Finally, to structure the presentation of our results, the final set of technologies, as well as the set of effects of technology, were grouped into 5 and 6 sections respectively (see Tables 1 and 2 ).

General observations

A somewhat wide range of images of the future presents itself in our data. Ranging from highly imaginative to conservative, and simplistic to highly detailed, the essays cover many societal transformations and systemic interactions within society, but focus mainly on technology and the routines of adult life. Derek (all student names given here are pseudonyms) imagined a post-scarcity world, Andre thought that ‘most problems are solved’ in 2035, and Damian imagined himself in the future, missing the ‘old days’ before overtechnologisation. Some students described worlds where climate change is ‘solved’, while in others’ images increasing climate issues serve as a looming backdrop. Quite interestingly, a ‘typical summer day’ in a preferable future also included a wealth of worries related to technology.

Almost all students described in some detail the technological advances apparent on a day in 2035 or 2040. For some students, these were creative, fantastic or narratively distant (ranging from a hub of sky-high glass tubes that serves as public transport to living on a Mars colony ruled by AI). For others, advances were more modest, such as longer-lasting smartphone batteries. Interestingly, a few students stated or implied that technology will likely not impact their lives: Thomas likened new innovations to useless things like ‘electric nailclippers’, while Robyn focused solely on changes in social issues such as human rights and (non-technologically) sustainable lifestyles. We also noted that some students addressed, even in length, aspects of the social construction of technology, such as risk-benefit analysis or democratisation of technological development. Such meanings students gave to technology in their essays will be presented elsewhere [ 40 ]—here we focus on the types of technology and the fields of influence, as described above.

Future technology and its effects

Overview of the analysis.

Various types of technology were identified from the data, ranging from general discussion of technology to smartwatches and from fusion reactors to neural implants. All the technology types in our coding are shown in Table 1 .

In essence, discussions of technology typically focused on everyday devices (e.g. phones, cars, household machines), technological systems and broad categories of technology (e.g. vague or general use of the word ‘technology’, energy production systems, large-scale automation of service jobs). Elements resembling typical science fiction scenarios were found to be relatively rare: these included advances in robotics, artificial intelligence and a few mentions of spacefaring or brain-computer interfaces. The full range of technologies present in students’ images was thus found to be somewhat conservative, perhaps reflecting the given time span of two decades, or perhaps due to the context of imagining one’s own future.

Despite students’ restraints in describing more imaginative or fantastical technological changes, the effects of technology show notable variation. Technology was usually seen as affecting everyday convenience (often specifically household activities), the structure of job markets and environmental issues. Technology was also associated with social life, equality, health and privacy, or connected with larger issues such as overtechnologisation or general progress (for a full list of our effect codes, see Table 2 ).

As the examples selected for Table 2 demonstrate, technology was depicted influencing the world in both positive and negative ways, again showing considerable range: at one extreme are nuclear wars and ‘loss of humanity’, at the other are happiness and ‘a better future’. In total, 244 units were coded as positive, 55 as negative and 86 as neutral. However, it is notable that students were instructed to focus on a preferable future. Thus, while valence counts are reported in Tables 1 and 2 , the goal of our exploratory study is to analyse qualitatively various themes identified in the dataset.

Let us now look at how the technology and effect codes interconnect. Our analysis revealed a somewhat complex web of connections between technology, impacts of technology, and the desirability of such developments. This is illustrated by Fig. 1 , a Sankey diagram of the entire coded dataset. As one notices by looking at the diagram, due to constraints of space we cannot in this paper give examples of every type of connection in the data. Instead, we will present some key findings in the following sections, moving from more obvious roles of technology (practical uses) to more complex ones (societal challenges and the systemic effects of technology).

The connections between technologies and their effects. The width of the lines indicates the frequency of the connection. Green colour indicates positively, yellow neutrally and red negatively depicted change

Everyday life and relationships

Some of the connections are rather unsurprising, such as the idea that smart home technology has a positive effect on everyday convenience. In fact, the ‘easier everyday life’ of the future is one of the most salient features in our data. These imagined technological advances were related to handing tasks such as household chores over to robots, paying purchases with one’s phone more often, faster commuting and self-driving cars, wireless phone chargers or a more general expectation of adult life that is not limited or burdened by mundane tasks.

Laptops would also be paper-thin and easy to carry with you. (Willow)

Unless I wanted to, I would not have to do anything to maintain my house. In the modern world, everything revolves very closely around technology. Life is easy, because everything that is ‘unpleasant’ is handled by artificial intelligence. (Andre)

While in students’ visions technology often makes life easier and frees up time for more fulfilling activities, self-actualisation was rarely seen as stemming directly from technology. Similarly, technology was depicted providing an easy way of managing one’s social life, but it could not replace social activity not mediated by technology. In fact, some students saw technology as a force driving people apart: either by creating a culture of superficial acquaintances or by allowing people to retreat into lonely virtual worlds. However, the technologies students proposed as future ways of communication were typically not radically different from technologies that exist today.

I would like to live in a technologically advanced environment where a single lightweight, easy-to-carry device could be used to accomplish a lot of things. (...) one downside to this may be that our social life is likely to become more distant. (Oliver)

Environment

Alongside hopes of easier everyday life, other technological impacts that were seen positively were those relating to the environment. As Fig. 1 clearly shows, the connection between technology and environment was overwhelmingly positive. This was sometimes discussed as ‘solving’ climate change, and sometimes simply as a more incremental move towards greener technologies:

Climate change and other environmental problems have already been solved successfully, and all energy production is renewable or utilizes, for example, fusion power. (Manuel)

Electric cars are used for long-distance travel, since they are ecological. (Claire)

Technologies relevant in overcoming environmental unsustainability included energy production, recycling, production and transportation, but also geoengineering. While some students regarded fighting climate change as a hopeless battle against indifference, in most students’ essays climate and sustainability issues were discussed as either ‘solved’ problems or tackled by ongoing action:

However, new technologies have solved many climate-related problems, such as carbon dioxide and sulphur emissions. These can now be removed from the atmosphere to the surrounding space in a controlled way. (Natalie)

Despite technological development efforts, climate change is still a very relevant problem, and we will probably have had to create global technological solutions to slow it down. (Lily)

Not all efforts to mitigate climate change were based on new technologies—other kinds of sociotechnical change, such as banning cars and increased demand for green energy production were also mentioned. However, while students often discussed climate change mitigation in their essays, almost none of them imagined any technologies related to adapting to a changed climate, with the following exception:

While the worst of the predicted climate catastrophe is yet to come, these new automated fans that follow along with you are just not enough. (Isabella)

Employment, equality and privacy

While students saw potential in technology impacting environmental issues positively, in many other societal issues technology was linked to worries and fears. These included questions of privacy, the risks and vulnerabilities of digital systems, people becoming passive consumers of entertainment or losing the ability to concentrate, increasing social inequality (often caused by the automation of entire professions) and sometimes an AI catastrophe, technological weapons or misuse of mind-reading technology. For example, in Nina’s vision, society was still recovering from ‘the big data leak of 2037’, a nationwide data security catastrophe, and in Derek’s future, people ‘spend their time brainlessly staring at the screen’.

A large portion of the essays depicted a society dealing with impending or ongoing mass unemployment of people in automated service or manual work sectors:

There are not so many jobs these days, so many people are working in research and technology, just like me. Many of the professions that required human contact in the past have been replaced by robots that do the work as well as humans, except they are cheaper and more efficient. (Zelda)

Typically more intellectual jobs were expected to remain viable, including those in science, design, cybersecurity, innovation, programming or undefined ‘new professions’. In these visions, working life was often portrayed as competitive and hectic, with a constant need to keep up with changing demands:

Through social media, you are in contact with every organization in the world, and every organization is in contact with you. If you know what is expected of you (…) you can be very successful in this world. (Aurora)

Many students foresaw technology causing inequality in the future. This effect took place mostly through the unemployment in large work sectors discussed above. Students also expressed fears that technology could marginalise less educated people or ‘widen the gap between the rich and the poor and enable the latter to be oppressed on a global scale’. In fact, even in more positive visions, the connection between technology and equality was sometimes phrased in ways that seem to imply concern:

I want to live in a place where technology benefits everyone, not just those who are more fortunate than others. (Mel)

Divisions, overtechnologisation and progress

Technology (and the increasing embeddedness of technology in human life) was also connected with what appear to be technomoral questions. In other words, technology was not only seen benefiting various stakeholders or communities differently, but also as an issue where values and beliefs surface, creating societal and cultural tensions and polarisation:

By 2040 (...) technology used to study the brain and the functional systems of digital devices will be tightly integrated, and information technology can often be used just by thinking a few thoughts. (...) Our society is divided into groups: those who see nothing bad or unpredictably dangerous in this technology, and those who oppose it completely. (Aurora)

Curiously, similar mind-reading technology was described in solely positive terms by other students, but in these cases it was contextualised as easy-to-use interfaces for smart devices. This illustrates how some students seemed to concentrate on new possibilities, while others (even in a ‘desirable future’ framing) seemed to be more trade-off oriented, especially in larger, society-wide contexts. A similar pattern is seen in the way individual innovations were often discussed as positive developments, while forecasts of larger technological trends were more often paired with some worry. This is most clearly reflected in discourses of ‘overtechnologisation’:

The biggest fear is that with the advancement of technology and electronics, we might lose our humanity (…). (Brian)

(...) I do not want to live on technology’s terms in a world that is chock-full of technology. (Emilia)

Similar developments are possibly implied by students who emphasised that they wanted to live in cities where greenery has ‘not been replaced’, or surrounded by nontechnological objects. In fact, many students had written about a balance between technology and nature (or humans), whether in conjunction with overtechnologisation or not. Relatedly, students pictured futures in which one needs to consciously ‘unplug’ from time to time to retain connection with other facets of life:

It is important to me to not spend my entire life surrounded by machines, even though they make my life easier. (Mel)

Thus, technology was associated with a dangerous allure that individuals or humankind as a whole should guard against. However, the general fear related to the direction of humanity’s technological progress is in stark contrast to ideas centred on possibilities and progress. Several students expressed general trust or hope in technology being a part of a better future, or even a sign of humanity’s success:

I am sure we will live in the era of amazing technology. We can expect huge breakthroughs in physics and information technology that can benefit everyone. The place where I want to live is a place where you can clearly see the development of technology and humanity as a whole (...). (Malcolm)

I would wake up in the morning and, instead of waking up to the news of how humanity is failing, I would wake up to news of new technology being invented. (Lianna)

Lianna’s comparison between humanity’s failings and new technology—as well as Malcolm’s pairing of development of technology and development of humanity—seems far removed from fears of overtechnologisation or loss of humanity. Furthermore, Lianna described only exponential positive progress, while in Malcolm’s image of the future technology also creates unemployment. This exemplifies how students’ images of technological futures seem to reflect views of technology in general, hopes and fears of the overall future of humanity, and mediation between such elements.

Systems perspectives and complexity of sociotechnical change

The causal links between technology and effects also showed diversity. A contrast can be seen, for example, in two quotations provided earlier: Aurora’s complicated narrative of computer-brain interfaces stirring cultural polarisation and Manuel’s straightforward recounting of solving climate change. Technological change was not always seen influencing the world in immediate and instrumentalist ways, but also through systemic, higher order effects. This is a key observation and is well worth another example. Caden saw the future becoming even more globalised via technology-driven location independence and explained this process in some depth:

As communication and traffic systems evolve, I believe that travelling and exchanging thoughts and information across the world will be very common in the future. As a result of globalization, cultures and states will become more and more alike in the future, citizens will continue to move from place to place, and states will no longer exist in their traditional form. (Caden)

These somewhat ‘historical’ narratives were constructed around both positive and negative developments. On the clearly positive side, Lex imagined technology creating prosperity which allows universal basic income, ushering in a new age of people working for passion rather than money. However, for some students the intended use of technology and its direct effects were overshadowed by collateral damage to society, as in this rather dystopic vision:

(...) our society is unstable and environmental problems are a major problem, but people are not interested, because they are locked into their own bubbles. In their own virtual worlds. Sometimes I miss the old days. (Damian)

This quotation was extracted from a relatively rich context: the rather unrecognisable sci-fi cityscape in Damian’s vision and his portrayal of himself as a protagonist who is ‘ready to change the world’ (through his scientific career, in a time where most jobs are automated) is a powerful representation of the range of meanings science and technology may take in young people’s futures views. For some students, these meanings seemed to cause some dissonance that was sometimes addressed or resolved in the essays, for example by weighing the excitement of robot waiters against the perspective of the unemployed service staff. In the case of conflicted feelings towards technology, some students reflected on their positions either by identifying as their future self or explaining their hopes and fears from the present perspective:

I am grateful for all the inventions and technologies that I get to use today. But at the same time I am a little worried – for example life is no longer as private as it used to be. In the past, I might have been somewhat shocked if I had seen the present-day society. I talk a lot about this with my friends and family, and they, too, completely agree on both the opportunities and concerns. (Claire)

I believe there are both good and bad aspects to technology, and I cannot imagine a future where only one or the other would occur. (Natalie)

Conclusions

Discussion of results.

In our study, we examined Finnish upper-secondary school students’ images of desirable technological futures. As Tables 1 and 2 and diagram 1 summarise, students’ futures thinking shows a somewhat wide range of technological futures thinking. While students’ images involve an arguably limited perspective of areas of technology that may be relevant for their futures, these technologies, and technology in general, were associated with a fairly wide range of effects. Of these effects, most salient were hopes of easy day-to-day life, advances in environmental issues, and the automation of jobs.

Students’ views correspond to a large extent to the results of earlier studies on images of the future. Technological points of interest that students examine in their essays included robots and automation, smart homes, transportation and energy (cf. [ 25 , 48 ]), technology for sustainability (cf. [ 3 , 15 ]), the role of technology in everyday life (cf. [ 3 , 17 , 48 ]), inequality and isolation (cf. [ 30 , 48 ]), privacy and cybersecurity (cf. [ 18 ,  48 ]), and technology as progress as opposed to fall or stagnation (cf. [ 15 , 25 ]). Our study builds on these results firstly by not predetermining what technologies should be addressed in imagined futures, thus allowing respondents to construct a vision based on their own ideas, and secondly by explicitly addressing the difference and the associations between technological change and its societal or individual effects. Furthermore, by utilising a written assignment as the basis of the study, we were able to elicit students’ own sense-making of these connections both in the context of specific technologies that they associated with their own future, and the wider trend of technologisation.

Our results demonstrate how some students quite readily problematise sociotechnical change, identifying moral questions, considering trade-offs, stakeholder perspectives and systemic long-term effects. Technology was given both instrumentalist and unproblematic meanings (such as increased convenience) and much wider and more abstract meanings such as general progress or a dangerous trajectory leading to overtechnologisation of life. Interestingly, positive effects were commonly attributed to incremental improvements of existing technologies or specific new innovations, while the larger trends of automation, digitalisation and technologisation were seen in more conflicted terms.

These elements in students’ essays form a somewhat multifaceted picture of the roles technology may take in young people’s futures thinking; no single element captures the multitude of these roles and meanings. For example, it is not straightforward to determine whether students’ images of technological futures are overall ‘positive’ or ‘negative’. Given that students were asked to describe the kind of technological future they would like to see, it is worthwhile to note the frequency of both negative expectations and the ‘Faustian bargain’ discourse. On some level, many students seem to share the belief that positive and negative aspects go hand in hand. However, it is equally worthwhile to note that 24 student essays did not contain any negative effect codes, and of these eight discussed only positive effects. For example, Violet’s technological future featured smooth everyday life, the tools ‘to cure deadly diseases’, an atmospheric cleaner, fusion power and superhuman AI with endless uses.

The difference between purely positive and mixed images of technological futures could be attributed to variation in students’ views, but it is equally arguable that the difference may stem from students focusing to different degrees on ‘preferable’ (as opposed to ‘probable’ or ‘plausible’) futures—i.e. whether students focused on possibilities or critical perspectives. It is partly because of this interpretative ambiguity that we have here focused on analysing the ‘micro-level’ roles of technology in images of the future rather than the overall sociotechnical futures (i.e. each essay as a whole), with the intention of capturing the diversity of students’ ideas, hopes and fears about technology.

Limitations of this study and opportunities of further research

As the writing prompt given to students asked for a description of a desirable future, the strong leaning on positive effects of technology does not necessarily signify technological optimism. Similarly, asking students to think of a typical day may have primed students to think primarily of familiar (i.e. conservative) future worlds. However, perceptions of the future are complex, and any singular image is only a component of a larger whole. Further research is needed on the way individuals navigate various or even contradicting ideas about the future that they may simultaneously hold. As a related challenge, the essays analysed here can be seen exhibiting varying degrees of perceived ‘realness’ to the students. For example, one very short essay described the author living on a Mars colony ruled by an AI system. For us, this entry seemed unserious, possibly indicating some challenge in imagining (or writing about) one’s actual future. Thus, further research may need to gauge how likely students believe their imagined futures are to actually manifest.

Our study tentatively indicates that there are multiple layers of the entanglement of technology and futures that may exist in young people’s thinking: the everyday devices and general technological landscape of one’s life, various positive and negative societal transformations related to technological change, and general trends of technologisation that indicate whether humanity is ‘headed in the right direction’. Further research is needed to identify and operationalise how images of the future are constructed with relation to specific and general beliefs, hopes and fears about technology. An additional key issue unexplored by the present study is the sources from where young people draw elements of their images of the future.

Accordingly, there is much room for similar work to be carried out with various focus points. Here we have operated on the level of individual connections between technology, its effects and their desirability in order to reveal some of the complexity of students’ images of the future. Further studies could investigate students’ beliefs regarding the agents that drive sociotechnical change, the values they associate with these changes (see, e.g. [ 21 ]), and how they connect larger trends to their own lives and their own agency. For this end, this paper lays groundwork for further work carried out in the FEDORA project to discuss the desirable effects of technology in the light of students' values [ 40 ].

In addition, it may be worthwhile to examine what kinds of (science) pedagogies could meaningfully address students’ future views. Such initiatives have been carried out, for example the I SEE project (2016-2019) (see e.g. [ 35 , 41 ]) and the FEDORA project (fedora-project.eu). The implications of the present study for science education are discussed in the following section.

Finally, we note that the sampling is very likely not representative of Finnish youth, as the participants of the study were volunteers enrolling for an additional science course on futures thinking. Thus, they were likely to be interested in science subjects and think positively about scientific ideas. Our study may underrepresent views of the future that are common to other cohorts. The frequency of various perceptions among different age groups, genders and cultural backgrounds also demands broader samples and is left for further investigations.

Implications for science education

As our results demonstrate, images of the future provide a rich perspective into the interaction of students’ futures thinking and sociotechnical thinking. However, as we have shown, images of technological futures differ in many ways from each other. Therefore, science education oriented towards socio-scientific issues (SSIs) [ 49 ] should not address the future as a separate SSI but integrate it in a variety of scientific, social, cultural, ethical, environmental and economic aspects. Our results on the breadth and connectedness of students’ sociotechnical future visions give support and contribute to the holistic type of SSI teaching suggested by Rundgren and Rundgren [ 44 ] and invite science education researchers and practitioners to develop tools to help students connect their technological and socioscientific reasoning with their future outlooks and their futures thinking skills.

Such tools have already been developed for science classrooms in a few initiatives during the past two decades [ 29 , 36 , 38 ]. In Europe, future-oriented science education has been advanced in the I SEE project. The research presented here lays the groundwork and contributes to initiatives of this type by building a more nuanced understanding of students’ images of the future with relation to science and technology.

For science educators, a particularly interesting phenomenon seen in the data reported here concerns the depth of students’ spontaneous socioscientific thinking. In vastly different ideas such as Caden’s technologically united globe, Aurora’s polarising neurotechnology and Damian’s world of VR-induced indifference, a seemingly limited area of technology has effects that range well beyond the immediately obvious. This illustrates how complex and multilayered one’s future perception can be: even a singular and tightly expressed image of the future may contain a wealth of interacting beliefs and ideas. When constructing an image of the world students went beyond addressing simplistic cause-effect socioscientific discourse and engaged in thinking of systemic, higher order effects of sociotechnical change.

Thus, our results imply that constructing images of the future can be a pedagogically rich and meaningful task that taps into the transversal learning objectives in science curricula. While such future-oriented pedagogies face the challenge of addressing the inherently unknowable, in the context of science education they can also harness students’ curiosity about the future, their existing futures thinking skills, and the prevalent idea that scientific and technological ideas may come to determine the future to a great extent. As Facer (2012) [ 20 ] has argued, framing the future as ‘lived’ and ‘local’ seems to encourage students to think meaningfully and critically of sociotechnical change. This approach could also address the need to help students contextualise the ‘core knowledge’ of science, which is a focus of STSE and SSI education (see, e.g. [ 6 ]), to promote scientific literacy (see, e.g. [ 45 ]), and to give students a more nuanced representation of the nature of technology (see, e.g. Clough et al., 2013).

Our results also brought out a variety of technology-related hopes and fears that students may typically hold. In order to foster students’ agency, science and technology education should find ways to address and elaborate such feelings and escape simplistic visions that may be either dystopian, utopian or static. Teachers should help students perceive both opportunities and pitfalls in technology and, for example, problematise the naïve expectations of ‘technological fix’ for sustainability challenges. Relatedly, the diversifying attitudes towards technology should be linked to a belief in the malleability of (sociotechnical) futures through informed agency.

Our study offers evidence that upper-secondary students can be quite capable of engaging in futures thinking in a manner that combines creativity, value-based evaluation, a systems perspective and scientific literacy. However, for the purposes of science education, and the goal of understanding young people’s futures perceptions, it may prove useful for educators and researchers to distinguish between different types of sociotechnical transformations, such as complex systemic transformations (relevant from the SSI perspective) and more incremental and limited technological change (e.g. from a problem-solving, instrumentalist perspective).

Finally, it seems reasonable that practicing formulating images of desirable futures is necessary to acquire the skills needed for technology experts’ reflective practice (see, e.g. [ 4 ]), or steering technology towards sustainability. After all, ‘[w]hen students’ images of possible futures are elicited, valued and acted upon students are empowered to work towards a future they would prefer’ [ 36 ]. This goal requires further exploration of young people’s conceptions and pedagogies inspired by futures studies to evoke and evolve these conceptions—a task that we hope to have demonstrated to be feasible, fruitful and necessary. However, for this purpose there needs to be much more dialogue between the fields of futures studies and educational research.

Availability of data and materials

The dataset analysed during the current study is available in the Zenodo.org repository, https://doi.org/10.5281/zenodo.5517595 .

Ahvenharju S, Lalot F, Minkkinen M, Quiamzade A (2021) Individual futures consciousness: psychology behind the five-dimensional futures consciousness scale. Futures 128:102708. https://doi.org/10.1016/j.futures.2021.102708

Article   Google Scholar  

Aikenhead GS, Ryan AG (1992) The development of a new instrument: ‘views on science—technology—society’ (VOSTS). Sci Educ 76(5):477–491. https://doi.org/10.1002/sce.3730760503

Angheloiu C, Sheldrick L, Tennant M (2020) Future tense: exploring dissonance in young people’s images of the future through design futures methods. Futures 117:102527. https://doi.org/10.1016/j.futures.2020.102527

Ankiewicz P, De Swardt E, De Vries MJ (2006) Some implications of the philosophy of technology for science, technology and society (STS) studies. Int J Technol Des Educ 16(2):117–141. https://doi.org/10.1007/s10798-005-3595-x

Bauchspies W, Croissant J, Restivo S (2006) Science, technology, and society: a sociological approach. Blackwell Publishing

Google Scholar  

Bencze L, Pouliot C, Pedretti E, Simonneaux L, Simonneaux J, Zeidler D (2020) SAQ, SSI and STSE education: defending and extending “science-in-context”. Cult Stud Sci Educ 15:825–851. https://doi.org/10.1007/s11422-019-09962-7

Besley JC (2013) The state of public opinion research on attitudes and understanding of science and technology. Bull Sci Technol Soc 33(1-2):12–20. https://doi.org/10.1177/0270467613496723

Börjeson L, Höjer M, Dreborg KH, Ekvall T, Finnveden G (2006) Scenario types and techniques: towards a user’s guide. Futures 38(7):723–739. https://doi.org/10.1016/j.futures.2005.12.002

Borup M, Brown N, Konrad K, Van Lente H (2006) The sociology of expectations in science and technology. Technol Anal Strateg Manag 18(3–4):285–298. https://doi.org/10.1080/09537320600777002

Bostrom N (2013) Existential risk prevention as global priority. Glob Policy 4(1):15–31. https://doi.org/10.1111/1758-5899.12002

Braun V, Clarke V (2006) Using thematic analysis in psychology. Qual Res Psychol 3(2):77–101. https://doi.org/10.1191/1478088706qp063oa

Bybee RW (2013) The case for STEM education: challenges and opportunities. NSTA press, Arlington

Carter L, Smith C (2003) Revisioning science education from a science studies and futures perspective. J Futures Stud 7(4):45–54. https://doi.org/10.1080/03057260408560205

Clough MP (2013) Teaching about the nature of technology: issues and pedagogical practices. In: Clough MP, Olson JK, Niederhauser DS (eds) The nature of technology: implications for learning and teaching. Springer Science & Business Media, Rotterdam

Chapter   Google Scholar  

Cook J (2016) Young adults’ hopes for the long-term future: from re-enchantment with technology to faith in humanity. J Youth Stud 19(4):517–532. https://doi.org/10.1080/13676261.2015.1083959

ESPAS (2015) Global trends to 2030: can the EU meet the challenges ahead? An inter-institutional EU project. Publications Office of the European Union, Luxembourg

European Commission (2013) Special Eurobarometer 401: responsible research and innovation (RRI), science and technology (no. 401). European Commission, Brussels

European Commission (2014) Special Eurobarometer 419: public perceptions of science, research and innovation. Office for Publications of the European Commission, Luxembourg

European Commission (2021) Standard Eurobarometer 94: public opinion in the European Union. European Union, Brussels

Facer K (2012) Taking the 21st century seriously: young people, education and socio-technical futures. Oxf Rev Educ 38(1):97–113.  https://doi.org/10.1080/03054985.2011.577951

Feenberg A (2009) What is philosophy of technology? In: Jones AT, de Vries MJ (eds) International handbook of Research and Development in technology education. Brill Sense, Rotterdam, pp 159–166

Gidley JM, Hampson GP (2005) The evolution of futures in school education. Futures 37(4):255–271. https://doi.org/10.1016/j.futures.2004.07.005

Hicks D (2008) A futures perspective: lessons from the school room. In: Bussey M, Inayatullah S, Milojevic I (eds) Alternative educational futures: pedagogies for emergent worlds. Sense, Rotterdam, pp 75–90

Häggström M, Schmidt C (2021) Futures literacy – to belong, participate and act!: an educational perspective. Futures 132:102813. https://doi.org/10.1016/j.futures.2021.102813

Heikkilä K, Nevala T, Ahokas I, Hyttinen L, Ollila J (2017) Nuorten tulevaisuuskuvat 2067. Näkökulmia suomalisen yhteiskunnan kehittämiseksi, TUTU, Turku

Hodson D (2011) Looking to the future. Building a curriculum for social activism. Sense, Rotterdam

Book   Google Scholar  

Inayatullah S (2008) Six pillars: futures thinking for transforming. Foresight 10:4–21. https://doi.org/10.1108/14636680810855991

Jensen BB (2002) Knowledge, action and pro-environmental behaviour. Environ Educ Res 8(3):325–334. https://doi.org/10.1080/13504620220145474

Jones A, Buntting C, Hipkins R, McKim A, Conner L, Saunders K (2012) Developing students’ futures thinking in science education. Res Sci Educ 42(4):687–708. https://doi.org/10.1007/s11165-011-9214-9

Kaboli SA, Tapio P (2018) How late-modern nomads imagine tomorrow? A causal layered analysis practice to explore the images of the future of young adults. Futures 96:32–43. https://doi.org/10.1016/j.futures.2017.11.004

Kerschner C, Ehlers MH (2016) A framework of attitudes towards technology in theory and practice. Ecol Econ 126:139–151. https://doi.org/10.1016/j.ecolecon.2016.02.010

Kurzweil R (2005) The singularity is near: when humans transcend biology. Viking, New York

Laherto A (2010) An analysis of the educational significance of nanoscience and nanotechnology in scientific and technological literacy. Sci Educ Int 21(3):160–175.

Levrini O, Tasquier G, Branchetti L, Barelli E (2019) Developing future-scaffolding skills through science education. Int J Sci Educ 41(18):2647–2674. https://doi.org/10.1080/09500693.2019.1693080

Levrini O, Tasquier G, Barelli E, Laherto A, Palmgren E, Branchetti L, Wilson C (2021) Recognition and operationalization of future‐scaffolding skills: Results from an empirical study of a teaching–learning module on climate change and futures thinking. Sci Educ 105(2):281–308.  https://doi.org/10.1002/sce.21612

Lloyd D, Wallace J (2004) Imaging the future of science education: the case for making futures studies explicit in student learning. Stud Sci Educ 40(1):139–177. https://doi.org/10.1080/03057260408560205

Myllyniemi S (2017) Katse tulevaisuudessa. Nuorisobarometri 2016. Grano, Helsinki

Paige K, Lloyd D (2016) Use of future scenarios as a pedagogical approach for science teacher education. Res Sci Educ 46(2):263–285. https://doi.org/10.1007/s11165-015-9505-7

Pedretti E, Nazir J (2011) Currents in STSE education: mapping a complex field, 40 years on. Sci Educ 95(4):601–626. https://doi.org/10.1002/sce.20435

Rasa T, Lavonen J, Laherto A (2022) Agency and transformative potential of technology in upper-secondary students’ images of the future: Role of futures in scientific literacy [Unpublished manuscript]. Department of Education, University of Helsinki.

Rasa T, Palmgren E, Laherto A (2022) Futurising science education: students’ experiences from a course on futures thinking and quantum computing. Instr Sci p. 1–23. https://doi.org/10.1007/s11251-021-09572-3

Raskin P, Banuri T, Gallopin G, Gutman P, Hammond A, Kates R, Swart R (2002) Great transition: the promise and lure of the times ahead, vol 1. Stockholm Environmental Institute, Boston

Rubin A (2013) Hidden, inconsistent, and influential: images of the future in changing times. Futures 45:S38–S44. https://doi.org/10.1016/j.futures.2012.11.011

Rundgren SNC (2010) Rundgren CJ (2010) SEE-SEP: from a separate to a holistic view of socioscientific issues. In: Asia-Pacific forum on science learning and teaching, the Education University of Hong Kong, department of science and environmental studies

Sjöström J, Frerichs N, Zuin V, Eilks I (2017) Use of the concept of Bildung in the international science education literature, its potential, and implications for teaching and learning. Stud Sci Educ 53(2):165–192. https://doi.org/10.1080/03057267.2017.1384649

Stirling A (2011) Pluralising progress: from integrative transitions to transformative diversity. Environm Innov Soc Trans 1(1):82–88. https://doi.org/10.1016/j.eist.2011.03.005

Threadgold S (2012) ‘I reckon my life will be easy, but my kids will be buggered’: ambivalence in young people's positive perceptions of individual futures and their visions of environmental collapse. J Youth Stud 15(1):17–32. https://doi.org/10.1080/13676261.2011.618490

van der Duin P, Lodder P, Snijders D (2020) Dutch doubts and desires. Exploring citizen opinions on future and technology. Futures 124:102637. https://doi.org/10.1016/j.futures.2020.102637

Zeidler DL, Sadler TD, Simmons ML, Howes EV (2005) Beyond STS: a research-based framework for socioscientific issues education. Sci Educ 89(3):357–377. https://doi.org/10.1002/sce.20048

Download references

Acknowledgements

We acknowledge Elina Palmgren for organising the data collection, Paula Pekkala for assisting in the coding process and Pia Erkko for translating the essays. We also thank Prof. Jari Lavonen for some helpful comments on the manuscript and the partners of the FEDORA project, coordinated by Prof. Olivia Levrini in University of Bologna, for their helpful comments on the design of the study. We also thank Steve Bogart for the free SankeyMATIC tool that was used for Fig. 1 . Finally, our warmest thanks to the upper secondary school students who participated in the research.

The collection of the data analysed in this study was supported by the European Commission Erasmus+ programme under Grant Agreement no. 2016-1-IT02-KA201-024373 (project "I SEE").

The analysis of the data and writing of the manuscript was supported by the European Commission Horizon2020 programme under Grant Agreement no. 872841 (project "FEDORA"). Open access funded by Helsinki University Library.

Author information

Authors and affiliations.

Department of Education, University of Helsinki, Siltavuorenpenger 5 A, 00014 Helsingin yliopisto, Helsinki, Finland

Antti Laherto

You can also search for this author in PubMed   Google Scholar

Contributions

TR carried out the data analysis and was the main contributor in all parts of the manuscript. AL planned and lead the data collection in the I SEE project and framing the research in the FEDORA project and helped with writing the manuscript. Both authors read and approved the final manuscript.

Corresponding author

Correspondence to Tapio Rasa .

Ethics declarations

Ethics approval and consent to participate.

Participating in the study was voluntary. All participating students (in the case of underage students, also their guardian) gave a written consent to participate in the research. The need for an ethics approval for the study was waived.

Consent for publication

The participants have consented for essays written by them to be used and commented on in the study.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Rasa, T., Laherto, A. Young people’s technological images of the future: implications for science and technology education. Eur J Futures Res 10 , 4 (2022). https://doi.org/10.1186/s40309-022-00190-x

Download citation

Received : 28 September 2021

Accepted : 13 January 2022

Published : 03 April 2022

DOI : https://doi.org/10.1186/s40309-022-00190-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Images of the future
• Science education
• Technology education
• Student perceptions
• Future-oriented science education

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List

Nanotechnology: A Revolution in Modern Industry

Shiza malik.

1 Bridging Health Foundation, Rawalpindi 46000, Pakistan

Khalid Muhammad

2 Department of Biology, College of Science, UAE University, Al Ain 15551, United Arab Emirates

Yasir Waheed

3 Office of Research, Innovation, and Commercialization (ORIC), Shaheed Zulfiqar Ali Bhutto Medical University (SZABMU), Islamabad 44000, Pakistan

4 Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos 1401, Lebanon

Associated Data

Not applicable.

Nanotechnology, contrary to its name, has massively revolutionized industries around the world. This paper predominantly deals with data regarding the applications of nanotechnology in the modernization of several industries. A comprehensive research strategy is adopted to incorporate the latest data driven from major science platforms. Resultantly, a broad-spectrum overview is presented which comprises the diverse applications of nanotechnology in modern industries. This study reveals that nanotechnology is not limited to research labs or small-scale manufacturing units of nanomedicine, but instead has taken a major share in different industries. Companies around the world are now trying to make their innovations more efficient in terms of structuring, working, and designing outlook and productivity by taking advantage of nanotechnology. From small-scale manufacturing and processing units such as those in agriculture, food, and medicine industries to larger-scale production units such as those operating in industries of automobiles, civil engineering, and environmental management, nanotechnology has manifested the modernization of almost every industrial domain on a global scale. With pronounced cooperation among researchers, industrialists, scientists, technologists, environmentalists, and educationists, the more sustainable development of nano-based industries can be predicted in the future.

1. Introduction

Nanotechnology has slowly yet deeply taken over different industries worldwide. This rapid pace of technological revolution can especially be seen in the developed world, where nano-scale markets have taken over rapidly in the past decade. Nanotechnology is not a new concept since it has now become a general-purpose technology. Four generations of nanomaterials have emerged on the surface and are used in interdisciplinary scientific fields; these are active and passive nanoassemblies, general nanosystems, and small-scale molecular nanosystems [ 1 ].

This rapid development of nanoscience is proof that, soon, nano-scale manufacturing will be incorporated into almost every domain of science and technology. This review article will cover the recent advanced applications of nanotechnology in different industries, mainly agriculture, food, cosmetics, medicine, healthcare, automotive, oil and gas industries, chemical, and mechanical industries [ 2 , 3 ]. Moreover, a brief glimpse of the drawbacks of nanotechnology will be highlighted for each industry to help the scientific community become aware of the ills and benefits of nanotechnology side by side. Nanotechnology is a process that combines the basic attributes of biological, physical, and chemical sciences. These processes occur at the minute scale of nanometers. Physically, the size is reduced; chemically, new bonds and chemical properties are governed; and biological actions are produced at the nano scale, such as drug bonding and delivery at particular sites [ 4 , 5 ].

Nanotechnology provides a link between classical and quantum mechanics in a gray area called a mesoscopic system. This mesoscopic system is being used to manufacture nanoassemblies of nature such as agricultural products, nanomedicine, and nanotools for treatment and diagnostic purposes in the medical industry [ 6 ]. Diseases that were previously untreatable are now being curtailed via nano-based medications and diagnostic kits. This technology has greatly affected bulk industrial manufacturing and production as well. Instead of manufacturing materials by cutting down on massive amounts of material, nanotechnology uses the reverse engineering principle, which operates in nature. It allows the manufacturing of products at the nano scale, such as atoms, and then develops products to work at a deeper scale [ 7 ].

Worldwide, millions and billions of dollars and euros are being spent in nanotechnology to utilize the great potential of this new science, especially in the developed world in Europe, China, and America [ 8 ]. However, developing nations are still lagging behind as they are not even able to meet the industrial progression of the previous decade [ 9 ]. This lag is mainly because these countries are still fighting economically, and they need some time to walk down the road of nanotechnology. However, it is pertinent to say that both the developed and developing world’s scientific communities agree that nanotechnology will be the next step in technological generation [ 10 ]. This will make further industrial upgrading and investment in the field of nanotechnology indispensable in the coming years.

With advances in science and technology, the scientific community adopts technologies and products that are relatively cheap, safe, and cleaner than previous technologies. Moreover, they are concerned about the financial standing of technologies, as natural resources in the world are shrinking excessively [ 11 ]. Nanotechnology thus provides a gateway to this problem. This technology is clear, cleaner, and more affordable compared to previous mass bulking and heavy machinery. Moreover, nanotechnology holds the potential to be implemented in every aspect of life. This will mainly include nanomaterial sciences, nanoelectronics, and nanomedicine, being inculcated in all dimensions of chemistry and the physical and biological world [ 12 ]. Thus, it is not wrong to predict that nanotechnology will become a compulsory field of study for future generations [ 13 ]. This review inculcates the basic applications of nanotechnology in vital industries worldwide and their implications for future industrial progress [ 14 ].

2. Nanotechnology Applications

2.1. applications of nanotechnology in different industries.

After thorough and careful analyses, a wide range of industries—in which nanotechnology is producing remarkable applications—have been studied, reviewed, and selected to be made part of this review. It should be notified that multiple subcategories of industrial links may be discussed under one heading to elaborate upon the wide-scale applications of nanotechnology in different industries. A graphical abstract at the beginning of this article indicates the different industries in which nanotechnology is imparting remarkable implications, details of which are briefly discussed under different headings in the next session.

2.2. Nanotechnology and Computer Industry

Nanotechnology has taken its origins from microengineering concepts in physics and material sciences [ 15 ]. Nanoscaling is not a new concept in the computer industry, as technologists and technicians have been working for a long time to design such modified forms of computer-based technologies that require minimum space for the most efficient work. Resultantly, the usage of nanotubes instead of silicon chips is being increasingly experimented upon in computer devices. Feynman and Drexler’s work has greatly inspired computer scientists to design revolutionary nanocomputers from which wide-scale advantages could be attained [ 13 ]. A few years ago, it was an unimaginable to consider laptops, mobiles, and other handy gadgets as thin as we have today, and it is impossible for even the common man to think that with the passage of time, more advanced, sophisticated, and lighter computer devices will be commonly used. Nanotechnology holds the potential to make this possible [ 16 ].

Energy-efficient, sustainable, and urbanized technologies have been emerging since the beginning of the 21st century. The improvement via nanotechnology in information and communication technology (ICT) is noteworthy in terms of the improvements achieved in interconnected communities, economic competitiveness, environmental stability during demographic shifts, and global development [ 17 ]. The major implications of renewable technology incorporate the roles of ICT and nanotechnology as enablers of environmental sustainability. The traditional methods of product resizing, re-functioning, and enhanced computational capabilities, due to their expensiveness and complicated manufacturing traits, have slowly been replaced by nanotechnological renovations. Novel technologies such as smart sensors logic elements, nanochips, memory storage nanodevices, optoelectronics, quantum computing, and lab-on-a-chip technologies are important in this regard [ 18 ].

Both private and public spending are increasing in the field of nanocomputing. The growth of marketing and industrialization in the biotechnology and computer industries are running in parallel, and their expected growth rates for the coming years are far higher. Researchers and technologists believe that by linking the advanced field of nanotechnology and informatics and computational industries, various problems in human society such as basic need fulfillment can be easily accomplished in line with the establishment of sustainable goals by the end of this decade [ 19 ]. The fourth industrial revolution is based upon the supporting pillars derived from hyperphysical systems including artificial intelligence, machine learning, the internet of things, robots, drones, cloud computing, fast internet technologies (5G and 6G), 3D printing, and block chain technologies [ 20 ].

Most of these technologies have a set basis in computing, nanotechnology, biotechnology, material science renovations, and satellite technologies. Nanotechnology offers useful alterations in the physiochemical, mechanical, magnetic, electrical, and optical properties of computing materials which enable innovative and newer products [ 21 ]. Thus, nanotechnology is providing a pathway for another broad-spectrum revolution in the field of automotive, aerospace, renewable energy, information technology, bioinformatics, and environmental management, all of which have root origins from nanotechnological improvements in computers. Sensors involved in software and data algorithms employ nanomaterials to induce greater sensitivity and processabilities with minimal margin-to-machine errors [ 22 ]. Nanomaterials provide better characteristics and robustness to sensor technologies which mean they are chemically inert, corrosion-resistant, and have greater tolerance profiles toward temperature and alkalinity [ 22 ].

Moreover, the use of semiconductor nanomaterials in the field of quantum computing has increased overall processing speeds with better accuracy and transmissibility. These technologies offer the creation of different components and communication protocols at the nano level, which is often called the internet of nano things [ 23 ]. This area is still in a continuous development and improvement phase with the potential for telecommunication, industrial, and medical applications. This field has taken its origin from the internet of things, which is a hyperphysical world of sensors, software, and other related technologies which allow broad-scale communication via internet operating devices [ 17 ]. The applications of these technologies range from being on the simple home scale to being on the complex industrial scale. The internet of things is mainly capable of gathering and distributing large-scale data via internet-based equipment and modern gadgets. In short, the internet of nano things is applicable to software, hardware, and network connection which could be used for data manipulation, collection, and sharing across the globe [ 24 ].

Another application of nanotechnology in the computer and information industry comes in the form of artificial intelligence, machine learning, and big data platforms which have set the basis for the fourth industrial revolution. Vast amounts of raw data are collected through interconnected robotic devices, sensors, and machines which have properties of nanomaterials [ 18 ]. After wide-scale data gathering, the next step is the amalgamation of the internet of things and the internet of people to prepare a greater analysis, understanding, and utilization of the gathered information for human benefit [ 4 ]. Such data complications can be easily understood through the use of big data in the medical industry, in which epidemiological data provide benefits for disease management [ 2 ]. Yet another example is the applications in business, where sales and retail-related data help to elucidate the target markets, sales industry, and consumer behavioral inferences for greater market consumption patterns [ 19 ].

Similarly, an important dimension of nanotechnology and computer combination comes in the form of drone and robotics technology. These technologies have a rising number of applications in maintenance, inspections, transportation, deliverability, and data inspection [ 25 ]. Drones, robots, and the internet of things are being perfectly amalgamated with the industrial sector to achieve greater goals. Drones tend to be more mobile but rely more on human control as compared to robots, which are less mobile but have larger potential for self-operation [ 26 ]. However, now, more mobile drones with better autonomous profiles are being developed to help out in the domain of manufacturing industries. These devices intensify and increase the pace of automation and precision in industries along with providing the benefits of lower costs and fewer errors [ 24 ]. The integrated fields of robotics, the internet of things, and nanotechnology are often called the internet of robotics and nano things. This field of nanorobotics is increasing the flexibility and dexterity in manufacturing processes compared to traditional robotics [ 25 ].

Drones, on the contrary, help to manage tasks that are otherwise difficult or dangerous to be managed by humans, such as working from a far distance or in dangerous regions. Nanosensors help to equip drones with the qualities of improved detection and sensation more precisely than previous sensor technologies [ 21 , 27 ]. Moreover, the over-potential of working hours, battery, and maintenance have also been improved with the operationalization of nano-based sensors in drone technology. These drones are inclusively used for various purposes such as maintaining operations, employing safety profiling, security surveys, and mapping areas [ 18 ]. However, limitations such as high speed, legal and ethical limitations, safety concerns, and greater automobility are some of the drawbacks of aerial and robotic drone technologies [ 26 ].

Three-dimensional printing is yet another important application of the nanocomputer industry, in which an integrated modus operandi works to help in production management [ 28 ]. Nanotechnology-based 3D printing offers the benefits of an autonomous, integrated, intelligent exchange network of information which enables wide-scale production benefits. These technologies have enabled a lesser need for industrial infrastructure, minimized post-processing operations, reduced waste material generation, and reduced need for human presence for overall industrial management [ 28 , 29 ]. Moreover, the benefits of 3D printing and similar technologies have potentially increased flexibility in terms of customized items, minimal environmental impacts, and sustainable practices with lower resource and energy consumption. The use of nano-scale and processed resins, metallic raw material, and thermoplastics along with other raw materials allow for customized properties of 3D printing technology [ 29 ].

The application of nanotechnology in computers cannot be distinguished from other industrial applications, because everything in modern industries is controlled by a systemic network in association with a network of computers and similar technologies. Thus, the fields of electronics, manufacturing, processing, and packaging, among several others, are interlinked with nanocomputer science [ 11 , 15 ]. Silicon tubes have had immense applications that revolutionized the industrial revolution in the 20th century; now, the industrial revolution is in yet another revolutionary phase based on nanostructures [ 16 ]. Silicon tubes have been slowly replaced with nanotubes, which are allowing a great deal of improvement and efficiency in computing technology. Similarly, lab-on-a-chip technology and memory chips are being formulated at nano scales to lessen the storage space but increase the storage volume within a small, flexible, and easily workable chip in computers for their subsequent applications in multiple other industries.

Hundreds of nanotechnology computer-related products have been marketed in the last 20 years of the nanotechnological revolution [ 30 ]. Modern industries such as textiles, automotive, civil engineering, construction, solar technologies, environmental applications, medicine, transportation agriculture, and food processing, among others are largely reaping the benefits of nano-scale computer chips and other devices. In simple terms, everything out there in nanoindustrial applications has something to do with computer-based applications in the nanoindustry [ 31 , 32 , 33 ]. Thus, all the applications discussed in this review more or less originate from nanocomputers. These applications are enabling considerable improvement and positive reports within the industrial sector. Having said that, it is hoped that computer scientists will remain engaged and will keep on collaborating with scientists in other fields to further explore the opportunities associated with nanocomputer sciences.

2.3. Nanotechnology and Bioprocessing Industries

Scientific and engineering rigor is being carried out to the link fields of nanotechnology with contributions to the bioprocessing industry. Researchers are interested in how the basics of nanomaterials could be used for the high-quality manufacturing of food and other biomaterials [ 15 , 34 ]. Pathogenic identification, food monitoring, biosensor devices, and smart packaging materials, especially those that are reusable and biodegradable, and the nanoencapsulation of active food compounds are only a few nanotechnological applications which have been the prime focus of the research community in recent years. Eventually, societal acceptability and dealing with social, cultural, and ethical concerns will allow the successful delivery of nano-based bio-processed products into the common markets for public usage [ 20 , 35 ].

With the increasing population worldwide, food requirements are increasing in addition to the concerns regarding the production of safe, healthy, and recurring food options. Sensors and diagnostic devices will help improve the sensitivity in food quality monitoring [ 36 ]. Moreover, the fake industrial application of food products could be easily scanned out of a system with the application of nanotechnology which could control brand protection throughout bio-processing [ 6 ]. The power usage in food production might also be controlled after a total nanotechnological application in the food industry. The decrease in power consumption would ultimately be positive for the environment. This could directly bring in the interplay of environment, food, and nanotechnology and would help to reduce environmental concerns in future [ 37 ].

One of the important implications of nanotechnology in bioprocessing industries can be accustomed to fermentation processes; these technologies are under usage for greater industrial demand and improved biomolecule production at a very low cost, unlike traditional fermentation processes [ 35 ]. The successful implementation and integration of fermentation and nanotechnology have allowed the development of biocompatible, safe, and nontoxic substances and nanostructures with wide-scale application in the field of food, bioprocessing, and winemaking industries [ 38 ]. Another important application is in the food monitoring and food supply chain management, present in various subsectors such as production, storage, distribution, and toxicity management. Nanodevices and nanomaterials are incorporated into chemical and biological sensor technologies to improve overall analytical performance with regard to parameters such as response time, sensitivity, selectivity, accuracy, and reliability [ 39 ]. The conventional methods of food monitoring are slowly being replaced with modern nano-based materials such as nanowires, nanocomposites, nanotubes, nanorods, nanosheets, and other materials that function to immobilize and label components [ 40 ]. These methods are either electrochemically or optically managed. For food monitoring, several assays are proposed and implemented with their roots in nano-based technologies; they may include molecular and diagnostic assays, immunological assays, and electrochemical and optical assays such as surface-enhanced Raman scattering and colorimetry technologies [ 34 ]. Materials ranging from heavy materials to microorganisms, pesticides, allergens, and antibiotics are easily monitored during commercial processing and bioprocessing in industries.

Additionally, nanotechnology has presented marvelous transformations in bio-composting materials. With the rising demand for biodegradable composites worldwide to reduce the environmental impact and increase the efficiency of industrial output, there is an increasing need for sustainable technologies [ 41 ]. Nanocomposites are thus being formulated with valuable mechanical properties better than conventional polymers, thus establishing their applicability in industries. The improved properties include optical, mechanical, catalytic, electrochemical, and electrical ones [ 42 ]. These biodegradable polymers are not only used in bioprocessing industries to create food products with relevant benefits but are also being deployed in the biomedical field, therapeutic industries, biotechnology base tissue engineering field, packing, sensor industries, drug delivery technology, water remediation, food industries, and cosmetics industries as well [ 2 , 24 , 34 , 43 ]. These nanocomposites have outstanding characteristics of biocompatibility, lower toxicities, antimicrobial activity, thermal resistance, and overall improved biodegradation properties which make them worthy of applications in products [ 44 ]. However, it is still imperative to conduct wide-scale toxicity and safety profiling for these and other nanomaterials to ensure the safety requirements, customer satisfaction, and public benefit are met [ 44 ].

Moreover, the advancement of nanotechnology has also been conferred to the development of functional food items. The exposure and integration of nanotechnology and the food industry have resulted in larger quantities of sustainable, safer, and healthier food products for human consumption, which is a growing need for the rising population worldwide [ 45 ]. The overall positive impact of nanotechnology in food processing, manufacturing, packing, pathogenic detection, monitoring, and production profiles necessitates the wide-scale application of this technology in the food industry worldwide [ 4 , 41 ]. Recent research has shown how the delivery of bioactive compounds and essential ingredients is and can be improved by the application of nanomaterials (nanoencapsulation) in food products [ 46 ]. These technologies improve the protection performance and sensitivity of bioactive ingredients while preventing unnecessary interaction with other constituents of foods, thus establishing clear-cut improved bioactivity and solubility profiles of nanofoods, thereby improving human health benefits. However, it should be kept in mind that the safety regards of these food should be carefully regulated with safety profiling, as they directly interact with human bodies [ 47 ].

2.4. Nanotechnology and Agri-Industries

Agriculture is the backbone of the economies of various nations around the globe. It is a major contributing factor to the world economy in general and plays a critical role in population maintenance by providing nutritional needs to them. As global weather patterns are changing owing to the dramatic changes caused by global warming, it is accepted that agriculture will be greatly affected [ 48 ]. Under this scenario, it is always better to take proactive measures to make agricultural practices more secure and sustainable than before. Modern technology is thus being employed worldwide. Nanotechnology has also come to play an effective role in this interplay of sustainable technologies. It plays an important role during the production, processing, storing, packaging, and transport of agricultural industrial products [ 49 ].

Nanotechnology has introduced certain precision farming techniques to enhance plant nutrients’ absorbance, alongside better pathogenic detection against agricultural diseases. Fertilizers are being improved by the application of nanoclays and zeolites which play effective roles in soil nutrient broths and in the restoration soil fertility [ 49 ]. Modern concepts of smart seeds and seed banks are also programmed to germinate under favorable conditions for their survival; nanopolymeric mixtures are used for coating in these scenarios [ 50 ]. Herbicides, pesticides, fungicides, and insecticides are also being revolutionized through nanotechnology applications. It has also been considered to upgrade linked fields of poultry and animal husbandry via the application of nanotechnology in treatment and disinfection practices.

2.5. Nanotechnology and Food Industry

The applications of nanotechnology in the food industry are immense and include food manufacturing, packaging, safety measures, drug delivery to specific sites [ 51 ], smart diets, and other modern preservatives, as summarized in Figure 1 . Nanomaterials such as polymer/clay nanocomposites are used in packing materials due to their high barrier properties against environmental impacts [ 52 ]. Similarly, nanoparticle mixtures are used as antimicrobial agents to protect stored food products against rapid microbial decay, especially in canned products. Similarly, several nanosensor and nano-assembly-based assays are used for microbial detection processes in food storage and manufacturing industries [ 53 ].

Nanotechnology applications in food and interconnected industries.

Nanoassemblies hold the potential to detect small gasses and organic and inorganic residues alongside microscopic pathogenic entities [ 54 ]. It should, however, be kept in mind that most of these nanoparticles are not directly added to food species because of the risk of toxicity that may be attached to such metallic nanoparticles. Work is being carried out to predict the toxicity attached, so that in the future, these products’ market acceptability could be increased [ 55 ]. With this, it is pertinent to say that nanotechnology is rapidly taking steps into the food industry for packing, sensing, storage, and antimicrobial applications [ 56 ].

Nanotechnology is also revolutionizing the dairy industry worldwide [ 57 ]. An outline of potential applications of nanotechnology in the dairy industry may include: improved processing methods, improved food contact and mixing, better yields, the increased shelf life and safety of dairy-based products, improved packaging, and antimicrobial resistance [ 58 ]. Additionally, nanocarriers are increasingly applied to transfer biologically active substances, drugs, enhanced flavors, colors, odors, and other food characteristics to dairy products [ 59 ].

These compounds exhibit higher delivery, solubility, and absorption properties to their targeted system. However, the problem of public acceptability due to the fear of unknown or potential side effects associated with nano-based dairy and food products needs to be addressed for the wider-scale commercialization of these products [ 60 ].

2.5.1. Nanotechnology, Poultry and Meat Industry

The poultry industry is a big chunk of the food industry and contributes millions of dollars every year to food industries around the world. Various commercial food chains are running throughout the world, the bases of which start from healthy poultry industries. The incidence of widespread foodborne diseases that originate from poultry, milk, and meat farms is a great concern for the food industry. Nanobiotechnology is certainly playing a productive role in tackling food pathogens such as those which procreate from Salmonella and Campylobacter infections by allowing increased poultry consumption while maintaining the affordability and safety of manufactured chicken products [ 61 ]. Several nano-based tools and materials such as nano-enabled disinfectants, surface biocides, protective clothing, air and water filters, packaging materials, biosensors, and detective devices are being used to confirm the authenticity and traceability of poultry products [ 62 ]. Moreover, nano-based materials are used to reduce foodborne pathogens and spoilage organisms before the food becomes part of the supply chain [ 63 ].

2.5.2. Nanotechnology—Fruit and Vegetable Industry

As already described, nanotechnology has made its way far ahead in the food industry. The agricultural, medicinal, and fruit and vegetable industries cannot remain unaffected under this scenario. Scientists are trying to increase the shelf life of fresh organic products to fulfill the nutritional needs of a growing population. From horticulture to food processing, packaging, and pathogenic detection technology, nanotechnology plays a vital role in the safety and production of vegetables and fruits [ 64 ].

Conventional technologies are now being replaced with nanotechnology due to their benefits of cost-effectiveness, satisfactory results, and overall shelf life improvement compared to past practices. Although some risks may be attached, nanotechnology has not yet reported high-grade toxicity to organic fresh green products. These technologies serve the purpose of providing safe and sufficient food sources to customers while reducing postharvest wastage, which is a major concern in developing nations [ 55 ]. Nanopackaging provides the benefits of lower humidity, oxygen passage, and optimal water vapor transmission rates. Hence, in the longer run, the shelf life of such products is increased to the desired level using nanotechnology [ 65 ].

2.5.3. Nanotechnology and Winemaking Industry

The winemaking industry is a big commercial application of the food industry worldwide. The usage of nanotechnology is also expanding in this industry. Nanotechnology serves the purpose of sensing technology through employment as nanoelectronics, nanoelectrochemical, and biological, amperometric, or fluorimetric sensors. These nanomaterials help to analyze the wine components, including polyphenols, organic acids, biogenic amines, or sulfur dioxide, and ensure they are at appropriate levels during the production of wine and complete processing [ 66 ].

Efforts are being made to further improve sensing nanotechnology to increase the accuracy, selectivity, sensitivity, and rapid response rate for wine sampling, production, and treatment procedures [ 53 ]. Specific nanoassemblies that are used in winemaking industries include carbon nanorods, nanodots, nanotubes, and metallic nanoparticles such as gold, silver, zinc oxide, iron oxide, and other types of nanocomposites. Recent research studies have introduced the concept of electronic tongues, nanoliquid chromatography, mesoporous silica, and applications of magnetic nanoparticles in winemaking products [ 67 ]. An elaborative account of these nanomaterials is out of the scope of the present study; however, on a broader scale, it is not wrong to say that nanotechnology is successfully reaping in the field of enology.

2.6. Nanotechnology and Packaging Industries

The packaging industry is continuously under improvement since the issue of environmentalism has been raised around the globe. Several different concerns are linked to the packaging industry; primarily, packaging should provide food safety to deliver the best quality to the consumer end. In addition, packaging needs to be environmentally friendly to reduce the food-waste-related pollution concern and to make the industrial processes more sustainable. Trials are being carried out to reduce the burden by replacing non-biodegradable plastic packaging materials with eco-friendly organic biopolymer-based materials which are processed at the nano scale to incur the beneficial properties of nanotechnology [ 68 ].

The nanomanufacturing of packaging biomaterials has proven effective in food packaging industries, as nanomanufacturing not only contributes to increasing food safety and production but also tackles environmental issues [ 69 ]. Some examples of these packaging nanomaterials may include anticaking agents, nanoadditives, delivery systems for nutraceuticals, and many more. The nanocompositions of packing materials are formed by mixing nanofillers and biopolymers to enhance packaging’s functionality [ 70 ]. Nanomaterials with antimicrobial properties are preferred in these cases, and they are mixed with a polymer to prevent the contamination of the packaged material. It is important to mention here that this technology is not only limited to food packaging; instead, packaging nanotechnology is now also being introduced in certain other industries such as textile, leather, and cosmetic industries in which it is providing large benefits to those industries [ 64 ].

2.7. Nanotechnology and Construction Industry and Civil Engineering

Efficient construction is the new normal application for sustainable development. The incorporation of nanomaterials in the construction industry is increasing to further the sustainability concern [ 71 ]. Nanomaterials are added to act as binding agents in cement. These nanoparticles enhance the chemical and physical properties of strength, durability, and workability for the long-lasting potential of the construction industry. Materials such as silicon dioxide which were previously also in use are now manufactured at the nano scale [ 71 ]. These nanostructures along with polymeric additives increase the density and stability of construction suspension [ 72 ]. The aspect of sustainable development is being applied to the manufacture of modern technologies coupled with beneficial applications of nanotechnology. This concept has produced novel isolative and smart window technologies which have driven roots in nanoengineering, such as vacuum insulation panels (VIPs) and phase change materials (PCMs), which provide thermal insulation effects and thus save energy and improve indoor air quality in homes [ 73 ].

A few of the unique properties of nanomaterials in construction include light structure, strengthened structural composition, low maintenance requirements, resistant coatings, improved pipe and bridge joining materials, improved cementitious materials, extensive fire resistance, sound absorption, and insulation properties, as well as the enhanced reflectivity of glass surfaces [ 74 ]. As elaborated under the heading of civil engineering applications, concrete’s properties are the most commonly discussed and widely changing in the construction industry because of concrete’s minute structure, which can be easily converted to the nano scale [ 75 ]. More specifically, the combination of nano-SiO 2 in cement could improve its performance in terms of compressiveness, large volumes with increased compressiveness, improved pore size distribution, and texture strength [ 76 ].

Moreover, some studies are also being carried out to improve the cracking properties of concrete by the application of microencapsulated healing polymers, which reduce the cracking properties of cement [ 77 ]. Moreover, some other construction materials, such as steel, are undergoing research to change their structural composites through nano-scale manufacturing. This nanoscaling improves steel’s properties such as improved corrosion resistance, increased weldability, the ease of handling for designing building materials, and construction work [ 78 ]. Additionally, coating materials have been improved by being manufactured at the nano scale. This has led to different improved coating properties such as functional improvement; anticorrosive action; high-temperature, fire, scratch, and abrasion resistance; antibacterial and antifouling self-healing capabilities; and self-assembly, among other useful applications [ 79 ].

Nanotechnology improves the compressive flexural properties of cement and reduces its porosity, making it absorb less water compared to traditional cementation preparations. This is because of the high surface-to-volume ratio of nanosized particles. Such an approach helps in reducing the amount of cement in concrete, making it more cost-effective, more strengthening, and eco-friendly, known as ‘green concrete’. Besides concrete, the revolutionary characteristics of nanotechnology are now also being adopted in other construction materials such as steel, glass, paper, wood, and multiple other engineering materials to upgrade the construction industry [ 80 ].

Similarly, carbon nanotubes, nanorods, and nanofibers are rapidly replacing steel constructions. These nanostructures along with nanoclay formations increase the mechanical properties and thus have paved the way for a new branch of civil engineering in terms of nanoengineering [ 80 ]. Apart from cement formulations, nanoparticles are included in repair mortars and concrete with healing properties that help in crack recovery in buildings. Furthermore, nanostructures, titanium dioxide, zinc, and other metallic oxides are being employed for the production of photocatalytic products with antipathogenic, self-cleaning, and water- and germ-repellent built-in technologies [ 33 ]. Similarly, quantum dot technologies are progressively employed for solar energy generation (a concept discussed later). These photovoltaic cells contribute to saving the maximum amount of solar energy [ 81 ].

2.8. Nanotechnology and Textiles Industry

The textile industry achieved glory in the 21st century with enormous outgrowth through social media platforms. Large brands have taken over the market worldwide, and millions are earned every year through textile industries. With the passing of time, nanotechnology is being slowly incorporated into the textile fiber industry owing to its unique and valuable properties. Previously, fabrics manufactured via conventional methods often curtailed the temporary effects of durability and quality [ 82 ]. However, the age of nanotechnology has allowed these fabric industries to employ nanotechnology to provide high durability, flexibility, and quality to clothes which is not lost upon laundering and wearing. The high surface-to-volume ratio of nanomaterials keeps high surface energy and thus provides better affinity to their fabrics, leading to long-term durability [ 82 ]. Moreover, a thin layering and coating of nanoparticles on the fabric make them breathable and make them smooth to the touch. This layering is carried out by processes such as printing, washing, padding, rinsing, drying, and curing to attach nanoparticles on the fabric surface. These processes are carried out to impart the properties of water repellence, soil resistance, flame resistance, hydrophobicity, wrinkle resistance, antibacterial and antistatic properties, and increased dyeability to the clothes [ 83 ].

The unique properties of nanomaterials in textile industries have attracted large-scale businesses for the financial benefits attached to their application. For this reason, competitors are increasing in nanotextile industry speedily, which may make the conventional textile industry sidelined in the near future [ 84 ]. Some benefits associated with nanotextile engineering and industry may include: improved cleaning surfaces, soil, wrinkle, stain, and color damage resistance, higher wettability and strike-through characteristics, malodor- and soil-removal abilities, abrasion resistance, a modified version of surface friction, and color enhancement through nanomaterials [ 85 ].

These characteristics have hugely improved the functionality and performance characteristics of textile and fiber materials [ 86 ]. Based upon the numerous advantages, nanotextile technology is increasingly being used in various inter-related fields, including in medical clothes, geotextiles, shock-resistant textiles, and fire-resistant and water-resistant textiles [ 87 ]. These textiles and fibers help overcome severe environmental conditions in special industries where high temperatures, pressure, and other conditions are adjusted for manufacturing purposes. These textiles are now increasingly called smart clothes due to renewed nanotechnological application to traditional methods [ 88 ].

The increasing demand for durable, appealing, and functionally outstanding textile products with a couple of factors of sustainability has allowed science to incorporate nanotechnology in the textile sector. These nano-based materials offer textile properties such as stain-repellent, wrinkle-free textures and fibers’ electrical conductivity alongside guaranteeing comfort and flexibility in clothing [ 82 ]. The characteristics of nanomaterials are also exhibited in the form of connected garments creation that undergo sensations to respond to external stimuli through electrical, colorant, or physiological signals. Thus, a kind of interconnection develops between the fields of photonic, electrical, textile and nanotechnologies [ 89 ]. Their interconnected applications confer the properties of high-scale performance, lasting durability, and connectivity in textile fibers. However, the concerns of nanotoxicity, the chances of the release of nanomaterials during washing, and the overall environmental impact of nanotextiles are important challenges that need to be ascertained and dealt with successfully in the coming years to ensure wide-scale acceptance and the global broad-spectrum application of nanotextiles [ 90 ].

The global market for the textile industry is constantly on the rise; with so many new brands, the competition is rising in regard to pricing, material, product outlook, and market exposure. Under this scenario, nanotechnology has contributed in terms of value addition to textiles by contributing the properties of water repellence, self-cleaning, and protection from radiation and UV light, along with safety against flames and microorganisms [ 82 ]. A whole new market of smart clothes is slowly taking our international markets along with improvements in textile machinery and economic standing. These advances have effectively established the sustainable character of the textile industry and have created grounds to meet the customer’s demand [ 91 ]. Some important examples of smart clothing originating from the nanotextile industry can be seen in products such as bulletproof jackets, fabric coatings, and advanced nanofibers. Fabric coatings and pressure pads can exhibit characteristics of invisibility and entail a silver, nickel, or gold nanoparticle-based material with inherent antimicrobial properties [ 92 ]. Such materials are effectively being utilized and introduced into the medical industry for bandages, dressings, etc. [ 92 ].

Similarly, woven optical fibers are already making progress in the textile and IT industry. With the incorporation of nanomaterials, optical fibers are being utilized for a range of purposes such as light transmission, sensing technologies, deformation, improved formational characteristic detection, and long-range data transmission. These optical fibers with phase-changing material properties can also be utilized for thermostability maintenance in the fiber industry. Thus, these fibers have combined applications in the computer, IT, and textile sectors [ 93 ]. In addition, the nano cellulosic material that is naturally obtained from plants confers properties of stiffness, strength, durability, and large surface area to volume ratios, which is acquired through the large number of surface hydroxyl groups embedded in nanocellulose particles [ 94 ]. Moreover, the characteristics of high resistance, lower weight, cost-effectiveness, and electrical conductivity are some additional benefits which are also linked to these nanocellulosic fibers [ 93 ]. The aforementioned technologies will allow industrialists to manufacture fabrics based on nanomaterials through a variety of chemical, physical, and biological processes. The scope of improvement in the textile properties, cost, and production methods is making the nanotextile industry a strong field of interest for future industrial investments.

2.9. Nanotechnology and Transport and Automobile Industry

The automotive industry is always improving its production. Nanotechnology is one such tool that could impart the automotive industry with a totally new approach to manufacturing. Automobile shaping could be improved greatly without any changes to the raw materials used. The replacement of conventional fabrication procedures with advanced nanomanufacturing is required to achieve the required outcome. Nanotechnology intends to partly renovate the automobile industry by enhancing the technical performance and reducing production costs excessively. However, there is a gap in fully harnessing the potential of nanomaterials in the automotive industry. Industrialists who were previously strict about automotive industrial principles are ready to employ novelties attached to nanotechnology to create successful applications to automobiles in the future [ 95 ]. Nanotechnology could provide assistance in manufacturing methods with an impartment of extended life properties. Cars that have been manufactured with nanotechnology applications have shown lower failure rates and enhanced self-repairing properties. Although the initial investment in the nanoautomated industry is high, the outcomes are enormous.

The concept of sustainable transport could also be applied to the manufacturing of such nano-based technology which is CO 2 free and imparts safe driving and quiet, clean, and wider-screen cars, which, in the future, may be called nanocars. The major interplay of nanotechnology and the automotive industry comes in the manufacturing of car parts, engines, paints, coating materials, suspensions, breaks, lubrication, and exhaust systems [ 32 ]. These properties are largely imparted via carbon nanotubes and carbon black, which renders new functionalities to automobiles. These products were previously in use, but nanoscaling and nanocoating allow for enhanced environmental, thermal, and mechanical stability to be imparted to the new generation of automobiles. In simple terms, automobiles manufactured with principal nanonovelties could result in cars with less wearing risk, better gliding potential, thinner coating lubrication requirements, and long service bodies with weight reductions [ 31 ]. These properties will ultimately reduce costs and will impart more space for improved automobile manufacturing in the future. Similarly, the development of electric cars and cars built on super capacitor technology is increasingly based on nanotechnology. The implications of nanotechnology in the form of rubber fillers, body frames made of light alloys, nanoelectronic components, nanocoatings of the interior and exterior of cars, self-repairing materials against external pressure, nanotextiles for interiors, and nanosensors are some of the nanotechnological-based implications of the automotive industry [ 96 ]. Owing to these properties, nanotechnology ventures are rapidly progressing in the automobile industry. It is expected that, soon, the automobile industry will commercialize nanotechnological perspectives on their branding strategies.

2.10. Nanotechnology, Healthcare, and Medical Industry

The genesis of nanomedicine simply cannot be ignored when we talk about the large fields of biological sciences, biotechnology, and medicine. Nanotechnology is already making its way beyond the imagination in the broader vision of nanobiotechnology. The quality of human life is continuously improved by the successful applications of nanotechnology in medicine, and resultantly, the entire new field of nanomedicine has come to the surface, which has allowed scientists to create upgraded versions of diagnostics, treatment, screening, sequencing, disease prevention, and proactive actions for healthcare [ 97 ]. These practices may also involve drug manufacturing, designing, conjugation, and efficient delivery options with advances in nano-based genomics, tissue engineering, and gene therapy. With this, it could be predicted that soon, nanomedicine will be the foremost research interest for the coming generation of biologists to study the useful impacts and risks that might be associated with them [ 98 ]. As illustrated in Figure 2 , we summarized the applications of nanotechnology in different subfields of the medical industry.

Nanotechnology applications in medical industry. Nanotechnology has a broad range of applications in various diagnostics and treatments using nanorobotics and drug delivery systems.

In various medical procedures, scientists are exploring the potential benefits of nanotechnology. In the field of medical tools, various robotic characters have been applied which have their origins in nano-scale computers, such as diagnostic surfaces, sensor technologies, and sample purification kits [ 99 ]. Similarly, some modifications are being accepted in diagnostics with the development of devices that are capable of working, responding, and modifying within the human body with the sole purpose of early diagnosis and treatment. Regenerative medicine has led to nanomanufacturing applications in addition to cell therapy and tissue engineering [ 100 ]. Similarly, some latest technologies in the form of ‘lab-on-a-chip’, as elaborated upon earlier, are being introduced with large implications in different fields such as nanomedicine, diagnostics, dentistry, and cosmetics industries [ 101 ]. Some updated nanotechnology applications in genomics and proteomics fields have developed molecular insights into antimicrobial diseases. Moreover, medicine, programming, nanoengineering, and biotechnology are being merged to create applications such as surgical nanorobotics, nanobioelectrics, and drug delivery methods [ 102 ]. All of these together help scientists and clinicians to better understand the pathophysiology of diseases and to bring about better treatment solutions in the future.

Specifically, the field of nanocomputers and linked devices help to control activation responses and their rates in mechanical procedures [ 2 ]. Through these mechanical devices, specific actions of medical and dental procedures are executed accurately. Moreover, programmed nanomachines and nanorobots allow medical practitioners to carry out medical procedures precisely at even sub-cellular levels [ 4 ]. In diagnostics fields, the use of such nanodevices is expanding rapidly, which allows predictions to be made about disease etiology and helps to regulate treatment options [ 103 ]. The use of in vitro diagnosis allows increased efficiency in disease apprehension. Meanwhile, in in vivo diagnoses, such devices have been made which carry out the screening of diseased states and respond to any kind of toxicities or carcinogenic or pathological irregularities that the body faces [ 104 ].

Similarly, the field of regenerative medicine is employing nanomaterials in various medical procedures such as cell therapy, tissue engineering, and gene sequencing for the greater outlook of treatment and reparation of cells, tissues, and organs. Nanoassemblies have been recorded in research for applications in powerful tissue regeneration technologies with properties of cell adhesion, migration, and cellular differentiation [ 102 ]. Additionally, nanotechnology is being applied in antimicrobial (antibacterial and antiviral) fields. The microscopic abilities of these pathogens are determined through nano-scale technologies [ 100 ]. Greek medicinal practices have long been using metals to cure pathogenic diseases, but the field of nanotechnology has presented a new method to improve such traditional medical practices; for example, nanosized silver nanomaterials are being used to cure burn wounds owing to the easy penetration of nanomaterials at the cellular level [ 102 , 105 ].

In the field of bioinformatics and computational biology, genomic and proteomic technologies are elucidating molecular insights into disease management [ 106 ]. The scope of targeted and personalized therapies related to pathogenic and pathophysiological diseases have greatly provided spaces for nanotechnological innovative technologies [ 107 , 108 ]. They also incorporate the benefits of cost-effectiveness and time saving [ 109 ]. Similarly, nanosensors and nanomicrobivores are utilized for military purposes such as the detection of airborne chemical agents which could cause serious toxic outcomes otherwise [ 102 ]. Some nanosensors also serve a purpose similar to phagocytes to clear toxic pathogens from the bloodstream without causing septic shock conditions, especially due to the inhalation of prohibited drugs and banned substances [ 100 , 105 , 110 ]. These technologies are also used for dose specifications and to neutralize overdosing incidences [ 110 ] Nano-scale molecules work as anticancer and antiviral nucleoside analogs with or without other adjuvants [ 21 ].

Another application of nanotechnology in the medical industry is in bone regeneration technology. Scientists are working on bone graft technology for bone reformation and muscular re-structuring [ 111 , 112 ]. Principle investigations of biomineralization, collagen mimic coatings, collagen fibers, and artificial muscles and joints are being conducted to revolutionize the field of osteology and bone tissue engineering [ 113 , 114 ]. Similarly, drug delivery technologies are excessively considering nanoscaling options to improve drug delivery stability and pharmacodynamic and pharmacokinetic profiles at a large scale [ 110 ]. The use of nanorobots is an important step that allows drugs to travel across the circulatory system and deliver drug entities to specifically targeted sites [ 99 , 115 ]. Scientists are even working on nanorobots-based wireless intracellular and intra-nucleolar nano-scale surgeries for multiple malignancies, which otherwise remain incurable [ 102 ]. These nanorobotics can work at such a minute level that they can even cut a single neuronic dendrite without causing harm to complex neuronal networks [ 116 ].

Another important application of nanotechnology in the medical field is oncology. Nanotechnology is providing a good opportunity for researchers to develop such nanoagents, fluorescent materials, molecular diagnostics kits, and specific targeted drugs that may help to diagnose and cure carcinogenesis [ 104 ]. Scientists are trying various protocols of adjoining already-available drugs with nanoparticulate conjugation to enhance drug specificity and targeting in organs [ 104 , 107 , 117 ]. Nanomedicine acts as the carrier of hundreds of specific anticancerous molecules that could be projected at tumor sites; moreover, the tumor imaging and immunotherapy approaches linked with nanomedicine are also a potential field of interest when it comes to cancer treatment management [ 112 , 117 ]. A focus is also being drawn toward lessening the impact of chemotherapeutic drugs by increasing their tumor-targeting efficiency and improving their pharmacokinetic and pharmacodynamic properties [ 112 ]. Similarly, heat-induced ablation treatment against cancer cells alongside gene therapy protocols is also being coupled with nanorobotics [ 99 , 118 ]. Anticancerous drugs may utilize the Enhanced Permeation and Retention Effect (EPR effect) by applications of nano assemblies such as liposomes, albumin nanospheres, micelles, and gold nanoparticles, which confirms effective treatment strategies against cancer [ 119 ]. Such advances in nanomedicine will bring about a more calculated, outlined, and technically programmed field of nanomedicine through association and cooperation between physicians, clinicians, researchers, and technologies.

2.10.1. Nanoindustry and Dentistry

Nanodentistry is yet another subfield of nanomedicine that involves broad-scale applications of nanotechnology ranging from diagnosis, prevention, cure, prognosis, and treatment options for dental care [ 120 ]. Some important applications in oral nanotechnology include dentition denaturalization, hypersensitivity cure, orthodontic realignment problems, and modernized enameling options for the maintenance of oral health [ 2 , 121 ]. Similarly, mechanical dentifrobots work to sensitize nerve impulse traffic at the core of a tooth in real-time calculation and hence could regulate tooth tissue penetration and maintenance for normal functioning [ 122 ]. The functioning is coupled with programmed nanocomputers to execute an action from external stimuli via connection with localized internal nerve stimuli. Similarly, there are other broad-range applications of nanotechnology in tooth repair, hypersensitivity treatment, tooth repositioning, and denaturalization technologies [ 4 , 118 , 120 , 121 ]. Some of the applications of nanotechnology in the field of dentistry are elaborated upon in Figure 3 .

Nanotechnology applications in field of dentistry. Nanotechnology can be largely used in dentistry to repair and treat dental issues.

2.10.2. Nanotechnology and Cosmetics Industry

The cosmetics industry, as part of the greater healthcare industry, is continuously evolving. Nanotechnology-based renovations are progressively incorporated into cosmetics industries as well. Products are designed with novel formulations, therapeutic benefits, and aesthetic output [ 123 ]. The nanocosmetics industry employs the usage of lipid nanocarrier systems, polymeric or metallic nanoparticles, nanocapsules, nanosponges, nanoemulsions, nanogels, liposomes, aquasomes, niosomes, dendrimers, and fullerenes, etc., among other such nanoparticles [ 101 ]. These nanomaterials bring about specific characteristics such as drug delivery, enhanced absorption, improved esthetic value, and enhanced shelf life. The benefits of nanotechnology are greatly captured in the improvement of skin, hair, nail, lip, and dental care products, and those associated with hygienic concerns. Changes to the skin barrier have been largely curtailed owing to the function of the nano scale of materials. The nanosize of active ingredients allows them to easily permeate skin barriers and generate the required dermal effect [ 124 ].

More profoundly, nanomaterials’ application is encouraged in the production of sun-protective cosmetics products such as sunblock lotions and creams. The main ingredient used is the rational combination of cinnamates (derived from carnauba wax) and titanium dioxide nanosuspensions which provide sun-protective effects in cosmetics products [ 125 ]. Similarly, nanoparticle suspensions are being applied in nanostructured lipid carriers (NLCs) for dermal and pharmaceutical applications [ 126 ]. They exhibit the properties of controlled drug-carrying and realizing properties, along with direct drug targeting, occlusion, and increased penetration and absorption to the skin surface. Moreover, these carrier nanoemulsions exhibit excellent tolerability to intense environmental and body conditions [ 127 ]. Moreover, these lipid nanocarriers have been researched and declared safe for potential cosmetic and pharmaceutical applications. However, more research is still required to assess the risk/benefit ratio of their excessive application [ 128 ].

2.11. Nanotechnology Industries and Environment

The environment, society, and technology are becoming excessively linked under a common slogan of sustainable development. Nanotechnology plays a key role in the 21st century to modify the technical and experimental outlook of various industries. Environmental applications cannot stand still against revolutionary applications of nanotechnology. Since the environment has much to do with the physical and chemical world around a living being, the nano scale of products greatly changes and affects environmental sustainability [ 129 ]. The subsequent introduction of nanomaterials in chemistry, physics, biotechnology, computer science, and space, food, and chemical industries, in general, directly impacts environmental sciences.

With regard to environmental applications, the remarkable research and applications of nanotechnology are increasing in the processing of raw materials, product manufacturing, contaminate treatment, soil and wastewater treatment, energy storage, and hazardous waste management [ 130 ]. In developed nations, it is now widely suggested that nanotechnology could play an effective role in tackling environmental issues. In fact, the application of nanotechnology could be implemented for water and cell cleaning technologies, drinking safety measures, and the detoxification of contaminants and pollutants from the environment such as heavy metals, organochlorine pesticides, and solvents, etc., which may involve reprocessing although nanofiltration. Moreover, the efficiency and durability of materials can be increased with mechanical stress and weathering phenomena. Similarly, the use of nanocage-based emulsions is being used for optical imaging techniques [ 131 ].

In short, the literature provides immense relevance to how nanotechnology is proving itself through groundbreaking innovative technologies in environmental sciences. The focus, for now, is kept on remediation technologies with prime attention on water treatment, since water scarcity is being faced worldwide and is becoming critical with time. There is a need for the scientific community to actively conduct research on comprehending the properties of nanomaterials for their high surface area, related chemical properties, high mobility, and unique mechanical and magnetic properties which could be used for to achieve a sustainable environment [ 132 ].

2.12. Nanotechnology—Oil and Gas Industry

The oil and gas industry makes up a big part of the fossil industry, which is slowly depleting with the rising consumption. Although nanotechnology has been successfully applied to the fields of construction, medicine, and computer science, its application in the oil and gas industry is still limited, especially in exploration and production technologies [ 133 ]. The major issue in this industry is to improve oil recovery and the further exploitation of alternative energy sources. This is because the cost of oil production and further purification is immense compared to crude oil prices. Nanotechnologists believe that they could overcome the technological barriers to developing such nanomaterials that would help in curtailing these problems.

Governments are putting millions of dollars into the exploration, drilling, production, refining, wastewater treatment, and transport of crude oil and gas. Nanotechnology can provide assistance in the precise measurement of reservoir conditions. Similarly, nanofluids have been proven to exhibit better performance in oil production industries. Nanocatalyses enhance the separation processing of oil, water, and gases, thus bringing an efficient impurity removal process to the oil and gas industry. Nanofabrication and nanomembrane technologies are excessively being utilized for the separation and purification of fossil materials [ 134 ]. Finally, functional and modified nanomaterials can produce smart, cost-effective, and durable equipment for the processing and manufacturing of oil and gas. In short, there is immense ground for the improvement of the fossil fuel industry if nanotechnology could be correctly directed in this industry [ 135 ].

2.13. Nanotechnology and Renewable Energy (Solar) Industry

Renewable energy sources are the solutions to many environmental problems in today’s world. This makes the renewable energy industry a major part of the environmental industry. Subsequently, nanotechnology needs to be considered in the energy affairs of the world. Nanotechnologies are increasingly applied in solar, hydrogen, biomass, geothermal, and tidal wave energy production. Although, scientists are convinced that much more needs to be discovered before enhancing the benefits of coupled nanotechnology and renewable energy [ 136 ].

Nanotechnology has procured its application way down the road of renewable energy sources. Solar collectors have been specifically given much importance since their usage is encouraged throughout the world, and with events of intense solar radiation, the production and dependence of solar energy will be helpful for fulfilling future energy needs. Research data are available regarding the theoretical, numerical, and experimental approaches adopted for upgrading solar collectors with the employment of nanotechnologies [ 137 ].

These applications include the nanoengineering of flat solar plates, direct absorption plates, parabolic troughs, and wavy plates and heat pipes. In most of these instruments and solar collection devices, the use of nanofluids is becoming common and plays a crucial role in increasing the working efficiency of these devices. A gap, however, exists concerning the usage of nanomaterials in the useful manufacturing design of solar panels and their associated possible efficiencies which could be brought to the solar panel industry. Moreover, work needs to be done regarding the cost-effectiveness and efficiency analyses of traditional and nanotechnology-based solar devices so that appropriate measures could be adopted for the future generation of nanosolar collectors [ 138 ].

2.14. Nanotechnology and Wood Industry

The wood industry is one of the main economic drivers in various countries where forest growth is immense and heavy industrial setups rely on manufacturing and selling wood-based products [ 139 ]. However, the rising environmental concerns against deforestation are a major cause for researchers to think about a method for the sustainable usage of wood products. Hence, nanotechnology has set its foot in the wood industry in various applications such as the production of biodegradable materials in the paper and pulp industry, timber and furniture industry, wood preservatives, wood composites, and applications in lignocellulosic-based materials [ 140 ]. Resultantly, new products are introduced into the market with enhanced performance (stronger yet lighter products), increased economic potential, and reduced environmental impact.

One method of nano-based application in the wood industry is the derivation of nanomaterials directly from the forest, which is now called nanocellulose material, known broadly for its sustainable characteristics [ 141 ]. This factor has pushed the wood industry to convert cellulosic material to nanocellulose with increased strength, low weight, and increased electromagnetic response along with a larger surface area [ 142 ]. These characteristics are then further used as reinforcing agents in different subcategories of wood-based industries, including substrate, stabilizer, electronics, batteries, sensor technologies, food, medicine, and cosmetics industries [ 143 ]. Moreover, functional characteristics such as the durability, UV absorption, fire resistance, and decreased water absorption of wood-based biodegradable products are also being improved with the application of nanomaterials such as nanozinc oxide or nanotitanium oxide [ 144 ]. Similarly, wood biodegradable properties are reduced through the application of nanoencapsulated preservatives to improve the impregnation of wood with the increasing penetration of applied chemicals and a reduced leaching effect.

Cellulosic nanomaterials exhibit nanofibrillar structures which can be made multifunctional for application in construction, furniture, food, pharmaceuticals, and other wood-based industries [ 145 ]. Research is emerging in which promising results are predicted in different industries in which nanofibers, nanofillers, nanoemulsions, nanocomposites, and nano-scaled chemical materials are used to increase the potential advantages of manufactured wood products [ 146 ]. The outstanding properties of nanocellulusice materials have largely curtailed the environmental concerns in the wood industry in the form of their potential renewable characteristics, self-assembling properties, and well-defined architecture. However, there are a few challenges related to such industries, such as cost/benefit analyses, a lack of compatibility and acceptability from the public owing to a lack of proper commercialization, and a persistent knowledge gap in some places [ 145 ]. Therefore, more effort is required to increase the applications and acceptability of nano-based wood products in the market worldwide.

2.15. Nanotechnology and Chemical Industries

Nanotechnology can be easily applied to various chemical compositions such as polymeric substances; this application can bring about structural and functional changes in those chemical materials and can address various industrial applications including medicine, physics, electronics, chemical, and material industries, among others [ 76 , 132 , 138 ]. One such industrial application is in electricity production, in which different nanomaterials driven from silver, golden, and organic sources could be utilized to make the overall production process cheaper and effective [ 147 ]. Another effective application is in the coatings and textile industry, which has already been discussed briefly. In these industries, enzymatic catalysis in combination with nanotechnology accelerates reaction times, saving money and bringing about high-quality final products. Similarly, the water cleaning industry can utilize the benefits of nanomaterials in the form of silver and magnetic nanoparticles to create strong forces of attraction that easily separate heavy material from untreated water [ 148 ]. Similarly, there is a wide range of chemicals that can be potentially upgraded, although the nano scale for application in biomedical industries is discussed under the heading of nanotechnology and medicine.

Another major application of nanotechnology in the chemical industry includes the surfactant industry, which is used for cleaning paper, inks, agrochemicals, drugs, pharmaceuticals, and some food products [ 149 ]. The traditional surfactant application was of great environmental and health concern, but with the newer and improved manufacturing and nanoscaling of surfactants, environmentally friendly applications have been made possible. These newer types may include biosurfactants obtained via the process of fermentation and bio-based surfactants produced through organic manufacturing. More research is required to establish the risks and side effects of these nanochemical agents [ 3 ].

3. Closing Remarks

Nanotechnology, within a short period, has taken over all disciplinary fields of science, whether it is physics, biology, or chemistry. Now, it is predicted to enormously impact manufacturing technology owing to the evidential and proven benefits of micro scaling. Every field of industry, such as computing, information technology, engineering, medicine, agriculture, and food, among others, is now originating an entire new field in association with nanotechnology. These industries are widely known as nanocomputer, nanoengineering, nanoinformatics, nanobiotechnology, nanomedicine, nanoagriculture, and nanofood industries. The most brilliant discoveries are being made in nanomedicine, while the most cost-effective and vibrant technologies are being introduced in materials and mechanical sciences.

The very purpose of nanotechnology, in layman’s terms, is to ease out the manufacturing process and improve the quality of end products and processes. In this regard, it is easy and predictable that it is not difficult for nanotechnology to slowly take out most of the manufacturing process for industrial improvement. With every coming year, more high-tech and more effective-looking nanotechnologies are being introduced. This is smoothing out the basis of a whole new era of nanomindustries. However, the constructive need is to expand the research basis of nanoapplications to entail the rigorous possible pros of this technology and simultaneously figure out a method to deal with the cons of the said technology.

The miniaturization of computer devices has continued for many years and is now being processed at the nanometer scale. However, a gap remains to explore further options for the nanoscaling of computers and complex electronic devices, including computer processors. Moreover, there is an immense need to enable the controlled production and usage of such nanotechnologies in the real world, because if not, they could threaten the world of technology. Scientists should keep on working on producing nanoelectronic devices with more power and energy efficiency. This is important in order to extract the maximum benefits from the hands of nanotechnology and computer sciences [ 5 ].

Under the influence of nanotechnology, food bioprocessing is showing improvement, as proven by several scientific types of research and industrial applications in food chain and agricultural fields. Moreover, the aspect of sustainability is being introduced to convert the environment, food chains, processing industries, and production methods to save some resources for future generations. The usage of precision farming technologies based upon nanoengineering, modern nano-scale fertilizers, and pesticides are of great importance in this regard. Moreover, a combined nanotechnological aspect is also being successfully applied to the food industry, affecting every dimension of packing, sensing, storage, manufacturing, and antimicrobial applications. It is pertinent to say that although the applications of nanotechnology in the food, agriculture, winemaking, poultry, and associated packaging industries are immense, the need is to accurately conduct the risk assessment and potential toxicity of nanomaterials to avoid any damage to the commercial food chains and animal husbandry practices [ 63 ].

The exposure of the nano-based building industry is immense for civil and mechanical engineers; now, we need to use these technologies to actually bring about changes in those countries in which the population is immense, construction material is depleting, and environmental sustainability problems are hovering upon the state. By carefully assessing the sustainability potential of these nanomaterials, their environmental, hazardous, and health risks could be controlled, and they could likely be removed from the construction and automobile industry all over the world with sincere scientific and technical rigor [ 150 ]. It is expected that soon, the construction and automobile industry will commercialize the nanotechnological perspectives alongside sustainability features in their branding strategies. These nano-scale materials could allow the lifecycle management of automotive and construction industries with the provision of sustainable, safe, comfortable, cost-effective, and more eco-friendly automobiles [ 32 ]. The need is to explore the unacknowledged and untapped potential of nanotechnology applications in these industry industries.

Similarly, nanotechnology-based applications in consumer products such as textile and esthetics industries are immense and impressive. Professional development involves the application of nanotechnology-based UV-protective coatings in clothes which are of utmost need with climatic changes [ 73 ]. The application of nanotechnology overcomes the limitations of conventional production methods and makes the process more suitable and green-technology-based. These properties have allowed the textile companies to effectively apply nanotechnology for the manufacture of better products [ 90 ]. With greater consumer acceptability and market demand, millions are spent in the cosmetic industry to enable the further usage of nanotechnology. Researchers are hopeful that nanotechnology would be used to further upgrade the cosmetics industry in the near future [ 123 ].

Furthermore, the breakthrough applications of nanomedicine are not hidden from the scientific community. If nanomedicine is accepted worldwide in the coming years, then the hope is that the domain of diagnosis and treatment will become more customized, personalized, and genetically targeted for individual patients. Treatment options will ultimately become excessive in number and more successful in accomplishment. However, these assumptions will stay a dream if the research remains limited to scientific understanding.

The real outcome will be the application of this research into the experimental domain and clinical practices to make them more productive and beneficial for the medical industry. For this cause, a combined effort of technical ability, professional skills, research, experimentation, and the cooperation of clinicians, physicians, researchers, and technology is imperative. However, despite all functional beneficial characteristics, work needs to be done and more exploration is required to learn more about nanotechnology and its potential in different industries, especially nanomedicine, and to take into account and curtail the risks and harms attached to the said domain of science.

Additionally, climatic conditions, as mentioned before, along with fossil fuel depletion, have pushed scientists to realize a low-energy-consuming and more productive technological renovation in the form of nanoengineered materials [ 48 ]. Now, they are employing nanomaterials to save energy and harvest the maximum remaining natural resources. There is immense ground for the improvement of the fossil fuel industry if nanotechnology could be correctly directed in this industry [ 135 ]. The beneficial applications within the solar industry, gas and oil industry, and conversion fields require comparative cost-effectiveness and efficiency analyses of traditional and nano-based technologies so that appropriate measures could be adopted for the future generation of nano-based products in said industries [ 138 ].

As every new technology is used in industries, linked social, ethical, environmental, and human safety issues arise to halt the pace of progress. These issues need to be addressed and analyzed along with improving nanotechnology so that this technology easily incorporates into different industries without creating social, moral, and ethical concerns. Wide-scale collaboration is needed among technologists, engineers, biologists, and industrials for a prospective future associated with the wide-scale application of nanotechnology in diversified fields.

4. Conclusions

Highly cost-effective and vibrant nanotechnologies are being introduced in materials and mechanical sciences. A comprehensive overview of such technologies has been covered in this study. This review will help researchers and professionals from different fields to delve deeper into the applications of nanotechnology in their particular areas of interest. Indeed, the applications of nanotechnology are immense, yet the risks attached to unlimited applications remain unclear and unpronounced. Thus, more work needs to be linked and carefully ascertained so that further solutions can be determined in the realm of nanotoxicology. Moreover, it is recommended that researchers, technicians, and industrialists should cooperate at the field and educational level to explore options and usefully exploit nanotechnology in field experiments. Additionally, more developments should be made and carefully assessed at the nano scale for a future world, so that we are aware of this massive technology. The magnificent applications of nanotechnology in the industrial world makes one think that soon, the offerings of nanotechnology will be incorporated into every possible industry. However, there is a need to take precautionary measures to be aware of and educate ourselves about the environmental and pollution concerns alongside health-related harms to living things that may arise due to the deviant use of nanotechnology. This is important because the aspect of sustainability is being increasingly considered throughout the world. So, by coupling the aspect of sustainability with nanotechnology, a prosperous future of nanotechnology can be guaranteed.

Funding Statement

K.M.’s work is supported by United Arab Emirates University-UPAR-Grant#G3458, SURE plus Grant#3908 and SDG research programme grant#4065.

Author Contributions

Conceptualization, Y.W. methodology, S.M. validation, S.M., K.M. and Y.W. formal analysis, S.M., K.M. and Y.W. investigation, S.M., K.M. and Y.W. resources, K.M. and Y.W. data curation, S.M., K.M. and Y.W. writing—original draft preparation, S.M. writing—review and editing, S.M., K.M. and Y.W. supervision, Y.W. project administration, K.M. and Y.W. funding acquisition, Y.W. and K.M. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

• April 21, 2024 | Ingenuity’s Final Transmission: NASA’s Mars Helicopter Team Says Goodbye … for Now
• April 21, 2024 | Groundbreaking AI Method Identifies New Parkinson’s Treatments 10x Faster
• April 21, 2024 | Breakthrough Device Brings Scientists a Step Closer to Successfully Growing Plants in Space
• April 21, 2024 | This Week @NASA: New Partners to the Artemis Accords, Altitude Chamber Upgrade, PACE Satellite
• April 21, 2024 | “Bizarre” Patterns Unearthed – Cambridge Study Challenges Traditional Views on Human Origins

Technology News

Read the latest technology news on SciTechDaily, your comprehensive source for the latest breakthroughs, trends, and innovations shaping the world of technology. We bring you up-to-date insights on a wide array of topics, from cutting-edge advancements in artificial intelligence and robotics to the latest in green technologies, telecommunications, and more.

Our expertly curated content showcases the pioneering minds, revolutionary ideas, and transformative solutions that are driving the future of technology and its impact on our daily lives. Stay informed about the rapid evolution of the tech landscape, and join us as we explore the endless possibilities of the digital age.

Discover recent technology news articles on topics such as Nanotechnology ,  Artificial Intelligence , Biotechnology ,  Graphene , Green Tech , Battery Tech , Computer Tech , Engineering , and Fuel-cell Tech featuring research out of MIT , Cal Tech , Yale , Georgia Tech , Karlsruhe Tech , Vienna Tech , and Michigan Technological University . Discover the future of technology with SciTechDaily.

Technology April 21, 2024

Breakthrough Device Brings Scientists a Step Closer to Successfully Growing Plants in Space

Researchers from the University of Illinois Urbana-Champaign have developed new, highly flexible sensors capable of monitoring and transmitting data on plant growth autonomously, according to…

MIT Unlocks the Power of 2D Magnets for Future Computing

Science Made Simple: How Do Lithium-Ion Batteries Work?

Turbocharged Skyrmions: Accelerating Toward the Future of Computing

Crucial Connection Completed: Laying the Foundation for the Quantum Internet

MIT’s New AI Model Predicts Human Behavior With Uncanny Accuracy

Reimagining Memory: New Research Reveals That Superconducting Loops Mimic the Brain

New Material Supercharges Electrostatic Energy Storage – 19x Energy Density

Quantum Internet Unleashed With HiFi’s Laser Breakthrough

Technology April 17, 2024

Researchers Develop “Goldene” – A New Form of Ultra-Thin Gold With Semiconductor Properties

For the first time, scientists have managed to create sheets of gold only a single atom layer thick. The material has been termed goldene. According…

Soaring Into the Future: DOE Researchers Develop Game-Changing Batteries for Air Taxis

Analysis of eVTOL batteries reveals unique operating demands. Researchers at the Department of Energy’s Oak Ridge National Laboratory are advancing clean transportation by developing and…

Quantum Stretch: Unveiling the Future of Elastic Displays

Intrinsically stretchable quantum dot-based light-emitting diodes achieved record-breaking performance. A team of South Korean scientists led by Professor KIM Dae-Hyeong of the Center for Nanoparticle…

Technology April 16, 2024

Revolutionizing 3D: New Holographic Technique Breaks Computational Barriers

A groundbreaking approach utilizes a split Lohmann lens-based diffraction model for the real-time creation of Computer-Generated Holography (CGH), dramatically lowering computational demands while preserving the…

Technology April 15, 2024

Revolutionizing Energy Storage: Li-CO2 Batteries With Carbon Capture

New technology could lead to batteries that store energy and capture CO2, offering a significant advancement in environmental technology. Efficient and cheap batteries that can…

“Extraordinary Potential” – The New Dawn of Low-Cost, High-Efficiency Solar Cells

Commercial solar panels currently have the capability to transform approximately 15% to 20% of the sunlight they capture into electrical power. However, experts at Soochow…

Technology April 14, 2024

How MIT Is Teaching AI to Avoid Toxic Mistakes

MIT’s novel machine learning method for AI safety testing utilizes curiosity to trigger broader and more effective toxic responses from chatbots, surpassing previous red-teaming efforts….

3D Magnetic Recording: Unprecedented Hard Drive Storage Density Unlocked

Possibility of ultra-high density hard disk drives with areal densities exceeding 10 Tbit/in² using multi-level magnetic recording. Research groups from NIMS, Seagate Technology, and Tohoku…

From Lab Curiosity to Industrial Reality: The New Dawn of Transition Metal Telluride Nanosheets

Nanosheets made from transition metal tellurides have demonstrated significant potential for basic research and applications in various fields, yet until recently, their large-scale production has…

Advertisement

Analytical study on the impact of technology in higher education during the age of COVID-19: Systematic literature review

• Published: 30 March 2021
• Volume 26 , pages 6719–6746, ( 2021 )

Cite this article

• Manar Abu Talib   ORCID: orcid.org/0000-0003-3001-0077 1 ,
• Anissa M. Bettayeb 1 &
• Razan I. Omer 1  

61k Accesses

65 Citations

3 Altmetric

Explore all metrics

With the advent of COVID-19 arose the need for social distancing measures, including the imposition of far-reaching lockdowns in many countries. The lockdown has wreaked havoc on many aspects of daily life, but education has been particularly hard hit by this unprecedented situation. The closure of educational institutions brought along many changes, including the transition to more technology-based education. This is a systematic literature review that seeks to explore the transition, in the context of the pandemic, from traditional education that involves face-to-face interaction in physical classrooms to online distance education. It examines the ways in which this transition has impacted academia and students and looks at the potential long-term consequences it may have caused. It also presents some of the suggestions made by the studies included in the paper, which may help alleviate the negative impact of lockdown on education and promote a smoother transition to online learning.

Avoid common mistakes on your manuscript.

1 Introduction

Severe acute respiratory syndrome, also known as COVID-19, is a contagious respiratory disease caused by the SARS-CoV-2 virus, which was first identified in a seafood market in Wuhan in late December 2019 (Huang, 2020 ).

The disease is airborne and mainly spreads through physical proximity with infected people. Clinical analysis results of the virus showed person-to-person transmission (Li et al., 2020 ). Broadly speaking, there are two modes of transmission—direct and indirect. The direct mode involves droplet and air transmission, while indirect transmission may occur via contaminated surfaces (Karia, 2020 ).

Due to its highly contagious nature, the COVID-19 virus swept the globe in the matter of weeks. Between December 2019 and October 2020, more than 45 million cases of COVID-19 were reported, including over a million deaths. (European Centre for Disease Prevention and Control, 2020 ). By March 2020, the epidemic was declared a pandemic by the World Health Organization (WHO, 2020 ).

The call for social distancing and limiting face-to-face contact outside the immediate family has never been louder. Social distancing is a deliberate increase in the physical gap between individuals to minimize the spread of disease (Red Cross, 2020 ).

Many facets of everyday life have been devastated by the pandemic. It prompted counties around the world to adopt a sequence of emergency response systems (Zhang et al., 2020 ). Authorities worldwide issued stay-at-home orders, imposing prolonged periods of lockdown, which led to a disruption in educational activities globally. This was done to curb infection rates and flatten the incidence curve in an effort to prevent healthcare systems from being overwhelmed.

In many parts of the world, this meant a temporary shutdown of educational institutions. These nationwide closures impacted millions of students and their families, particularly those from underprivileged communities (UNESCO, 2020 ).

Some of the educational institutions that faced closure progressively re-opened and started operating under online learning models in order to continue the academic progress of students, while simultaneously observing measures to reduce the impact of the current health crisis.

Previous outbreaks of infectious diseases such as swine flu have prompted significant school closures worldwide, with varying degrees of effectiveness (Barnum, 2020 ). If school closures happen late during a pandemic, they are less effective and may have little impact at all (Zumla et al., 2010 ). Educational institutions have been compelled to make an immediate transition to remote methods of learning that rely heavily on technology. The immediate transition to online learning has not made it possible for many to be adequately prepared for the challenges ahead (Hodges et al., 2020 ). This migration to remote learning had to be implemented as quickly as possible, and for many learning institutions, it happened several months into the academic year, leaving both staff and students with little time to plan, adjust and adapt.

This shed the light on various underlying economic and social issues. According to UNESCO, more than a billion learners worldwide have been affected at some point by the school closures that were initiated in response to the COVID-19 pandemic. As of November 2020, over 300 million learners spread across over 30 countries, which constitute approximately 18% of total enrolled learners, have been kept out of schools due to lockdown (UNESCO, 2020 ).

While the disruption in learning caused by COVID-19 is unprecedented, important insights can be gained about its far-reaching implications through an examination of relevant existing studies and data.

This paper is a systematic literature review that looks at the existing literature and discusses the crisis-response migration methods to technology-based online learning done by mainly higher learning institutions in terms of their impact on instructional delivery, students and faculty, and education as a whole. Firstly, it categorizes the studies in terms of which facet of education the impact of COVID-19 in was explored. Then, it performs a SWOT analysis on the digital transformation to online learning. In other words, it looks at the strengths, weaknesses, opportunities and threats. Lastly, it attempts to collect and summarize student and faculty feedback on online education and then outlines some of the recommendations made by either the students and faculty or the authors of the selected studies for improving the system.

The rest of the paper is divided into six sections. Section 2 discusses some of the related works, while Section 3 presents the methodology used in this study, including the selected research questions, search strategy, study selection process, quality assessment rules and data extraction strategy. It also presents some statistics about the selected papers. Section 4 presents the findings of the study and discusses them in detail, while Section 5 concludes with a summary of the research outcomes and possible future work. Section 6 constitutes an acknowledgement of various contributions to the creation of this paper.

2 Related work

In response to COVID-19, a lot of countries were faced with pressure to contain the spread of this highly contagious disease. To many educational institutions, this meant either partial or complete closure. Others transitioned to technology-based distance learning.

A systematic review was conducted by Viner et al. ( 2020 ) examines existing knowledge to identify the effects of school closures and other social distancing measures during outbreaks on infection rates and virus transmission. It suggested that school closures play a relatively small role in the control of disease transmission, and that the insignificant benefits such closures bring to transmission reduction could be easily outweighed by their profound negative economic and social consequences (Viner et al., 2020 ).

There is no strong evidence to support the effectiveness of full closure in controlling the pandemic. If anything, there are significant economic downfalls to such a response, not to mention the academic delay incurred by students. That is why a lot of academic institutions opted for the less drastic measure of transitioning to online distance education (ODE).

ODE is the use of the internet and certain other significant technology for the production of educational content, instructional delivery and program management (Fry, 2001 ). ODE can be delivered in two main formats: synchronous and asynchronous. As the name suggests, synchronous distance education (SDE) involves live, real-time interaction between teachers and students. It aims to simulate the communication model of a traditional classroom. Examples of SDE would include live webinars or virtual classrooms. Asynchronous education, on the other hand, introduces temporal flexibility. It does not require real-time interaction; instead, the educational material is available online for students to access at their own convenience. Examples of asynchronous education would be video recordings and emails (The Florida Center for Instructional Technology, n.d. ).

A systematic review and meta-analysis provided on randomized controlled trials (RCTs) conducted by papers released between January 2000 and March 2020 on the effectiveness and acceptance of SDE in health sciences as compared to more traditional educational methods measured the knowledge of students, their skills (using objective assessments) and their overall satisfaction (using subjective evaluations). It found there to be no significant difference between traditional education and synchronous distance education in terms of effectiveness and objective assessments. However, in subjective evaluations, SDE resulted in a higher satisfaction rating, indicating that it was preferred to some extent by students, despite being neither better nor worse in the earlier two measures (He et al., 2020 ).

Additionally, Carrillo & Flores ( 2020 ) conducted a review of the literature between January 2000 and April 2020 on online teaching and learning practices in teacher education to explore how and why online teaching and learning in teacher education occur, and also discussing its implications in the context of the pandemic. The review highlighted the complex nature of the model, discussing such factors as social, cognitive and teaching issues and the need for a comprehensive view of the pedagogy of online technology-based education used to support teaching and learning (Carrillo & Flores, 2020 ).

Daoud et al. ( 2020 ) conducted a systematic review focused on the issue of equity regarding home internet access by evaluating the educational value of having internet at home for school-aged children. It found a range of correlations that were mostly positive between access to home internet and educational value across three functions: qualification (academic knowledge and skills), subjectification (strengthening individuality) and socialization (of future citizens). However, the correlation was not straightforward, nor did it imply causation. The educational value in home internet use is influenced by variables regarding the nature of online activities such as how the technology is being used and socio-economic status (Daoud et al., 2020 ).

Di Pietro et al. ( 2020 ) produced a paper that attempts to explore the direct and indirect ways in which the COVID-19 pandemic may impact education. Based on the existing literature and pre-COVID-19 data, it made predictions about the impact on and future of education. The paper drew four main conclusions: 1) learning is expected to suffer a setback on average; 2) the effect on academic performance is likely to vary with socio-economic status; 3) inequality in socio-economic status may manifest in an emotional response, as those from less privileged backgrounds may be under more environmental stress; 4) the widening social gap may persist and have long-term implications (Di Pietro et al., 2020 ).

Some online emergency learning approaches are criticized for not adhering to sound pedagogical norms, best practices and prior studies (Hodges et al., 2020 ). Some have noted the potential negative effects of educational technology fixes being implemented quickly without balancing their effect (Selwyn et al., 2020 ; St. Amour, 2020 ). In addition, leaping into online education and online learning platforms has also raised concerns regarding surveillance and privacy and its impact on the lives of students (Harwell, 2020 ).

A study that aims to map the scientific literature in the areas of education and management in the context of the COVID-19 pandemic suggests the existence of three distinct groups or research flows in the published literature. These main themes were identified as: 1) education based on online constructs and distance learning; 2) the impact of COVID-19 from a management perspective; and 3) studies with a particular focus on Canada. The studies chosen for the analysis were found to be of various typologies, the most relevant of which was qualitative. The analysis revealed that research on the disruption in education and scientific production caused by the pandemic is rather scarce, which might be the result of the lack of empirical data (Rodrigues et al., 2020 ).

Since this phenomenon is still relatively recent, there is a lack of research that discusses the direct effect of the digital transformation in higher education caused by the pandemic, its pros, cons and future implications. This systematic literature review is different from those described above, as it provides an extensive review on the research done on the impact of the COVID-19 pandemic on formal education. Specifically, this study explores the ways in which the transition from traditional in-person educational models that involve face-to-face interaction and classroom teaching to ODE has impacted academia and students, and the consequences it might have had on student performance and the well-being of all involved.

The pandemic might have set in motion changes that are to last millennia in the way education is conducted across the globe. It is therefore imperative to study the direct impact of the pandemic on the education sector and understand the role it played in revolutionizing the way we think about education in order to make informed pedagogical choices in the future and ensure a smooth transition into more flexible but effective online teaching methods. As a result, our research paper has the following important contributions:

Explore the kind of changes the shift to online education has caused

Discuss the impact of these changes on students and teachers

Provide an insight into the current state of education and how the pandemic could affect its future

Table  1 summarizes the literature reviews discussed in this section as well as this study’s objective.

3 Methodology

This study is a Systematic Literature Review (SLR) based on the guidelines for performing such reviews laid out in the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (Moher et al., 2015 ), which are comprised of three main stages: search, eligibility and data collection and extraction. For example:

Search defines the search strategy in terms of what keywords and search engines or libraries will be used.

Eligibility is concerned with setting up inclusion and exclusion criteria aligned with the research objectives to specify the study and reporting standards, and then applying them to the collected papers.

Data collection and extraction is the process of obtaining eligible reports and extracting data from them in order to investigate the posed research questions.

This study tackles the topic of education during the COVID-19 pandemic and the accompanying shift to remote learning. The review process is composed of six stages. The first stage was coming up with research questions that reflect the aim of the study. The second involved collecting papers relevant to the topic. In the third stage, exclusion and inclusion criteria were defined and applied to the collected papers. The fourth stage involved extracting answers to the research questions from papers that made it through the final round of exclusion. The fifth and final stage was the synthesis of data obtained through this information extraction process to reach meaningful conclusions.

Figure  1 below illustrates this process.

Research methodology

3.1 Research questions

This systematic literature review aims to examine and summarize the impact COVID-19 had on education through the shift to online learning it caused in early 2020. The following five research questions were posed:

What are the aspects and impacts of COVID-19 on education?

RQ1 aims to identify the underlying theme or lens through which the impact of COVID-19 on education was explored in the papers. In other words, on what aspect of education or the educational system is the paper attempting to shed light on the impact of COVID-19?

What are the limitations of online education?

RQ2 examines the implemented online teaching models critically and identifies their flaws as defined in the research papers. This is the first phase of a SWOT analysis, which stands for strengths, weaknesses, opportunities, and threats. It considers the weakness and threats of online education.

What are the advantages & opportunities laid out by this digital transformation in higher education?

The aim of RQ3 is to recognize the benefits and opportunities presented by this unprecedented move toward digital-based learning in higher education institutions. This is the second phase of the SWOT analysis and it focuses on the digital transformation’s strengths and opportunities.

What was the feedback of students and teachers?

RQ4 collects and summarizes the responses of students and teachers to this transformation and how it impacted their experience.

What recommendations were made?

RQ5 attempts to summarize the recommendations put forward by either the authors of the studies or the people who participated in them.

3.2 Search strategy

The research questions were used as a guideline to roughly identify the main search keywords. Terms synonymous or highly related to the main search keywords were included in the search. Google Scholar was used for the search, which employed variations of the following search keywords: “COVID-19” “effects” “impact” “education” “higher education” “academia” “university” “online learning” “students” “teaching” “e-learning”.

The number of results varied by combination of keywords, but on average between 200 and 300 results showed up per search, a number increasing by the day given the current relevance of the topics at hand. The majority of papers came from journals.

3.3 Study selection

All papers based on the search keywords mentioned above that seemed, if only tenuously, relevant to the topic of education during COVID-19 were collected. Only papers that were published later than 2019 were retained. Papers that did not belong to high-quality, prestigious journals were excluded.

To ensure the quality of the selected papers and they do not belong to predatory journals, we first checked them against Elsevier’s abstract and citation database, Scopus. We also made sure they belonged to either the first quartile (Q1) or second quartile (Q2) according to the SCImago Journal Rank (SJR). SJR indicates the scientific influence of scholarly journals. Moreover, the journals were reviewed against Beall’s List, which is a list of predatory open-access publishers that did not perform proper peer review and they publish any article as long as the authors paid the open-access fee. This brought the number of papers selected for the purpose of this study down dramatically to 47—less than half of all papers collected initially.

As mentioned earlier, the search based on the selected keywords yielded somewhere between 100 and 300 results. Over 100 papers seemed relevant and were downloaded to serve as a starting point. Moving on, we filtered the papers based on their compliance with our inclusion criteria. The process can be summarized as follows:

download papers that showed up in the search results

delete any duplicates

apply the inclusion and exclusion criteria to get rid of any irrelevant papers

set aside survey and review papers

extract answers to the research questions from the selected papers while applying the quality assessment rules stated in section 3.4 that were designed to include only qualified papers.

Table  2 summarizes the applied inclusion and exclusion criteria of study papers.

3.4 Quality assessment rules (QARs)

This final step is to determine the quality of the collected research papers. To measure the quality of the papers included in the study and confirm their pertinence to our research objectives, ten Quality Assessment Rules (QARs) were set. Marks out of 10 were given to each paper based on its compliance with the established QARs. The QARs were formulated based on our understanding of the current state of research in this field and the research gap this paper is attempting to fill. The papers were scored for their ability to meet high research standards while adequately addressing our research question. For each of the ten questions, a paper is given a score as follows: “fully answered” = 1, “above average” = 0.75, “average” = 0.5, “below average” = 0.25, “not answered” = 0. The summation of the marks achieved for the 10 QARs is the paper’s ranking. Papers that score 5 or higher are accepted, while the remaining are excluded.

Are the study objectives clearly defined?

Is the impact of COVID-19 on education well-defined?

Is the specific context and usage (themes) clearly defined?

Is the study method well-designed and justifiable?

Is the scope of the study large enough?

Are the advantages and opportunities of the proposed teaching/technology methods well-explained?

Are the weaknesses and limitations of the proposed teaching/technology methods well-explained?

Are student/teacher evaluations reported?

Are the recommendations of the proposed methods suitable?

Overall, does the study enrich the academic community or industry?

3.5 Data extraction strategy

In this step, the final list of papers was analyzed to answer the research questions and extract any pertinent information.

The following information was extracted from each paper: Paper title, Publisher, Journal, month of publication, description of the paper’s objective, the answers to RQ1, RQ2, RQ3, RQ4 and RQ5.

Due to the indistinct terminology used within some papers and the relative narrowness of our research questions in comparison to the questions posed by the collected papers, there were gaps in the answer extraction as reflected in Fig.  4 .

In some cases, the authors had to infer answers that weren’t explicity expressed in the papers. This meant that some of the answers extracted were personal intrepretations of the findings done by the authors.

3.6 Statistics about the selected papers

As can be seen from Fig. 2 , Elsevier & IJWIL journals held the 2nd and 3rd positions, coming in at 19% and 17% respectively. Other publishers, including Springer, Routledge & MDPI, contributed similar amounts of papers and came at 13% of the total paper count or less.

Publishers of the selected papers by frequency

However, 32% of the papers were put out by miscellaneous publishers. These publishers include: The BMJ, ACS Publication, Science Press, Wiley, Taylor and Francis Ltd., Primrose Hall Publishing Group, Scientific Research Publishing, Academy of Science of South Africa, Association for Learning Technology, Association for Social Studies Educators, Modestum and Kathmandu University.

Figure  3 shows the months of publication of the selected papers. It is noteworthy that the largest number of papers relevant to this review were produced in July, three to four months after many lockdowns were implemented and distance learning was put in effect. The number of papers selected for this review subsequently declined. For 13 of the selected papers, the month of publication was either not explicitly specified or couldn’t be identified by the authors.

Frequency of selected papers by month

As can be seen from Fig. 4 , all research questions were answered by more than 70% of the papers, which speaks to their broadness and generality. The only exception was RQ5, which had a 61.70% answer rate, mostly from papers discussing the topic of “student experience”, as will be shown in the following section.

Frequency of answers for each research question

4 Results and discussion

The majority of educational institutions in the chosen studies migrated to distance learning. While not all papers specified the particular methods or platforms employed, video conferencing, E-portals, webinars, websites, video recordings, simulations and online quizzes were frequently listed as the primary means of conducting classes and evaluating student performance.

A total of 47 studies were compiled using the quality criteria mentioned in section 3.4 . A list of these studies is included in Table  7 in Appendix A. Here in section 4 , we present the findings of this literature review. The outcomes of each research question are explored in detail in each of the following five sections.

4.1 Area of focus

In this section, the first research question (RQ1) is addressed, which aims to identify the underlying theme or lens through which the impact of COVID-19 on education was explored in the papers. There were four main identifiable themes:

Impact on Education : explores the transition from traditional classroom teaching methods to more technology-based learning, and the impact of that transition.

Student Experience : explores the impact the lockdown had on students either academically or personally and their experience with ODE as well as their academic performance using remote learning methods.

Proposal : proposes and/or experiments with a remote teaching method or platform.

Policy : explores the responses to the pandemic and the role of policymaking in leveling the playfield in education.

Equality : discusses the disparity observed between different social groups during the pandemic and the impact it had on accessibility and equity.

In this review, 25 papers discussed the impact of COVID-19 on education, namely the digital transformation driven by it, its advantages and disadvantages, and what this could mean going forward.

Eighteen papers included discussions about the experience of students and staff with ODE, as well as the participants’ views on its potential upsides and downsides. Most of the answers given for RQ5 came from this group.

Four papers proposed solutions for remote learning or experimented with a particular platform to analyze its efficacy.

Three papers looked at the current academic situation through a political lens, discussing education-related policy in light of the pandemic.

Two papers discussed how the lockdown and the accompanying transition to technology-based learning further exacerbated differences in educational progress between the children of lower income families with limited access to Wi-Fi and digital devices or services and those of higher income families that do not share the same struggles.

Figure  5 highlights the differences in the frequency of the discussed areas. It is worth noting that these percentages add up to more than 100% because there is overlap between the papers in terms of the areas chosen for discussion.

Topics discussed in selected papers

4.2 Disadvantages & limitations

This section addresses research question 2 (RQ2), which takes a critical view of the implemented teaching models and identifies their shortcomings as described in the papers that studied or mentioned them.

The key disadvantages can be summarized in the following points:

Inequality & inaccessibility : there is a gap in student access to this type of education, which is usually related to family income.. Transitioning to online learning exacerbated differences between privileged and underprivileged students. Students from less prosperous regions have limited or no access to digital devices and Wi-Fi. They also have lower technical abilities., granting more privileged students an unfair academic advantage. This disparity extends to educational institutions in rural areas or deprived parts of the world that may be less well-equipped than those in urban areas.

Inadequacy : while technology can be a great aid to the learning experience, it cannot act as a complete substitute, particularly for STEM fields that require hands-on training in laboratories or operation rooms. This is especially true for health care sciences. 34% of the chosen studies focused on medical education specifically, looking at nursing or residency programs in particular. These papers tended to emphasize the value of practical training and how indirect knowledge gained from simulations or demonstration videos alone cannot act as a substitute.

Communication quality : building and sustaining relationships and developing rapport between students, their peers, and their teachers became more difficult due to the devaluation or lack of face-to-face contact, as well as the inherent ambiguity of written interactions.. Clarifying instructions and gauging student response, engagement and participation, or lack thereof, becomes more difficult for teachers and instructors in the absence of direct contact and the ability to monitor students face-to-face.

Technical difficulties : poor internet reception or Wi-Fi, connection stability, glitches and other technical failures can interfere with the flow of communication.

Stress, workload and morale : the forced and rapid transition to online learning affected mental health among students. Many experienced lockdown-related anxieties about financial stability and socializing that indirectly affected their performance. Academic staff had to deal with an increased or even doubled workload. Also, lack of face-to-face social interaction for extended periods of time can have a detrimental effect on mental health.

Technological literacy : due to the sudden and forced nature of this digital transition, a lot of educational institutions were caught off-guard, allowing them little to no time to prepare their academic staff. This left non-tech savvy teachers and instructors underprepared and/or underequipped to handle sophisticated computer and internet related tasks. Instructors’ lack of technological competence and previous training in or familiarity with utilizing online tools posed an obstacle. The inability of academic staff to use technology negatively impacted the success of ODE in many cases.

Student engagement, participation and motivation : student engagement was sometimes lacking due to factors such as reliance on recorded lectures, a lack of motivation or interest, stress and boredom, as well as the distraction caused by using electronic devices. Added to this was fatigue induced by prolonged staring at screens and feelings of isolation and depression from lack of personal contact.

Student performance assessment : due to the difficulties associated with bringing students to campus to administer tests, academic staff were faced with the challenge of redesigning evaluations in a way that fairly and reliably captured student performance. This was particularly challenging in practical courses.

Work-life balance : ODE allows great flexibility in time and location. While this flexibility may be convenient, it’s a double-edged sword that could also blur the boundaries between academic and personal life. Whereas in conventional educational models lectures are strictly bound by fixed times and physical locations.

Privacy concerns : concerns about breach of privacy, data protection and anonymous misconduct.

Table  3 lists the research articles that mentioned disadvantages and limitations of distance education based on the aforementioned points.

4.3 Advantages & opportunities

This section addresses research question 3 (RQ3), which aims to identify the advantages and opportunities laid by this digital transformation in education.

There are several main identifiable key advantages and opportunities. They can be summarized as follows:

Remote learning : ODE transcends the borders of time and geographical location. It allows students the flexibility to tune in into their lectures from the comfort of their own homes or any other location. It also allows students to self-regulate their learning and proceed at their own pace thanks to the temporal flexibility of online learning, which is made possible by features such as lecture recording.

Discussion & Communication : online learning facilitates a modern and convenient mode of communication. Important discussions can be raised during lectures and participating students can benefit from these discussions by listening or by engaging through chat. It is also an effective means of communication as participants do not have to meet in person or face the discomfort that can accompany speaking in front of a live audience, thereby further encouraging discussion. Online learning also helps parents of young children to be more involved in their children’s education.

Impetus for change : this forced digital transformation in education exposed problems within the system and pushed educators to contemplate and review current and previous models of education, providing a window into what a technology-based education and work environment might be like, thereby stimulating pedagogical innovations and accelerating change. It is hastening progress and can be viewed as an impetus for the reform of curriculum and teaching approaches.

Equally effective : the implementation of online learning and the use of simulations and other methods for didactic purposes were perceived as useful and adequate, if not complete, substitutes for traditional learning. It accomplished its goal of continuing the delivery of education amidst the pandemic, while also helping students meet the requirements expected from them.

Efficient : contributed to or improved knowledge dissemination, with cost-effectiveness, flexibility and overall efficiency as added benefits.

Exposure to tech : incorporating technology into education exposes students to modern and relevant technologies. This helps both students and academic staff close the technological literacy gap while also fostering expertise in online and digital media, thereby preparing students for the job market in an increasingly technology-reliant world of digitization and automation.

Decreased costs : the shift to online education can be credited for the decrease in educational costs. It provides students with a comparable learning experience without the need for expensive infrastructure, not to mention a reduction in other hidden costs such as travel expenses.

Table  4 lists the research articles that mentioned advantages and opportunities of distance education based on the aforementioned points.

4.4 Student and teacher feedback

This section addresses the fourth research question (RQ4), which aims to gauge the response of students and teachers to this transformation and how it impacted their experience.

The papers that explored the topic of student experience provided the main insights to this question, which can be summarized as follows:

Satisfactory or beneficial : ODE was regarded as a good learning experience and helpful in the sense that it assisted in cultivating knowledge in a unique and efficient manner.

Adequate and effective : ODE was deemed satisfactory in achieving its objective of continuing education. In some cases, it was thought to have had no significant impact on studies. And in other cases it was thought to boost productivity.

Expressed doubts or concern : participants expressed doubts about the efficacy of ODE, uncertainty about the future, and concern over the long-term consequences of the digital transformation on health, security and equity..

Overwhelming : some staff had difficulty adjusting given how abrupt the transition was. Many had to devise new student performance assessment methods to compensate for the inability to directly monitor students in exams and quizzes. In some cases, the transition led to an increase in workload.

Potential : some participants thought ODE could support their teaching or studies, recommended it for future use or viewed it as a catalyst for revision of existing norms.

Appreciation for staff or peers : participants expressed appreciation and gratitude towards others within the institution for their efforts in coping with the situation, providing assistance and being responsive.

Improvement in performance : ODE was thought to enhance efficiency, performance and attention, as well as help in the learning process.

Preferred to traditional : although students expressed sentiments of missing peer-to-peer interaction, the majority were open to and some even favoured ODE to conventional learning that requires physical attendance and is restricted to classrooms. This may be due to the flexibility, convenience and low cost of online learning.

Anxiety inducing : some participants reported feelings of stress or anxiety in trying to grapple with the current pandemic situation while adapting to the new learning scheme.

Table  5 lists the research articles that described feedback received on distance education based on the aforementioned points.

4.5 Study recommendations

This section addresses research question 5 (RQ5), which attempts to summarize the recommendations put forward by either the authors of the selected studies or the people who participated in them.

The following are the key recommendations made:

Support for students : boosting and maintaining motivation of students to improve morale and help combat any lockdown-induced stress or anxiety.

High-quality tools : providing accessible, user-friendly, error-free and high-quality E-learning portals and other types of online platforms.

Providing & receiving feedback : providing and receiving feedback to and from students to improve the quality of online education.

Investigating efficacy : exploring the outcomes of ODE and reflecting on the differences between it and traditional education in order to ascertain which aspects of it are viable and meet the demands sets by the pandemic situation. This is also to assist teachers in employing effective teaching techniques and to enable researchers and institutions to continue the development of online educational tools.

Stating objectives : students need to feel the relevance of the study material to the real world, as well as understand the course requirements. To that end, teachers must spell out expectations and clarify course objectives as well as the importance of the syllabus. They also need to delineate their roles and responsibilities as lecturers and mentors early on in the academic year.

Policymaking : policymakers should seek to understand and mitigate any risks or inequalities created by this rapid transition to online learning, which may be caused by income or workload disparities.

Redesign : the revisiting and rethinking of pedagogical strategies and the development of orienting principles to guide the transition to online education, as well as making the necessary adjustments to infrastructure.

Training of staff & students : providing students and teachers with adaptability training to familiarize them with technology, increase their competence and prepare them to deal with technical issues that can occur during online lectures. This will also help in the smart application of technology to realize its potential in the realm of online education.

Diversifying : maximizing efficiency by avoiding reliance on a single method or platform and instead using a variety of online learning resources. For example, a course could use both video conferencing and text messaging.

Broadening accessibility : this could mean providing underequipped students with the equipment necessary to partake in online activities, such as electronic devices and stable internet connection.

Table  6 lists the research articles that made recommendations based on the points listed above.

5 Conclusion and future work

It goes with without saying that the COVID-19 pandemic has had profound impacts on society and on the way humans organize themselves in the real world. It has exposed systematic issues within institutions and brought about long overdue changes. The educational system was no exception to this.

This review aimed to look at and evaluate the impact these changes have had on education, with a particular focus on the digital transformation and the shift to online learning caused by the pandemic. To do so, we took a look at more than 40 papers from high impact journals that touched on the topic of education during the times of COVID-19.

Many institutions and governments were underprepared for this abrupt migration to technology-based working and learning. This resulted in issues of inequality, lack of access and lack of skills to facilitate this type of learning. There are limitations inherent to ODE that prevent it from acting as a full substitute to traditional education. This is particularly true in fields where hands-on training is an absolute necessity to meet learning requirements.

On the plus side, the new forced dependence on technology in education may hasten some already underway changes. On the negative side, requiring children to continue their studies at home may worsen educational disparities caused by inequalities.

From the viewpoint of learners and educators, there are a range of difficulties in switching from offline to online learning modes. Another stumbling block in the acceptance of online teaching is involving students and indulging them in teaching-learning progression. It takes an hour to create content that not only covers the curriculum, but also inspires learners.

We found that some of the key disadvantages of ODE that were cited in the collected papers were inequality of access, inadequacy of online teaching, poor communication quality, technical difficulties, increased workload and stress, low technological literacy, difficulty in assessment of student engagement and performance, bad work-life balance and some privacy concerns.

Whereas the main advantages of ODE according to the papers were flexibility and convenience, discussion & communication, effectiveness as a didactic tool, efficiency, decreased costs, increased exposure to technology and that it was seen as an impetus for change.

The papers that explored the topic of student experience aimed to gauge the response of students and teachers to this transformation and how it impacted their experience and we found that the main feedback point given was that online education was satisfactory, beneficial and effective. However, some expressed doubts over the efficacy of remote learning, uncertainty about the future, and concern over the long-term consequences on health, security and access due to this digital transformation. Others found it to be overwhelming or anxiety inducing. However, some observed an improvement in performance and expressed more appreciation towards their peers and faculty members.

Although the adoption of online teaching during COVID-19 is commendable, the quality of teaching and courses offered online must also be developed and strengthened. Some of the advice that has been put forward to help in that regard includes supporting students by improving morale, providing high-quality e-learning tools, giving and receiving feedback from students, investigating the outcomes of ODE, clarifying course objectives and expectations to students, providing training for students and teachers to familiarize them with technology, diversfying instructional delivery methods, broadening accessibility to online learning, soliciting policymakers to make necessary changes and the revisiting and redesigning of pedagogical strategies.

The flexibilty and convenience ODE offers and the much-needed push for change it has inspired cannot be denied. However, its efficiency in terms of student outcome as compared to traditional education is still a point of dispute. It is therefore imperative to continue investigating online education. Policymakers should take the findings of research on education seriously in order to bridge whatever gaps may be present.

Future research could draw from a broader diversity of sources to reach wider conclusions.

Data availability

The data is available to anyone for review.

Code availability

Not applicable.

Adedoyin, O. B., & Soykan, E. (2020). Covid-19 pandemic and online learning: The challenges and opportunities. Interactive Learning Environments , 1–13. https://doi.org/10.1080/10494820.2020.1813180 .

Agarwal, S., & Dewan, J. (2020). An Analysis of the Effectiveness of Online Learning in Colleges of Uttar Pradesh during the COVID 19 Lockdown Page No : 2957. Journal of Xi’an University of Architecture & Technology, XII (V), 2957–2963.

Google Scholar  

Al Lily, A. E., Ismail, A. F., Abunasser, F. M., & Alhajhoj Alqahtani, R. H. (2020). Distance education as a response to pandemics: Coronavirus and Arab culture. Technology in Society, 63 (July), 101317. https://doi.org/10.1016/j.techsoc.2020.101317 .

Article   Google Scholar  

Ali, K. A. G., Khalil, H. E. M., & El-Sharkawy, F. M. (2020). Impacts of online remote education on the learning process among nursing students. Open Journal of Nursing, 10 (09), 810–830. https://doi.org/10.4236/ojn.2020.109057 .

Almarzooq, Z. I., Lopes, M., & Kochar, A. (2020). Virtual learning during the COVID-19 pandemic: A disruptive Technology in Graduate Medical Education. Journal of the American College of Cardiology, 75 (20), 2635–2638. https://doi.org/10.1016/j.jacc.2020.04.015 .

Al-Taweel, D., Al-Haqan, A., Bajis, D., Al-Bader, J., Al-Taweel, A. R. M., Al-Awadhi, A., & Al-Awadhi, F. (2020). Multidisciplinary academic perspectives during the COVID-19 pandemic. International Journal of Health Planning and Management , July, 1–7. https://doi.org/10.1002/hpm.3032 .

Alvi, M., & Gupta, M. (2020). Learning in times of lockdown: How Covid-19 is affecting education and food security in India. Food Security, 12 (4), 793–796. https://doi.org/10.1007/s12571-020-01065-4 .

Barnum, M. (2020). Should schools close due to coronavirus? Here's what research says. Chalkbeat. Retrieved March 2021, from https://www.chalkbeat.org/2020/3/9/21178727/to-close-or-not-to-close-as-schools-weigh-tradeoffs-in-light-of-coronavirus-here-s-what-research-say .

Batholmeus, P. N. (n.d.). Using simulations to improve skills needed for work- integrated learning before and during COVID-19 in Namibia.

Briant, S. (2020). Reimagining internships through online experiences: Multi- disciplinary engagement for creative industries students.

Carmody, C., Brown, L., & Fabbro, L. D. E. L. (2020). Preparing for work-integrated learning during COVID-19: How a new virtual orientation tool facilitated access for all .

Carrillo, C., & Flores, M. A. (2020). COVID-19 and teacher education: A literature review of online teaching and learning practices. https://doi.org/10.1080/02619768.2020.1821184 .

Chatziralli, I., Ventura, C. V., Touhami, S., Reynolds, R., Nassisi, M., Weinberg, T., Pakzad-Vaezi, K., Anaya, D., Mustapha, M., Plant, A., Yuan, M., & Loewenstein, A. (2020). Transforming ophthalmic education into virtual learning during COVID-19 pandemic: A global perspective. Eye (Basingstoke). https://doi.org/10.1038/s41433-020-1080-0 .

Chick, R. C., Clifton, G. T., Peace, K. M., Propper, B. W., Hale, D. F., Alseidi, A. A., & Vreeland, T. J. (2020). Using technology to maintain the education of residents during the COVID-19 pandemic. Journal of Surgical Education, 77 (4), 729–732. https://doi.org/10.1016/j.jsurg.2020.03.018 .

Daoud, R., Starkey, L., Eppel, E., Vo, T. D., & Sylvester, A. (2020). The educational value of internet use in the home for school children: A systematic review of literature. Journal of Research on Technology in Education, 0 (0), 1–22. https://doi.org/10.1080/15391523.2020.1783402 .

Darras, K. E., Spouge, R. J., de Bruin, A. B. H., Sedlic, A., Hague, C., & Forster, B. B. (2020). Undergraduate radiology education during the COVID-19 pandemic: A review of teaching and learning strategies. Canadian Association of Radiologists Journal . https://doi.org/10.1177/0846537120944821 .

Di Pietro, G., Biagi, F., Costa, P., Karpiński, Z., & Mazza, J. (2020). The likely impact of COVID-19 on education: Reflections based on the existing literature and recent international datasets. In publications Office of the European Union, Luxembourg: Vol. EUR, 30275 (Issue JRC121071). https://doi.org/10.2760/126686 .

Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., Gupta, B., Lal, B., Misra, S., Prashant, P., Raman, R., Rana, N. P., Sharma, S. K., & Upadhyay, N. (2020). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management , 102211. https://doi.org/10.1016/j.ijinfomgt.2020.102211 .

Ehrlich, H., McKenney, M., & Elkbuli, A. (2020). We asked the experts: Virtual learning in surgical education during the COVID-19 pandemic—Shaping the future of surgical education and training. World Journal of Surgery, 44 (7), 2053–2055. https://doi.org/10.1007/s00268-020-05574-3 .

European Centre for Disease Prevention and Control (2020). COVID-19 situation update worldwide, as of 9 November 2020 . Retrieved November 9 2020, from https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases .

Fry, K. (2001). E-learning markets and providers: Some issues and prospects. Education+Training, 43 (4/5), 233–239. https://doi.org/10.1108/EUM0000000005484 .

Harfouche, A. L., & Nakhle, F. (2020). Creating bioethics distance learning through virtual reality. Trends in Biotechnology, 38 (11), 1187–1192. https://doi.org/10.1016/j.tibtech.2020.05.005 .

Harwell, D. (2020). Mass school closures in the wake of the coronavirus are driving a new wave of student surveillance. Washington Post. Retrieved March 2020, from https://www.washingtonpost.com/technology/2020/04/01/online-proctoring-college-exams-coronavirus/ .

Hasan, N., & Bao, Y. (2020). Impact of “e-learning crack-up” perception on psychological distress among college students during COVID-19 pandemic: A mediating role of “fear of academic year loss”. Children and Youth Services Review, 118 (July), 105355. https://doi.org/10.1016/j.childyouth.2020.105355 .

He, L., Yang, N., Xu, L., Ping, F., Li, W., Sun, Q., & Li, Y. (2020). Synchronous distance education vs traditional education for health science students : A systematic review and meta-analysis . July , 1–16. https://doi.org/10.1111/medu.14364 .

Hedding, D. W., Greve, M., Breetzke, G. D., Nel, W., & van Vuuren, B. J. (2020). COVID-19 and the academe in South Africa: Not business as usual. South African Journal of Science, 116 (8), 8–10. https://doi.org/10.17159/sajs.2020/8298 .

Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between emergency remote teaching and online learning. Retrieved March 2021, from https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning .

Huang, J. (2020). Successes and Challenges: Online Teaching and Learning of Chemistry in Higher Education in China in the Time of COVID-19. Journal of Chemical Education, 97 (9), 2810–2814. https://doi.org/10.1021/acs.jchemed.0c00671 .

Hudson, L., Engel-Hills, P., & Winberg, C. (2020). The potential of a simulated workplace environment for emergency remote teaching. International Journal of Work-Integrated Learning, 21 (5), 559–572.

Ibraheem, M., Ahmed, A., & Hassan, M. (2020). University education in KSA in COVID times : Status. Challenges and Prospects., 14 (3), 971–984.

Jes, A., Leal-costa, C., & Moral-garc, E. (2020). Experiences of nursing students during the abrupt change from face-to-face to e-learning education during the first month of confinement due to COVID-19 in Spain.

Kara, N., Çubukçuoğlu, B., & Elçi, A. (2020). Using social media to support teaching and learning in higher education: An analysis of personal narratives. Research in Learning Technology, 28 (1063519), 1–16. https://doi.org/10.25304/rlt.v28.2410 .

Karia, R. (2020). COVID-19 and its modes of transmission. In 1798–1801 .

Khalaf, K., El-Kishawi, M., Moufti, M. A., & Al Kawas, S. (2020). Introducing a comprehensive high-stake online exam to final-year dental students during the COVID-19 pandemic and evaluation of its effectiveness. Medical Education Online, 25 (1). https://doi.org/10.1080/10872981.2020.1826861 .

Kidd, W., & Murray, J. (2020). The Covid-19 pandemic and its effects on teacher education in England: How teacher educators moved practicum learning online. European Journal of Teacher Education, 43 (4), 542–558. https://doi.org/10.1080/02619768.2020.1820480 .

Kim, J. (2020). Learning and teaching online during Covid-19: Experiences of student teachers in an early childhood education Practicum. International Journal of Early Childhood, 52 (2), 145–158. https://doi.org/10.1007/s13158-020-00272-6 .

Levkoe, C. Z., Knezevic, I., Appavoo, D., Moraes, A., & Scott, S. (2020). Serving up food studies online: Teaching about “food from somewhere” from nowhere. Food, Culture . Society, 23 (3), 434–453. https://doi.org/10.1080/15528014.2020.1754041 .

Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K., Lau, E., Wong, J., Xing, X., Xiang, N., Wu, Y., Li, C., Chen, Q., Li, D., Liu, T., Zhao, J., Liu, M., . . . Feng, Z. (2020). Early transmission dynamics in Wuhan, China, of novel coronavirus–infected pneumonia. New England Journal of Medicine, 382 (13), 1199–1207.

Matters, M. E., Brightman, A. O., Buzzanell, P. M., & Zoltowski, C. B. (2020). Inclusive teaching in isolating situations: Impact of COVID-19 on efforts toward increasing diversity in BME. Biomedical Engineering Education. https://doi.org/10.1007/s43683-020-00012-1 .

McRoy, C., Patel, L., Gaddam, D. S., Rothenberg, S., Herring, A., Hamm, J., Chelala, L., Weinstein, J., Smith, E., & Awan, O. (2020). Radiology education in the time of COVID-19: A novel distance learning workstation experience for residents. Academic Radiology, 27 (10), 1467–1474. https://doi.org/10.1016/j.acra.2020.08.001 .

Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., et al. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4 (1), 1.

Mulenga, E. M., & Marbán, J. M. (2020). Prospective teachers’ online learning mathematics activities in the age of COVID-19: A cluster analysis approach. Eurasia Journal of Mathematics, Science and Technology Education, 16 (9). https://doi.org/10.29333/EJMSTE/8345 .

Murray, C., Heinz, M., Munday, I., Keane, E., Flynn, N., Connolly, C., Hall, T., & MacRuairc, G. (2020). Reconceptualising relatedness in education in ‘distanced’ times. European Journal of Teacher Education, 43 (4), 488–502. https://doi.org/10.1080/02619768.2020.1806820 .

Novikov, P. (2020). Impact of COVID-19 emergency transition to on-line learning on international students’ perceptions of educational process at Russian University. Journal of Social Studies Education Research, 11 (3), 270–302.

MathSciNet   Google Scholar  

Papouli, E., Chatzifotiou, S., & Tsairidis, C. (2020). The use of digital technology at home during the COVID-19 outbreak: Views of social work students in Greece. Social Work Education, 00 (00), 1–9. https://doi.org/10.1080/02615479.2020.1807496 .

Patel, N. M., Khajuria, A., & Khajuria, A. (2020). Utility of a webinar to educate trainees on UK core surgical training (CST) selection – A cross sectional study and future implications amidst the COVID-19 pandemic. Annals of Medicine and Surgery, 59(August), 35–40. https://doi.org/10.1016/j.amsu.2020.08.05 4

Pather, N., Blyth, P., Chapman, J. A., Dayal, M. R., Flack, N. A. M. S., Fogg, Q. A., Green, R. A., Hulme, A. K., Johnson, I. P., Meyer, A. J., Morley, J. W., Shortland, P. J., Štrkalj, G., Štrkalj, M., Valter, K., Webb, A. L., Woodley, S. J., & Lazarus, M. D. (2020). Forced disruption of anatomy education in Australia and New Zealand: An acute response to the Covid-19 pandemic. Anatomical Sciences Education, 13 (3), 284–300. https://doi.org/10.1002/ase.1968 .

Practicum, T. (2020). Preservice teachers use of WhatsApp to explain subject content to school children during the COVID-19 pandemic.

Rasalam, R. O. Y. (2020). Virtual WIL clinics in medicine : Overcoming the COVID-19 challenge.

Red Cross. (2020). What social distancing means. Retrieved February 2021, from https://www.redcross.org/about-us/news-and-events/news/2020/coronavirus-what-social-distancing-means.html .

Rizun, M., & Strzelecki, A. (2020). Students ’ acceptance of the COVID-19 impact on shifting higher education to distance learning in Poland. 1–19.

Rodrigues, M., Franco, M., & Silva, R. (2020). COVID-19 and disruption in management and education academics: Bibliometric mapping and analysis. Sustainability (Switzerland), 12 (18). https://doi.org/10.3390/SU12187362 .

Rodriguez-segura, L., Zamora-antuñano, M. A., & Rodríguez-reséndiz, J. (2020). Teaching challenges in COVID-19 scenery: Teams platform-based student satisfaction approach. 1–29. https://doi.org/10.3390/su12187514

Salter, C. (2019). Working remotely : Innovative allied health placements in response to COVID-19.

Sandi-Urena, S. (2020). Experimentation skills away from the chemistry laboratory: Emergency remote teaching of multimodal laboratories. Journal of Chemical Education, 97 (9), 3011–3017. https://doi.org/10.1021/acs.jchemed.0c00803 .

Selwyn, N., Hillman, T., Eynon, R., Ferreira, G., Knox, J., Macgilchrist, F., & Sancho-Gil, J. M. (2020). What’s next for Ed-tech? Critical hopes and concerns for the 2020s. Learning, Media and Technology, 45 (1), 1–6. https://doi.org/10.1080/17439884.2020.1694945 .

Shahzad, A., Hassan, R., Aremu, A. Y., Hussain, A., & Lodhi, R. N. (2020). Effects of COVID-19 in E-learning on higher education institution students: the group comparison between male and female. Quality and Quantity , 0123456789. https://doi.org/10.1007/s11135-020-01028-z .

Sharma, K., Deo, G., Timalsina, S., Joshi, A., Shrestha, N., & Neupane, H. C. (2020). Online learning in the face of COVID-19 pandemic: Assessment of students’ satisfaction at Chitwan medical college of Nepal. Kathmandu University Medical Journal, 18 (19 70COVID-Special Issue), 38–45.

St. Amour, M. (2020). Privacy and the online pivot. Inside higher Ed. Retrieved March 2021, from https://www.insidehighered.com/news/2020/03/25/pivot-onlineraises-concerns-ferpa-surveillance .

The Florida Center for Instructional Technology. (n.d.). A Teacher's Guide to Distance Learning. Retrieved November 9 2020, from https://fcit.usf.edu/distance/chap1.htm#:~:text=Distance%20Learning%20can%20be%20roughly,live%22%20video%20of%20an%20instructor .

Thomas, M. S. C., & Rogers, C. (2020). Education, the science of learning, and the COVID-19 crisis. Prospects, 49 (1–2), 87–90. https://doi.org/10.1007/s11125-020-09468-z .

UNESCO (2020). Education: From disruption to recovery. Retrieved November 9 2020, from https://en.unesco.org/covid19/educationresponse .

Viner, R. M., Russell, S. J., Croker, H., Packer, J., Ward, J., Stansfield, C., Mytton, O., Bonell, C., & Booy, R. (2020). Review School closure and management practices during coronavirus outbreaks including COVID-19 : a rapid systematic review. The Lancet Child and Adolescent Health, 2019 (20), 1–8. https://doi.org/10.1016/S2352-4642(20)30095-X .

WHO (2020). WHO Director-General's opening remarks at the media briefing on COVID-19 - 11 March 2020. Retrieved November 9 2020, from https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19%2D%2D-11-march-2020#:~:text=We%20have%20therefore%20made%20the,to%20unnecessary%20suffering%20and%20death .

Wyres, M., & Taylor, N. (2020). Covid-19: Using simulation and technology-enhanced learning to negotiate and adapt to the ongoing challenges in UK healthcare education. BMJ Simulation and Technology Enhanced Learning , 1–3. https://doi.org/10.1136/bmjstel-2020-000642 .

Zegwaard, K. E., & Rowe, A. D. (2020). Responding to an international crisis : The adaptability of the practice of work-integrated learning.

Zhang, W., Wang, Y., Yang, L., & Wang, C. (2020) Suspending classes without stopping learning: China’s education emergency management policy in the COVID-19 outbreak. Journal of Risk and Financial Management, 13 (3), 55.

Zumla, A., Yew, W. W., & Hui, D. S. (2010). Emerging respiratory infections in the 21st century: An issue of infectious disease clinics-E-B.

Download references

Acknowledgments

The authors would like to thank University of Sharjah and OpenUAE Research and Development Group for funding this research study. We are also grateful to our research assistants who helped in collecting, summarizing, and analyzing the research articles for this SLR study.

This research paper was funded by the University of Sharjah (for OpenUAE Research and Development Group).

Author information

Authors and affiliations.

University of Sharjah, P. O. Box: 27272, Sharjah, United Arab Emirates

Manar Abu Talib, Anissa M. Bettayeb & Razan I. Omer

You can also search for this author in PubMed   Google Scholar

Contributions

All authors contributed to the study conception and design. The tasks of literature search, data analysis and manuscript drafting and revision were split between the authors. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Manar Abu Talib , Anissa M. Bettayeb or Razan I. Omer .

Ethics declarations

Conflict of interest.

The authors declare there are no conflicts of interest, financial or otherwise.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 21 kb)

Rights and permissions.

Reprints and permissions

About this article

Abu Talib, M., Bettayeb, A.M. & Omer, R.I. Analytical study on the impact of technology in higher education during the age of COVID-19: Systematic literature review. Educ Inf Technol 26 , 6719–6746 (2021). https://doi.org/10.1007/s10639-021-10507-1

Download citation

Received : 18 December 2020

Accepted : 16 March 2021

Published : 30 March 2021

Issue Date : November 2021

DOI : https://doi.org/10.1007/s10639-021-10507-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Online learning
• Performance
• Find a journal
• Publish with us
• Track your research

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

•  We're Hiring!
•  Help Center

Modern Technology

• Most Cited Papers
• Most Downloaded Papers
• Newest Papers
• Save to Library
• World Wide Web Follow Following
• User interfaces Follow Following
• Social Networking Follow Following
• Web 2.0 Follow Following
• Epekto Ng Makabagong Teknolohiya Sa Mga Kabataan Ngayon Follow Following
• Information Seeking Behaviour Follow Following
• User Studies Follow Following
• Universe Follow Following
• Japanese Anime Follow Following
• Tendering Follow Following

Enter the email address you signed up with and we'll email you a reset link.

• Academia.edu Publishing
•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

• Publications
• Our Methods
• Short Reads
• Tools & Resources

Read Our Research On:

About 1 in 5 U.S. teens who’ve heard of ChatGPT have used it for schoolwork

Roughly one-in-five teenagers who have heard of ChatGPT say they have used it to help them do their schoolwork, according to a new Pew Research Center survey of U.S. teens ages 13 to 17. With a majority of teens having heard of ChatGPT, that amounts to 13% of all U.S. teens who have used the generative artificial intelligence (AI) chatbot in their schoolwork.

Teens in higher grade levels are particularly likely to have used the chatbot to help them with schoolwork. About one-quarter of 11th and 12th graders who have heard of ChatGPT say they have done this. This share drops to 17% among 9th and 10th graders and 12% among 7th and 8th graders.

There is no significant difference between teen boys and girls who have used ChatGPT in this way.

The introduction of ChatGPT last year has led to much discussion about its role in schools , especially whether schools should integrate the new technology into the classroom or ban it .

Pew Research Center conducted this analysis to understand American teens’ use and understanding of ChatGPT in the school setting.

The Center conducted an online survey of 1,453 U.S. teens from Sept. 26 to Oct. 23, 2023, via Ipsos. Ipsos recruited the teens via their parents, who were part of its KnowledgePanel . The KnowledgePanel is a probability-based web panel recruited primarily through national, random sampling of residential addresses. The survey was weighted to be representative of U.S. teens ages 13 to 17 who live with their parents by age, gender, race and ethnicity, household income, and other categories.

This research was reviewed and approved by an external institutional review board (IRB), Advarra, an independent committee of experts specializing in helping to protect the rights of research participants.

Here are the  questions used for this analysis , along with responses, and its  methodology .

Teens’ awareness of ChatGPT

Overall, two-thirds of U.S. teens say they have heard of ChatGPT, including 23% who have heard a lot about it. But awareness varies by race and ethnicity, as well as by household income:

• 72% of White teens say they’ve heard at least a little about ChatGPT, compared with 63% of Hispanic teens and 56% of Black teens.
• 75% of teens living in households that make $75,000 or more annually have heard of ChatGPT. Much smaller shares in households with incomes between $30,000 and $74,999 (58%) and less than $30,000 (41%) say the same.

Teens who are more aware of ChatGPT are more likely to use it for schoolwork. Roughly a third of teens who have heard a lot about ChatGPT (36%) have used it for schoolwork, far higher than the 10% among those who have heard a little about it.

When do teens think it’s OK for students to use ChatGPT?

For teens, whether it is – or is not – acceptable for students to use ChatGPT depends on what it is being used for.

There is a fair amount of support for using the chatbot to explore a topic. Roughly seven-in-ten teens who have heard of ChatGPT say it’s acceptable to use when they are researching something new, while 13% say it is not acceptable.

However, there is much less support for using ChatGPT to do the work itself. Just one-in-five teens who have heard of ChatGPT say it’s acceptable to use it to write essays, while 57% say it is not acceptable. And 39% say it’s acceptable to use ChatGPT to solve math problems, while a similar share of teens (36%) say it’s not acceptable.

Some teens are uncertain about whether it’s acceptable to use ChatGPT for these tasks. Between 18% and 24% say they aren’t sure whether these are acceptable use cases for ChatGPT.

Those who have heard a lot about ChatGPT are more likely than those who have only heard a little about it to say it’s acceptable to use the chatbot to research topics, solve math problems and write essays. For instance, 54% of teens who have heard a lot about ChatGPT say it’s acceptable to use it to solve math problems, compared with 32% among those who have heard a little about it.

Note: Here are the  questions used for this analysis , along with responses, and its  methodology .

• Artificial Intelligence
• Technology Adoption
• Teens & Tech

Many Americans think generative AI programs should credit the sources they rely on

Americans’ use of chatgpt is ticking up, but few trust its election information, q&a: how we used large language models to identify guests on popular podcasts, striking findings from 2023, what the data says about americans’ views of artificial intelligence, most popular.

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

• Age & Generations
• Coronavirus (COVID-19)
• Economy & Work
• Family & Relationships
• Gender & LGBTQ
• Immigration & Migration
• International Affairs
• Internet & Technology
• Methodological Research
• News Habits & Media
• Non-U.S. Governments
• Other Topics
• Politics & Policy
• Race & Ethnicity
• Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

Copyright 2024 Pew Research Center

Terms & Conditions

Privacy Policy

Cookie Settings

Reprints, Permissions & Use Policy

Paper: To understand cognition—and its dysfunction—neuroscientists must learn its rhythms

Thought emerges and is controlled in the brain via the rhythmically and spatially coordinated activity of millions of neurons, scientists argue in a new article. Understanding cognition and its disorders requires studying it at that level.

It could be very informative to observe the pixels on your phone under a microscope, but not if your goal is to understand what a whole video on the screen shows. Cognition is much the same kind of emergent property in the brain . It can only be understood by observing how millions of cells act in coordination, argues a trio of MIT neuroscientists. In a new article , they lay out a framework for understanding how thought arises from the coordination of neural activity driven by oscillating electric fields—also known as brain “waves” or “rhythms.”

Historically dismissed solely as byproducts of neural activity, brain rhythms are actually critical for organizing it, write Picower Professor Earl Miller and research scientists Scott Brincat and Jefferson Roy in Current Opinion in Behavioral Science . And while neuroscientists have gained tremendous knowledge from studying how individual brain cells connect and how and when they emit “spikes” to send impulses through specific circuits, there is also a need to appreciate and apply new concepts at the brain rhythm scale, which can span individual, or even multiple, brain regions.

“Spiking and anatomy are important but there is more going on in the brain above and beyond that,” said senior author Miller, a faculty member in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences at MIT. “There’s a whole lot of functionality taking place at a higher level, especially cognition.”

The stakes of studying the brain at that scale, the authors write, might not only include understanding healthy higher-level function but also how those functions become disrupted in disease.

“Many neurological and psychiatric disorders, such as schizophrenia, epilepsy and Parkinson’s involve disruption of emergent properties like neural synchrony,” they write. “We anticipate that understanding how to interpret and interface with these emergent properties will be critical for developing effective treatments as well as understanding cognition.”

The emergence of thoughts

The bridge between the scale of individual neurons and the broader-scale coordination of many cells is founded on electric fields, the researchers write. Via a phenomenon called “ephaptic coupling,” the electrical field generated by the activity of a neuron can influence the voltage of neighboring neurons, creating an alignment among them. In this way, electric fields both reflect neural activity but also influence it. In a paper in 2022 , Miller and colleagues showed via experiments and computational modeling that the information encoded in the electric fields generated by ensembles of neurons can be read out more reliably than the information encoded by the spikes of individual cells. In 2023 Miller’s lab provided evidence that rhythmic electrical fields may coordinate memories between regions.

At this larger scale, in which rhythmic electric fields carry information between brain regions, Miller’s lab has published numerous studies showing that lower-frequency rhythms in the so-called “beta” band originate in deeper layers of the brain’s cortex and appear to regulate the power of faster-frequency “gamma” rhythms in more superficial layers. By recording neural activity in the brains of animals engaged in working memory games the lab has shown that beta rhythms carry “top down” signals to control when and where gamma rhythms can encode sensory information, such as the images that the animals need to remember in the game.

Some of the lab’s latest evidence suggests that beta rhythms apply this control of cognitive processes to physical patches of the cortex, essentially acting like stencils that pattern where and when gamma can encode sensory information into memory, or retrieve it. According to this theory, which Miller calls “ Spatial Computing ,” beta can thereby establish the general rules of a task (for instance, the back and forth turns required to open a combination lock), even as the specific information content may change (for instance, new numbers when the combination changes). More generally, this structure also enables neurons to flexibly encode more than one kind of information at a time, the authors write, a widely observed neural property called “mixed selectivity.” For instance, a neuron encoding a number of the lock combination can also be assigned, based on which beta-stenciled patch it is in, the particular step of the unlocking process that the number matters for.

In the new study Miller, Brincat and Roy suggest another advantage consistent with cognitive control being based on an interplay of large-scale coordinated rhythmic activity: “Subspace coding.” This idea postulates that brain rhythms organize the otherwise massive number of possible outcomes that could result from, say, 1,000 neurons engaging in independent spiking activity. Instead of all the many combinatorial possibilities, many fewer “subspaces” of activity actually arise, because neurons are coordinated, rather than independent. It is as if the spiking of neurons is like a flock of birds coordinating their movements.  Different phases and frequencies of brain rhythms provide this coordination, aligned to amplify each other, or offset to prevent interference. For instance, if a piece of sensory information needs to be remembered, neural activity representing it can be protected from interference when new sensory information is perceived.

“Thus the organization of neural responses into subspaces can both segregate and integrate information,” the authors write.

The power of brain rhythms to coordinate and organize information processing in the brain is what enables functional cognition to emerge at that scale, the authors write. Understanding cognition in the brain, therefore, requires studying rhythms.

“Studying individual neural components in isolation—individual neurons and synapses—has made enormous contributions to our understanding of the brain and remains important,” the authors conclude. “However, it’s becoming increasingly clear that, to fully capture the brain’s complexity, those components must be analyzed in concert to identify, study, and relate their emergent properties.”

Related Articles

Study reveals a universal pattern of brain wave frequencies.

Anesthesia blocks sensation by cutting off communication within the cortex

Anesthesia technology precisely controls unconsciousness in animal tests

A multifunctional tool for cognitive neuroscience

To revisit this article, visit My Profile, then View saved stories .

• Backchannel
• Newsletters
• WIRED Insider
• WIRED Consulting

Amanda Hoover

Students Are Likely Writing Millions of Papers With AI

Students have submitted more than 22 million papers that may have used generative AI in the past year, new data released by plagiarism detection company Turnitin shows.

A year ago, Turnitin rolled out an AI writing detection tool that was trained on its trove of papers written by students as well as other AI-generated texts. Since then, more than 200 million papers have been reviewed by the detector, predominantly written by high school and college students. Turnitin found that 11 percent may contain AI-written language in 20 percent of its content, with 3 percent of the total papers reviewed getting flagged for having 80 percent or more AI writing. (Turnitin is owned by Advance, which also owns Condé Nast, publisher of WIRED.) Turnitin says its detector has a false positive rate of less than 1 percent when analyzing full documents.

ChatGPT’s launch was met with knee-jerk fears that the English class essay would die . The chatbot can synthesize information and distill it near-instantly—but that doesn’t mean it always gets it right. Generative AI has been known to hallucinate , creating its own facts and citing academic references that don’t actually exist. Generative AI chatbots have also been caught spitting out biased text on gender and race . Despite those flaws, students have used chatbots for research, organizing ideas, and as a ghostwriter . Traces of chatbots have even been found in peer-reviewed, published academic writing .

Teachers understandably want to hold students accountable for using generative AI without permission or disclosure. But that requires a reliable way to prove AI was used in a given assignment. Instructors have tried at times to find their own solutions to detecting AI in writing, using messy, untested methods to enforce rules , and distressing students. Further complicating the issue, some teachers are even using generative AI in their grading processes.

Detecting the use of gen AI is tricky. It’s not as easy as flagging plagiarism, because generated text is still original text. Plus, there’s nuance to how students use gen AI; some may ask chatbots to write their papers for them in large chunks or in full, while others may use the tools as an aid or a brainstorm partner.

Students also aren't tempted by only ChatGPT and similar large language models. So-called word spinners are another type of AI software that rewrites text, and may make it less obvious to a teacher that work was plagiarized or generated by AI. Turnitin’s AI detector has also been updated to detect word spinners, says Annie Chechitelli, the company’s chief product officer. It can also flag work that was rewritten by services like spell checker Grammarly, which now has its own generative AI tool . As familiar software increasingly adds generative AI components, what students can and can’t use becomes more muddled.

Detection tools themselves have a risk of bias. English language learners may be more likely to set them off; a 2023 study found a 61.3 percent false positive rate when evaluating Test of English as a Foreign Language (TOEFL) exams with seven different AI detectors. The study did not examine Turnitin’s version. The company says it has trained its detector on writing from English language learners as well as native English speakers. A study published in October found that Turnitin was among the most accurate of 16 AI language detectors in a test that had the tool examine undergraduate papers and AI-generated papers.

Emily Mullin

Joel Khalili

C. Brandon Ogbunu

Schools that use Turnitin had access to the AI detection software for a free pilot period, which ended at the start of this year. Chechitelli says a majority of the service’s clients have opted to purchase the AI detection. But the risks of false positives and bias against English learners have led some universities to ditch the tools for now. Montclair State University in New Jersey announced in November that it would pause use of Turnitin’s AI detector. Vanderbilt University and Northwestern University did the same last summer.

“This is hard. I understand why people want a tool,” says Emily Isaacs, executive director of the Office of Faculty Excellence at Montclair State. But Isaacs says the university is concerned about potentially biased results from AI detectors, as well as the fact that the tools can’t provide confirmation the way they can with plagiarism. Plus, Montclair State doesn’t want to put a blanket ban on AI, which will have some place in academia. With time and more trust in the tools, the policies could change. “It’s not a forever decision, it’s a now decision,” Isaacs says.

Chechitelli says the Turnitin tool shouldn’t be the only consideration in passing or failing a student. Instead, it’s a chance for teachers to start conversations with students that touch on all of the nuance in using generative AI. “People don’t really know where that line should be,” she says.

You Might Also Like …

In your inbox: The best and weirdest stories from WIRED’s archive

Jeffrey Epstein’s island visitors exposed by data broker

8 Google employees invented modern AI. Here’s the inside story

The crypto fraud kingpin who almost got away

Listen up! These are the best podcasts , no matter what you’re into

Benj Edwards, Ars Technica

Will Knight

Matt Burgess

Reece Rogers

Steven Levy

Stephen Ornes