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Online and face‐to‐face learning: Evidence from students’ performance during the Covid‐19 pandemic
1 Department of Economics, University of Pretoria, Hatfield South Africa
2 Department of Education Innovation, University of Pretoria, Hatfield South Africa
This study investigates the factors that predict students' performance after transitioning from face‐to‐face to online learning as a result of the Covid‐19 pandemic. It uses students' responses from survey questions and the difference in the average assessment grades between pre‐lockdown and post‐lockdown at a South African university. We find that students' performance was positively associated with good wifi access, relative to using mobile internet data. We also observe lower academic performance for students who found transitioning to online difficult and who expressed a preference for self‐study (i.e. reading through class slides and notes) over assisted study (i.e. joining live lectures or watching recorded lectures). The findings suggest that improving digital infrastructure and reducing the cost of internet access may be necessary for mitigating the impact of the Covid‐19 pandemic on education outcomes.
The Covid‐19 pandemic has been a wake‐up call to many countries regarding their capacity to cater for mass online education. This situation has been further complicated in developing countries, such as South Africa, who lack the digital infrastructure for the majority of the population. The extended lockdown in South Africa saw most of the universities with mainly in‐person teaching scrambling to source hardware (e.g. laptops, internet access), software (e.g. Microsoft packages, data analysis packages) and internet data for disadvantaged students in order for the semester to recommence. Not only has the pandemic revealed the already stark inequality within the tertiary student population, but it has also revealed that high internet data costs in South Africa may perpetuate this inequality, making online education relatively inaccessible for disadvantaged students. 1
The lockdown in South Africa made it possible to investigate the changes in second‐year students' performance in the Economics department at the University of Pretoria. In particular, we are interested in assessing what factors predict changes in students' performance after transitioning from face‐to‐face (F2F) to online learning. Our main objectives in answering this study question are to establish what study materials the students were able to access (i.e. slides, recordings, or live sessions) and how students got access to these materials (i.e. the infrastructure they used).
The benefits of education on economic development are well established in the literature (Gyimah‐Brempong, 2011 ), ranging from health awareness (Glick et al., 2009 ), improved technological innovations, to increased capacity development and employment opportunities for the youth (Anyanwu, 2013 ; Emediegwu, 2021 ). One of the ways in which inequality is perpetuated in South Africa, and Africa as a whole, is through access to education (Anyanwu, 2016 ; Coetzee, 2014 ; Tchamyou et al., 2019 ); therefore, understanding the obstacles that students face in transitioning to online learning can be helpful in ensuring more equal access to education.
Using students' responses from survey questions and the difference in the average grades between pre‐lockdown and post‐lockdown, our findings indicate that students' performance in the online setting was positively associated with better internet access. Accessing assisted study material, such as narrated slides or recordings of the online lectures, also helped students. We also find lower academic performance for students who reported finding transitioning to online difficult and for those who expressed a preference for self‐study (i.e. reading through class slides and notes) over assisted study (i.e. joining live lectures or watching recorded lectures). The average grades between pre‐lockdown and post‐lockdown were about two points and three points lower for those who reported transitioning to online teaching difficult and for those who indicated a preference for self‐study, respectively. The findings suggest that improving the quality of internet infrastructure and providing assisted learning can be beneficial in reducing the adverse effects of the Covid‐19 pandemic on learning outcomes.
Our study contributes to the literature by examining the changes in the online (post‐lockdown) performance of students and their F2F (pre‐lockdown) performance. This approach differs from previous studies that, in most cases, use between‐subject designs where one group of students following online learning is compared to a different group of students attending F2F lectures (Almatra et al., 2015 ; Brown & Liedholm, 2002 ). This approach has a limitation in that that there may be unobserved characteristics unique to students choosing online learning that differ from those choosing F2F lectures. Our approach avoids this issue because we use a within‐subject design: we compare the performance of the same students who followed F2F learning Before lockdown and moved to online learning during lockdown due to the Covid‐19 pandemic. Moreover, the study contributes to the limited literature that compares F2F and online learning in developing countries.
Several studies that have also compared the effectiveness of online learning and F2F classes encounter methodological weaknesses, such as small samples, not controlling for demographic characteristics, and substantial differences in course materials and assessments between online and F2F contexts. To address these shortcomings, our study is based on a relatively large sample of students and includes demographic characteristics such as age, gender and perceived family income classification. The lecturer and course materials also remained similar in the online and F2F contexts. A significant proportion of our students indicated that they never had online learning experience before. Less than 20% of the students in the sample had previous experience with online learning. This highlights the fact that online education is still relatively new to most students in our sample.
Given the global experience of the fourth industrial revolution (4IR), 2 with rapidly accelerating technological progress, South Africa needs to be prepared for the possibility of online learning becoming the new norm in the education system. To this end, policymakers may consider engaging with various organizations (schools, universities, colleges, private sector, and research facilities) To adopt interventions that may facilitate the transition to online learning, while at the same time ensuring fair access to education for all students across different income levels. 3
1.1. Related literature
Online learning is a form of distance education which mainly involves internet‐based education where courses are offered synchronously (i.e. live sessions online) and/or asynchronously (i.e. students access course materials online in their own time, which is associated with the more traditional distance education). On the other hand, traditional F2F learning is real time or synchronous learning. In a physical classroom, instructors engage with the students in real time, while in the online format instructors can offer real time lectures through learning management systems (e.g. Blackboard Collaborate), or record the lectures for the students to watch later. Purely online courses are offered entirely over the internet, while blended learning combines traditional F2F classes with learning over the internet, and learning supported by other technologies (Nguyen, 2015 ).
Moreover, designing online courses requires several considerations. For example, the quality of the learning environment, the ease of using the learning platform, the learning outcomes to be achieved, instructor support to assist and motivate students to engage with the course material, peer interaction, class participation, type of assessments (Paechter & Maier, 2010 ), not to mention training of the instructor in adopting and introducing new teaching methods online (Lundberg et al., 2008 ). In online learning, instructors are more facilitators of learning. On the other hand, traditional F2F classes are structured in such a way that the instructor delivers knowledge, is better able to gauge understanding and interest of students, can engage in class activities, and can provide immediate feedback on clarifying questions during the class. Additionally, the designing of traditional F2F courses can be less time consuming for instructors compared to online courses (Navarro, 2000 ).
Online learning is also particularly suited for nontraditional students who require flexibility due to work or family commitments that are not usually associated with the undergraduate student population (Arias et al., 2018 ). Initially the nontraditional student belonged to the older adult age group, but with blended learning becoming more commonplace in high schools, colleges and universities, online learning has begun to traverse a wider range of age groups. However, traditional F2F classes are still more beneficial for learners that are not so self‐sufficient and lack discipline in working through the class material in the required time frame (Arias et al., 2018 ).
For the purpose of this literature review, both pure online and blended learning are considered to be online learning because much of the evidence in the literature compares these two types against the traditional F2F learning. The debate in the literature surrounding online learning versus F2F teaching continues to be a contentious one. A review of the literature reveals mixed findings when comparing the efficacy of online learning on student performance in relation to the traditional F2F medium of instruction (Lundberg et al., 2008 ; Nguyen, 2015 ). A number of studies conducted Before the 2000s find what is known today in the empirical literature as the “No Significant Difference” phenomenon (Russell & International Distance Education Certificate Center (IDECC), 1999 ). The seminal work from Russell and IDECC ( 1999 ) involved over 350 comparative studies on online/distance learning versus F2F learning, dating back to 1928. The author finds no significant difference overall between online and traditional F2F classroom education outcomes. Subsequent studies that followed find similar “no significant difference” outcomes (Arbaugh, 2000 ; Fallah & Ubell, 2000 ; Freeman & Capper, 1999 ; Johnson et al., 2000 ; Neuhauser, 2002 ). While Bernard et al. ( 2004 ) also find that overall there is no significant difference in achievement between online education and F2F education, the study does find significant heterogeneity in student performance for different activities. The findings show that students in F2F classes outperform the students participating in synchronous online classes (i.e. classes that require online students to participate in live sessions at specific times). However, asynchronous online classes (i.e. students access class materials at their own time online) outperform F2F classes.
More recent studies find significant results for online learning outcomes in relation to F2F outcomes. On the one hand, Shachar and Yoram ( 2003 ) and Shachar and Neumann ( 2010 ) conduct a meta‐analysis of studies from 1990 to 2009 and find that in 70% of the cases, students taking courses by online education outperformed students in traditionally instructed courses (i.e. F2F lectures). In addition, Navarro and Shoemaker ( 2000 ) observe that learning outcomes for online learners are as effective as or better than outcomes for F2F learners, regardless of background characteristics. In a study on computer science students, Dutton et al. ( 2002 ) find online students perform significantly better compared to the students who take the same course on campus. A meta‐analysis conducted by the US Department of Education finds that students who took all or part of their course online performed better, on average, than those taking the same course through traditional F2F instructions. The report also finds that the effect sizes are larger for studies in which the online learning was collaborative or instructor‐driven than in those studies where online learners worked independently (Means et al., 2010 ).
On the other hand, evidence by Brown and Liedholm ( 2002 ) based on test scores from macroeconomics students in the United States suggest that F2F students tend to outperform online students. These findings are supported by Coates et al. ( 2004 ) who base their study on macroeconomics students in the United States, and Xu and Jaggars ( 2014 ) who find negative effects for online students using a data set of about 500,000 courses taken by over 40,000 students in Washington. Furthermore, Almatra et al. ( 2015 ) compare overall course grades between online and F2F students for a Telecommunications course and find that F2F students significantly outperform online learning students. In an experimental study where students are randomly assigned to attend live lectures versus watching the same lectures online, Figlio et al. ( 2013 ) observe some evidence that the traditional format has a positive effect compared to online format. Interestingly, Callister and Love ( 2016 ) specifically compare the learning outcomes of online versus F2F skills‐based courses and find that F2F learners earned better outcomes than online learners even when using the same technology. This study highlights that some of the inconsistencies that we find in the results comparing online to F2F learning might be influenced by the nature of the course: theory‐based courses might be less impacted by in‐person interaction than skills‐based courses.
The fact that the reviewed studies on the effects of F2F versus online learning on student performance have been mainly focused in developed countries indicates the dearth of similar studies being conducted in developing countries. This gap in the literature may also highlight a salient point: online learning is still relatively underexplored in developing countries. The lockdown in South Africa therefore provides us with an opportunity to contribute to the existing literature from a developing country context.
2. CONTEXT OF STUDY
South Africa went into national lockdown in March 2020 due to the Covid‐19 pandemic. Like most universities in the country, the first semester for undergraduate courses at the University of Pretoria had already been running since the start of the academic year in February. Before the pandemic, a number of F2F lectures and assessments had already been conducted in most courses. The nationwide lockdown forced the university, which was mainly in‐person teaching, to move to full online learning for the remainder of the semester. This forced shift from F2F teaching to online learning allows us to investigate the changes in students' performance.
Before lockdown, classes were conducted on campus. During lockdown, these live classes were moved to an online platform, Blackboard Collaborate, which could be accessed by all registered students on the university intranet (“ClickUP”). However, these live online lectures involve substantial internet data costs for students. To ensure access to course content for those students who were unable to attend the live online lectures due to poor internet connections or internet data costs, several options for accessing course content were made available. These options included prerecorded narrated slides (which required less usage of internet data), recordings of the live online lectures, PowerPoint slides with explanatory notes and standard PDF lecture slides.
At the same time, the university managed to procure and loan out laptops to a number of disadvantaged students, and negotiated with major mobile internet data providers in the country for students to have free access to study material through the university's “connect” website (also referred to as the zero‐rated website). However, this free access excluded some video content and live online lectures (see Table 1 ). The university also provided between 10 and 20 gigabytes of mobile internet data per month, depending on the network provider, sent to students' mobile phones to assist with internet data costs.
Sites available on zero‐rated website
Note : The table summarizes the sites that were available on the zero‐rated website and those that incurred data costs.
High data costs continue to be a contentious issue in Africa where average incomes are low. Gilbert ( 2019 ) reports that South Africa ranked 16th of the 45 countries researched in terms of the most expensive internet data in Africa, at US$6.81 per gigabyte, in comparison to other Southern African countries such as Mozambique (US$1.97), Zambia (US$2.70), and Lesotho (US$4.09). Internet data prices have also been called into question in South Africa after the Competition Commission published a report from its Data Services Market Inquiry calling the country's internet data pricing “excessive” (Gilbert, 2019 ).
3. EMPIRICAL APPROACH
We use a sample of 395 s‐year students taking a macroeconomics module in the Economics department to compare the effects of F2F and online learning on students' performance using a range of assessments. The module was an introduction to the application of theoretical economic concepts. The content was both theory‐based (developing economic growth models using concepts and equations) and skill‐based (application involving the collection of data from online data sources and analyzing the data using statistical software). Both individual and group assignments formed part of the assessments. Before the end of the semester, during lockdown in June 2020, we asked the students to complete a survey with questions related to the transition from F2F to online learning and the difficulties that they may have faced. For example, we asked the students: (i) how easy or difficult they found the transition from F2F to online lectures; (ii) what internet options were available to them and which they used the most to access the online prescribed work; (iii) what format of content they accessed and which they preferred the most (i.e. self‐study material in the form of PDF and PowerPoint slides with notes vs. assisted study with narrated slides and lecture recordings); (iv) what difficulties they faced accessing the live online lectures, to name a few. Figure 1 summarizes the key survey questions that we asked the students regarding their transition from F2F to online learning.
Summary of survey data
Before the lockdown, the students had already attended several F2F classes and completed three assessments. We are therefore able to create a dependent variable that is comprised of the average grades of three assignments taken before lockdown and the average grades of three assignments taken after the start of the lockdown for each student. Specifically, we use the difference between the post‐ and pre‐lockdown average grades as the dependent variable. However, the number of student observations dropped to 275 due to some students missing one or more of the assessments. The lecturer, content and format of the assessments remain similar across the module. We estimate the following equation using ordinary least squares (OLS) with robust standard errors:
where Y i is the student's performance measured by the difference between the post and pre‐lockdown average grades. B represents the vector of determinants that measure the difficulty faced by students to transition from F2F to online learning. This vector includes access to the internet, study material preferred, quality of the online live lecture sessions and pre‐lockdown class attendance. X is the vector of student demographic controls such as race, gender and an indicator if the student's perceived family income is below average. The ε i is unobserved student characteristics.
4.1. descriptive statistics.
Table 2 gives an overview of the sample of students. We find that among the black students, a higher proportion of students reported finding the transition to online learning more difficult. On the other hand, more white students reported finding the transition moderately easy, as did the other races. According to Coetzee ( 2014 ), the quality of schools can vary significantly between higher income and lower‐income areas, with black South Africans far more likely to live in lower‐income areas with lower quality schools than white South Africans. As such, these differences in quality of education from secondary schooling can persist at tertiary level. Furthermore, persistent income inequality between races in South Africa likely means that many poorer black students might not be able to afford wifi connections or large internet data bundles which can make the transition difficult for black students compared to their white counterparts.
Notes : The transition difficulty variable was ordered 1: Very Easy; 2: Moderately Easy; 3: Difficult; and 4: Impossible. Since we have few responses to the extremes, we combined Very Easy and Moderately as well as Difficult and Impossible to make the table easier to read. The table with a full breakdown is available upon request.
A higher proportion of students reported that wifi access made the transition to online learning moderately easy. However, relatively more students reported that mobile internet data and accessing the zero‐rated website made the transition difficult. Surprisingly, not many students made use of the zero‐rated website which was freely available. Figure 2 shows that students who reported difficulty transitioning to online learning did not perform as well in online learning versus F2F when compared to those that found it less difficult to transition.
Transition from F2F to online learning.
Notes : This graph shows the students' responses to the question “How easy did you find the transition from face‐to‐face lectures to online lectures?” in relation to the outcome variable for performance
In Figure 3 , the kernel density shows that students who had access to wifi performed better than those who used mobile internet data or the zero‐rated data.
Access to online learning.
Notes : This graph shows the students' responses to the question “What do you currently use the most to access most of your prescribed work?” in relation to the outcome variable for performance
The regression results are reported in Table 3 . We find that the change in students' performance from F2F to online is negatively associated with the difficulty they faced in transitioning from F2F to online learning. According to student survey responses, factors contributing to difficulty in transitioning included poor internet access, high internet data costs and lack of equipment such as laptops or tablets to access the study materials on the university website. Students who had access to wifi (i.e. fixed wireless broadband, Asymmetric Digital Subscriber Line (ADSL) or optic fiber) performed significantly better, with on average 4.5 points higher grade, in relation to students that had to use mobile internet data (i.e. personal mobile internet data, wifi at home using mobile internet data, or hotspot using mobile internet data) or the zero‐rated website to access the study materials. The insignificant results for the zero‐rated website are surprising given that the website was freely available and did not incur any internet data costs. However, most students in this sample complained that the internet connection on the zero‐rated website was slow, especially in uploading assignments. They also complained about being disconnected when they were in the middle of an assessment. This may have discouraged some students from making use of the zero‐rated website.
Results: Predictors for student performance using the difference on average assessment grades between pre‐ and post‐lockdown
Coefficients reported. Robust standard errors in parentheses.
∗∗∗ p < .01.
Students who expressed a preference for self‐study approaches (i.e. reading PDF slides or PowerPoint slides with explanatory notes) did not perform as well, on average, as students who preferred assisted study (i.e. listening to recorded narrated slides or lecture recordings). This result is in line with Means et al. ( 2010 ), where student performance was better for online learning that was collaborative or instructor‐driven than in cases where online learners worked independently. Interestingly, we also observe that the performance of students who often attended in‐person classes before the lockdown decreased. Perhaps these students found the F2F lectures particularly helpful in mastering the course material. From the survey responses, we find that a significant proportion of the students (about 70%) preferred F2F to online lectures. This preference for F2F lectures may also be linked to the factors contributing to the difficulty some students faced in transitioning to online learning.
We find that the performance of low‐income students decreased post‐lockdown, which highlights another potential challenge to transitioning to online learning. The picture and sound quality of the live online lectures also contributed to lower performance. Although this result is not statistically significant, it is worth noting as the implications are linked to the quality of infrastructure currently available for students to access online learning. We find no significant effects of race on changes in students' performance, though males appeared to struggle more with the shift to online teaching than females.
For the robustness check in Table 4 , we consider the average grades of the three assignments taken after the start of the lockdown as a dependent variable (i.e. the post‐lockdown average grades for each student). We then include the pre‐lockdown average grades as an explanatory variable. The findings and overall conclusions in Table 4 are consistent with the previous results.
Robustness check: Predictors for student performance using the average assessment grades for post‐lockdown
As a further robustness check in Table 5 , we create a panel for each student across the six assignment grades so we can control for individual heterogeneity. We create a post‐lockdown binary variable that takes the value of 1 for the lockdown period and 0 otherwise. We interact the post‐lockdown dummy variable with a measure for transition difficulty and internet access. The internet access variable is an indicator variable for mobile internet data, wifi, or zero‐rated access to class materials. The variable wifi is a binary variable taking the value of 1 if the student has access to wifi and 0 otherwise. The zero‐rated variable is a binary variable taking the value of 1 if the student used the university's free portal access and 0 otherwise. We also include assignment and student fixed effects. The results in Table 5 remain consistent with our previous findings that students who had wifi access performed significantly better than their peers.
Notes : Coefficients reported. Robust standard errors in parentheses. The dependent variable is the assessment grades for each student on each assignment. The number of observations include the pre‐post number of assessments multiplied by the number of students.
The Covid‐19 pandemic left many education institutions with no option but to transition to online learning. The University of Pretoria was no exception. We examine the effect of transitioning to online learning on the academic performance of second‐year economic students. We use assessment results from F2F lectures before lockdown, and online lectures post lockdown for the same group of students, together with responses from survey questions. We find that the main contributor to lower academic performance in the online setting was poor internet access, which made transitioning to online learning more difficult. In addition, opting to self‐study (read notes instead of joining online classes and/or watching recordings) did not help the students in their performance.
The implications of the results highlight the need for improved quality of internet infrastructure with affordable internet data pricing. Despite the university's best efforts not to leave any student behind with the zero‐rated website and free monthly internet data, the inequality dynamics in the country are such that invariably some students were negatively affected by this transition, not because the student was struggling academically, but because of inaccessibility of internet (wifi). While the zero‐rated website is a good collaborative initiative between universities and network providers, the infrastructure is not sufficient to accommodate mass students accessing it simultaneously.
This study's findings may highlight some shortcomings in the academic sector that need to be addressed by both the public and private sectors. There is potential for an increase in the digital divide gap resulting from the inequitable distribution of digital infrastructure. This may lead to reinforcement of current inequalities in accessing higher education in the long term. To prepare the country for online learning, some considerations might need to be made to make internet data tariffs more affordable and internet accessible to all. We hope that this study's findings will provide a platform (or will at least start the conversation for taking remedial action) for policy engagements in this regard.
We are aware of some limitations presented by our study. The sample we have at hand makes it difficult to extrapolate our findings to either all students at the University of Pretoria or other higher education students in South Africa. Despite this limitation, our findings highlight the negative effect of the digital divide on students' educational outcomes in the country. The transition to online learning and the high internet data costs in South Africa can also have adverse learning outcomes for low‐income students. With higher education institutions, such as the University of Pretoria, integrating online teaching to overcome the effect of the Covid‐19 pandemic, access to stable internet is vital for students' academic success.
It is also important to note that the data we have at hand does not allow us to isolate wifi's causal effect on students' performance post‐lockdown due to two main reasons. First, wifi access is not randomly assigned; for instance, there is a high chance that students with better‐off family backgrounds might have better access to wifi and other supplementary infrastructure than their poor counterparts. Second, due to the university's data access policy and consent, we could not merge the data at hand with the student's previous year's performance. Therefore, future research might involve examining the importance of these elements to document the causal impact of access to wifi on students' educational outcomes in the country.
The authors acknowledge the helpful comments received from the editor, the anonymous reviewers, and Elizabeth Asiedu.
Chisadza, C. , Clance, M. , Mthembu, T. , Nicholls, N. , & Yitbarek, E. (2021). Online and face‐to‐face learning: Evidence from students’ performance during the Covid‐19 pandemic . Afr Dev Rev , 33 , S114–S125. 10.1111/afdr.12520 [ CrossRef ] [ Google Scholar ]
1 https://mybroadband.co.za/news/cellular/309693-mobile-data-prices-south-africa-vs-the-world.html .
2 The 4IR is currently characterized by increased use of new technologies, such as advanced wireless technologies, artificial intelligence, cloud computing, robotics, among others. This era has also facilitated the use of different online learning platforms ( https://www.brookings.edu/research/the-fourth-industrialrevolution-and-digitization-will-transform-africa-into-a-global-powerhouse/ ).
3 Note that we control for income, but it is plausible to assume other unobservable factors such as parental preference and parenting style might also affect access to the internet of students.
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A Survey on the Effectiveness of Online Teaching–Learning Methods for University and College Students
- Article of professional interests
- Published: 05 April 2021
- Volume 102 , pages 1325–1334, ( 2021 )
- Preethi Sheba Hepsiba Darius ORCID: orcid.org/0000-0003-0882-6213 1 ,
- Edison Gundabattini ORCID: orcid.org/0000-0003-4217-2321 2 &
- Darius Gnanaraj Solomon ORCID: orcid.org/0000-0001-5321-5775 2
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Online teaching–learning methods have been followed by world-class universities for more than a decade to cater to the needs of students who stay far away from universities/colleges. But during the COVID-19 pandemic period, online teaching–learning helped almost all universities, colleges, and affiliated students. An attempt is made to find the effectiveness of online teaching–learning methods for university and college students by conducting an online survey. A questionnaire has been specially designed and deployed among university and college students. About 450 students from various universities, engineering colleges, medical colleges in South India have taken part in the survey and submitted responses. It was found that the following methods promote effective online learning: animations, digital collaborations with peers, video lectures delivered by faculty handling the subject, online quiz having multiple-choice questions, availability of student version software, a conducive environment at home, interactions by the faculty during lectures and online materials provided by the faculty. Moreover, online classes are more effective because they provide PPTs in front of every student, lectures are heard by all students at the sound level of their choice, and walking/travel to reach classes is eliminated.
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Critical thinking and creativity of students increase with innovative educational methods according to the world declaration on higher education in the twenty-first century [ 1 ]. Innovative educational strategies and educational innovations are required to make the students learn. There are three vertices in the teaching–learning process viz., teaching, communication technology through digital tools, and innovative practices in teaching. In the first vertex, the teacher is a facilitator and provides resources and tools to students and helps them to develop new knowledge and skills. Project-based learning helps teachers and students to promote collaborative learning by discussing specific topics. Cognitive independence is developed among students. To promote global learning, teachers are required to innovate permanently. It is possible when university professors and researchers are given space to new educational forms in different areas of specializations. Virtual classrooms, unlike traditional classrooms, give unlimited scope for introducing teaching innovation strategies. The second vertex refers to the use of Information and Communication Technology (ICT) tools for promoting innovative education. Learning management systems (LMS) help in teaching, learning, educational administration, testing, and evaluation. The use of ICT tools promotes technological innovations and advances in learning and knowledge management. The third vertex deals with innovations in teaching/learning to solve problems faced by teachers and students. Creative use of new elements related to curriculum, production of something new, and transformations emerge in classrooms resulting in educational innovations. Evaluations are necessary to improve the innovations so that successful methods can be implemented in all teaching and learning community in an institution [ 2 ]. The pandemic has forced digital learning and job portal Naukri.com reports a fourfold growth for teaching professionals in the e-learning medium [ 3 ]. The initiatives are taken by the government also focus on online mode as an option in a post-covid world [ 4 ]. A notable learning experience design consultant pointed out that, educators are entrusted to lead the way as the world changes and are actively involved in the transformation [ 5 ]. Weiss notes that an educator needs to make the lectures more interesting [ 6 ].
This paper presents the online teaching–learning tools, methods, and a survey on the innovative practices in teaching and learning. Advantages and obstacles in online teaching, various components on the effective use of online tools, team-based collaborative learning, simulation, and animation-based learning are discussed in detail. The outcome of a survey on the effectiveness of online teaching and learning is included. The following sections present the online teaching–learning tools, the details of the questionnaire used for the survey, and the outcome of the survey.
Online Teaching and Learning Tools
The four essential parts of online teaching [ 7 ] are virtual classrooms, individual activities, assessments in real-time, and collaborative group work. Online teaching tools are used to facilitate faculty-student interaction as well as student–student collaborations [ 8 ]. The ease of use, the satisfaction level, the usefulness, and the confidence level of the instructor is crucial [ 9 ] in motivating the instructor to use online teaching tools. Higher education institutes recognize the need to accommodate wide diverse learners and Hilliard [ 10 ] points out that technical support and awareness to both faculty and student is essential in the age of blended learning. Data analytics tool coupled with the LMS is essential to enhance [ 11 ] the quality of teaching and improve the course design. The effective usage of online tools is depicted in Fig. 1 comprising of an instructor to student delivery, collaboration among students, training for the tools, and data analytics for constant improvement of course and assessment methods.
The various components of effective usage of online tools
Online Teaching Tools
A plethora of online teaching tools are available and this poses a challenge for decision-makers to choose the tools that best suits the needs of the course. The need for the tools, the cost, usability, and features determine which tools are adopted by various learners and institutions. Many universities have offered online classes for students. These are taken up by students opting for part-time courses. This offers them flexibility in timing and eliminates the need for travel to campus. The pandemic situation in 2019 has forced many if not all institutions to completely shift classes online. LMS tools are packaged as Software as a Service (SaaS) and the pricing generally falls into 4 categories: (i) per learner, per month (ii) per learner, per use (iii) per course (iv) licensing fee for on-premise installation [ 12 ].
Online Learning Tools
Online teaching/learning as part of the ongoing semester is typically part of a classroom management tool. GSuite for education [ 13 ] and Microsoft Teams [ 14 ] are both widely adopted by schools and colleges during the COVID-19 pandemic to effectively shift regular classes online. Other popular learning management systems that have been adopted as part of blended learning are Edmodo [ 15 ], Blackboard [ 16 ], and MoodleCloud [ 17 ]. Davis et al. [ 18 ] point out advantages and obstacles for both students and instructors about online teaching shown in Table 1 .
The effectiveness of course delivery depends on using the appropriate tools in the course design. This involves engaging the learners and modifying the course design to cater to various learning styles.
A Survey on Innovative Practices in Teaching and Learning
The questionnaire aims to identify the effectiveness of various online tools and technologies, the preferred learning methods of students, and other factors that might influence the teaching–learning process. The parameters were based on different types of learners, advantages, and obstacles to online learning [ 10 , 18 ]. Questions 1–4 are used to comprehend the learning style of the student. Questions 5–7 are posed to find out the effectiveness of the medium used for teaching and evaluation. Questions 8–12 are framed to identify the various barriers to online learning faced by students.
This methodology is adopted as most of the students are attending online courses from home and polls of this kind will go well with the students from various universities. Students participated in the survey and answered most of the questionnaire enthusiastically. The only challenge was a suitable environment and free time for them to answer the questionnaire, as they are already loaded with lots of online work. Students from various universities pursuing professional courses like engineering and medicine took part in this survey. They are from various branches of sciences and technologies. Students are from private universities, colleges, and government institutions. Figure 2 shows the institution-wise respondents. Microsoft Teams and Google meet platforms were used for this survey among university, medical college, and engineering college students. About 450 students responded to this survey. 52% of the respondents are from VIT University Vellore, Tamil Nadu, 23% of the respondents are from CMR Institute of Technology (CMRIT), Bangalore, 15% of the respondents are from medical colleges and 10% are from other engineering colleges. During this pandemic period, VIT students are staying with parents who are living in different states of India like Andhra, Telangana, Kerala, Karnataka, MP, Haryana, Punjab, Maharashtra, Andaman, and so on. Only a few students are living in Tamil Nadu. Some of the students are staying with parents in other countries like Dubai, Oman, South Africa, and so on. Some of the students of CMRIT Bangalore are living in Bangalore and others in towns and villages of Karnataka state. Students of medical colleges are living in different parts of Tamil Nadu and students of engineering colleges are living in different parts of Andhra Pradesh. Hence, the survey is done in a wider geographical region.
Figure 3 shows the branch-wise respondents. It is shown that 158 students belong to mechanical/civil engineering. 108 respondents belong to computer science and engineering, 68 students belong to medicine, 58 students belong to electrical & electronics engineering, and electronics & communication engineering. 58 students belong to other disciplines.
Students were assured of their confidentiality and were promised that their names would not appear in the document. A list of the questions asked as part of the survey is given below.
Sample group: B Tech students from different branches of sciences across various engineering institutions and MBBS medical students.
Which of the methods engage you personally to learn digitally ?
Small group (No. 5 students) work
Large group (No. 10 students and more) work
Which of the digital collaborations enables you to work on a specific task at ease
Two by two (2 member team)
Small group workgroup (No. 5 students) work
Which of the digital approaches motivate you to learn
Whiteboard and pen
Digital pen and slate
My experience with online learning from home digitally
I am learning at my own pace comfortably
My situational challenges are not suitable
I can learn better with uninterrupted network connectivity
I am distracted with various activities at home, viz. TV, chatting, etc.
Which type of recorded video lecture is more effective for learning ?
delivered by my faculty
delivered by NPTEL
delivered by reputed Overseas Universities
delivered by unknown experts
Which type of quiz is more effective for testing the understanding?
Traditional—pen and paper—MCQ
Traditional—pen and paper—short answers
Online quiz—short answers
Student version software downloaded from the internet is useful for learning
Unable to decide
Online teaching – learning takes place effectively because:
Every student can hear the lecture clearly
PPTs are available right in front of every student
Students can ask doubts without much reservation
Students need not walk long distances before reaching the class
Which of the following statements is true of online learning off-campus ?
No one disturbs me during my online learning.
My friend/family member/roommate/neighbor occasionally disturb me
My friend/family member/roommate/neighbor constantly disturb me
At home/place of residence, how many responsibilities do you have?
I don’t have many responsibilities.
I have a moderate amount of responsibilities, but I have sufficient time for online learning.
I have many responsibilities; I don’t have any time left for online learning.
What is your most preferred method for clearing doubts in online learning?
Ask the professor during/after an online lecture
Post the query in a discussion forum of your class and get help from your peers
Go through online material providing an additional explanation.
Which of the following devices do you use for your online learning?
A laptop/desktop computer
Outcome of the survey
Students would prefer to work in a group of 5 students to engage personally in digital learning as seen from Fig. 4 .
Personal engagement in digital learning
Digital collaboration to enable students to work at ease on a specific task is to allow them to work in small groups of 5 students as seen in Fig. 5 .
Digital collaboration to enable students to work at ease
Animations are found to be the best digital approach motivating many students to learn as seen in Fig. 6 .
Digital approaches that motivate students to learn
The online learning experience of students is shown in Fig. 7 . The majority of students have said that they can learn at their own pace comfortably through online learning.
The online learning experience of students
The effectiveness of the recorded video lecture is shown in Fig. 8 . The majority of students agree that the video lectures delivered by his/her faculty teaching the subject help students to learn effectively.
More effective recorded video lecture
Online quiz having multiple-choice questions (MCQ) is preferred by most of the students for testing their understanding of the subject as seen in Fig. 9 .
More effective quiz for testing the understanding
The usefulness of the student version of the software downloaded from the internet is shown in Fig. 10 . 45.7% of the students agree that it is useful for learning whereas 45.2% of them are unable to decide. The rest of the students feel that the student version of the software is not useful.
The usefulness of the student version of the software
The reasons for the effectiveness of online teaching–learning are shown in Fig. 11 . The majority of the students, feel that the PPTs are available right in front of every student so that following the lecture makes the learning effective. In universities where a fully flexible credit system (FFCS) is followed, students need to walk long distances for reaching their classrooms. Day Scholars in universities as well as engineering colleges are required to travel a considerable distance before reaching the first-hour class. According to many students, online learning is more effective since walking/traveling is completed eliminated. If the voice of the faculty member is feeble, students sitting in the last few rows of the class would not hear the lecture completely. Some students feel that online learning is more effective since the lecture is reaching every student irrespective of the number of students in a virtual classroom.
Reasons for the effectiveness of online teaching–learning
50.3% of students agree that they do not have any disturbance during online learning and it is more effective. Many of them feel that occasionally their friends or relatives disturb students during their online learning as shown in Fig. 12 .
Disturbances during online learning
Figure 13 shows the environment at home for online learning. 76.9% of the respondents stated that they have a moderate amount of responsibilities at home but they have sufficient time for online learning. 16.1% of them have said that they do not have many responsibilities whereas 7% of them claimed that they have many responsibilities at home and they do not have any time left for online learning.
The environment at home for online learning
Figure 14 shows the methods adopted for clearing doubts in online learning. 43.2% of the respondents ask the Professor and get their doubts clarified during online lectures. 25.5% of them post queries in the discussion forum and help from peers. 31.3% of them go through the online materials providing additional explanation and get their doubts clarified.
Methods adopted for clearing doubts in online learning
Figure 15 shows the devices used by students for online learning. Most of the students use laptop/desktop computers, many of them use smartphones and very few students use tablets.
Devices used for online learning
The association between responses 1 and 2 is tested using the chi-square test. The results are presented in Table 2 which shows the observed cell totals, expected cell values, and chi-square statistic for each cell. It is seen that association exists between several responses between questions.
The observed cell values indicate that the highest association is found between responses 1b and 2b since both these responses are related to a small working group having 5 members. The lowest association is found between the responses of 1c and 2a having the lowest observed cell value and expected cell value. The reason for this is response 1c shows the work done by a 10 member team and the response 2a shows a two-member team. The chi-square statistic is 65.6025. The p value is < 0.00001. The result is significant at p < 0.05.
The outcome of a survey on the effectiveness of innovations in online teaching–learning methods for university and college students is presented. About 450 students belonging to VIT Vellore, CMRIT Bangalore, Medical College, Pudukkottai, and engineering colleges have responded to the survey. A questionnaire designed for taking is survey is presented. The chi-square statistic is 65.6025. The p value is < 0.00001. The result is significant at p < 0.05. Associations between several responses of questions exist. The survey undertaken provides an estimate of the effectiveness and pitfalls of online teaching during the online teaching that has been taking place during the pandemic. The study done paves the way for educators to understand the effectiveness of online teaching. It is important to redesign the course delivery in an online mode to make students engaged and the outcome of the survey supports these aforementioned observations.
The outcome of the survey is given below:
A small group of 5 students would help students to have digital collaboration and engage personally in digital learning.
Animations are found to be the best digital approach for effective learning.
Online learning helps students to learn at their own pace comfortably.
Students prefer to learn from video lectures delivered by his/her faculty handling the subject.
Online quiz having multiple-choice questions (MCQ) preferred by students.
Student version software is useful for learning.
Online classes are more effective because they provide PPTs in front of every student, lectures are heard by all students at the sound level of their choice, and walking/travel to reach classes is eliminated.
Students do not have any disturbances or distractions which make learning more effective.
But for a few students, most of the students have no or limited responsibilities at home which provides a good ambiance and a nice environment for effective online learning.
Students can get their doubts clarified during lectures, by posting queries in discussion forums and by referring to online materials provided by the faculty.
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Department of Computer Science and Engineering, CMR Institute of Technology, Bangalore, 560037, India
Preethi Sheba Hepsiba Darius
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Darius, P.S.H., Gundabattini, E. & Solomon, D.G. A Survey on the Effectiveness of Online Teaching–Learning Methods for University and College Students. J. Inst. Eng. India Ser. B 102 , 1325–1334 (2021). https://doi.org/10.1007/s40031-021-00581-x
Received : 10 August 2020
Accepted : 18 March 2021
Published : 05 April 2021
Issue Date : December 2021
DOI : https://doi.org/10.1007/s40031-021-00581-x
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Impact of Online Classes on Students Essay
- Thesis Statement
- Impacts of online education
Introduction to Online Education
Online learning is one of the new innovative study methods that have been introduced in the pedagogy field. In the last few years, there has been a great shift in the training methods. Students can now learn remotely using the internet and computers.
Online learning comes in many forms and has been developing with the introduction of new technologies. Most universities, high schools, and other institutions in the world have all instituted this form of learning, and the student population in the online class is increasing fast. There has been a lot of research on the impacts of online education as compared to ordinary classroom education.
If the goal is to draw a conclusion of online education, considerable differences between the online learning environment and classroom environment should be acknowledged. In the former, teachers and students don’t meet physically as opposed to the latter, where they interact face to face. In this essay, the challenges and impact of online classes on students, teachers, and institutions involved were examined.
Thesis Statement about Online Classes
Thus, the thesis statement about online classes will be as follows:
Online learning has a positive impact on the learners, teachers, and the institution offering these courses.
Online learning or E learning is a term used to describe various learning environments that are conducted and supported by the use of computers and the internet. There are a number of definitions and terminologies that are used to describe online learning.
These include E learning, distance learning, and computer learning, among others (Anon, 2001). Distant learning is one of the terminologies used in E learning and encompasses all learning methods that are used to train students that are geographically away from the training school. Online learning, on the other hand, is used to describe all the learning methods that are supported by the Internet (Moore et al., 2011).
Another terminology that is used is E learning which most authors have described as a learning method that is supported by the use of computers, web-enabled communication, and the use of new technological tools that enhance communication (Spector, 2008). Other terminologies that are used to describe this form of online learning are virtual learning, collaborative learning, web-based learning, and computer-supported collaborative learning (Conrad, 2006).
Impacts of Online Classes on Students
Various studies and articles document the merits, demerits, and challenges of online studies. These studies show that online study is far beneficial to the students, teachers, and the institution in general and that the current challenges can be overcome through technological advancement and increasing efficiency of the learning process.
One of the key advantages of online learning is the ability of students to study in their own comfort. For a long time, students had to leave their comfort areas and attend lectures. This change in environment causes a lack of concentration in students. In contrast, E-learning enables the students to choose the best environment for study, and this promotes their ability to understand. As a result, students enjoy the learning process as compared to conventional classroom learning.
Another benefit is time and cost savings. Online students are able to study at home, and this saves them travel and accommodation costs. This is in contrast with the classroom environment, where learners have to pay for transport and accommodation costs as well as any other costs associated with the learning process.
Online study has been found to reduce the workload on the tutors. Most of the online notes and books are availed to the students, and this reduces the teacher’s workload. Due to the availability of teaching materials online, tutors are not required to search for materials. Teachers usually prepare lessons, and this reduces the task of training students over and over again.
Accessibility to learning materials is another benefit of online learning. Students participating in online study have unlimited access to learning materials, which gives them the ability to study effectively and efficiently. On the other hand, students in the classroom environment have to take notes as the lecture progress, and these notes may not be accurate as compared to the materials uploaded on the websites.
Unlimited resources are another advantage of online study. Traditionally, learning institutions were limited in the number of students that could study in the classroom environment. The limitations of facilities such as lecture theaters and teachers limited student enrollment in schools (Burgess & Russell, 2003).
However, with the advent of online studies, physical limitations imposed by classrooms, tutors, and other resources have been eliminated. A vast number of students can now study in the same institution and be able to access the learning materials online. The use of online media for training enables a vast number of students to access materials online, and this promotes the learning process.
Promoting online study has been found by most researchers to open the students to vast resources that are found on the internet. Most of the students in the classroom environment rely on the tutors’ notes and explanations for them to understand a given concept.
However, students using the web to study most of the time are likely to be exposed to the vast online educational resources that are available. This results in the students gaining a better understanding of the concept as opposed to those in the classroom environment (Berge & Giles, 2008).
An online study environment allows tutors to update their notes and other materials much faster as compared to the classroom environment. This ensures that the students receive up-to-date information on a given study area.
One of the main benefits of E-learning to institutions is the ability to provide training to a large number of students located in any corner of the world. These students are charged training fees, and this increases the money available to the institution. This extra income can be used to develop new educational facilities, and these will promote education further (Gilli et al., 2002).
Despite the many advantages that online study has in transforming the learning process, there are some challenges imposed by the method. One of the challenges is the technological limitations of the current computers, which affect the quality of the learning materials and the learning process in general.
Low download speed and slow internet connectivity affect the availability of learning materials. This problem is, however, been reduced through the application of new software and hardware elements that have high access speeds. This makes it easier to download learning materials and applications. As computing power increases, better and faster computers are being unveiled, and these will enable better access to online study facilities.
Another disadvantage of online learning as compared to the classroom environment is the lack of feedback from the students. In the classroom environment, students listen to the lecture and ask the tutors questions and clarifications any issues they didn’t understand. In the online environment, the response by the teacher may not be immediate, and students who don’t understand a given concept may find it hard to liaise with the teachers.
The problem is, however, been circumvented by the use of simple explanation methods, slideshows, and encouraging discussion forums between the teachers and students. In the discussion forums, students who don’t understand a concept can leave a comment or question, which will be answered by the tutor later.
Like any other form of learning, online studies have a number of benefits and challenges. It is, therefore, not logical to discredit online learning due to the negative impacts of this training method. Furthermore, the benefits of e-learning far outweigh the challenges.
Conclusion about Online Education
In culmination, a comparative study between classroom study and online study was carried out. The study was done by examining the findings recorded in books and journals on the applicability of online learning to students. The study revealed that online learning has many benefits as compared to conventional learning in the classroom environment.
Though online learning has several challenges, such as a lack of feedback from students and a lack of the proper technology to effectively conduct online learning, these limitations can be overcome by upgrading the E-Leaning systems and the use of online discussion forums and new web-based software.
In conclusion, online learning is beneficial to the students, tutors, and the institution offering these courses. I would therefore recommend that online learning be implemented in all learning institutions, and research on how to improve this learning process should be carried out.
Anon, C. (2001). E-learning is taking off in Europe. Industrial and Commercial Training , 33 (7), 280-282.
Berge, Z., & Giles, L. (2008). Implementing and sustaining e-learning in the workplace. International Journal of Web-Based Learning and Teaching Technologies , 3(3), 44-53.
Burgess, J. & Russell, J. (2003).The effectiveness of distance learning initiatives in organizations. Journal of Vocational Behaviour , 63 (2),289-303.
Conrad, D. (2006). E-Learning and social change, Perspectives on higher education in the digital age . New York: Nova Science Publishers.
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An Overview Of Stride In The EdTech Landscape
- Stride, Inc. has achieved consistent double-digit growth in online education the last 15 years, positioning itself as a trailblazer in the industry.
- The company's strategic acquisitions and innovative school-as-a-service model have contributed to its resilience and adaptability in the dynamic online education sector.
- Stride's impact on three million students and its anticipation of doubling in the future demonstrate its financial robustness and responsiveness to market demands.
SrdjanPav/E+ via Getty Images
Stride, Inc. ( NYSE: LRN ) has positioned itself as a trailblazer in online education, achieving consistent double-digit growth since 2006. With a focus on diverse learners, it offers a comprehensive suite for K-12 students and adults, leveraging an innovative school-as-a-service model.
Venturing into adult learning in 2020 through strategic acquisitions showcases Stride's visionary approach. Recent market dynamics, such as a 30% stock price surge, affirm its resilience and adaptability in the dynamic online education sector.
In the broader EdTech landscape, Stride's impact on three million students since 2000 sets it apart. Financially robust and responsive to market demands, Stride anticipates a potential doubling in the years ahead with increasing online education adoption.
With a commitment to catering to diverse learners, Stride offers a comprehensive suite of products targeting both K-12 students and adult learners.
At the core of Stride's revenue-generating prowess lies its innovative school-as-a-service model. Collaborating with a spectrum of educational institutions, from public schools to private schools and school districts, Stride provides an all-encompassing package comprising curriculum, resources, administrative services, and a robust software infrastructure. The expansion in the previous year saw Stride extending its school-as-a-service offerings to 87 schools in the General Education segment and 52 schools in the Career Learning segment.
In a strategic maneuver in 2020, Stride ventured into the adult learning market through strategic acquisitions of industry leaders such as Galvanize, Tech Elevator, and MedCerts. This strategic evolution, coupled with the rebranding from K12 to Stride, signifies the company's foresighted vision for long-term growth and diversification. Beyond traditional educational institutions, Stride has ventured into partnerships showcasing a commitment to pushing the boundaries of conventional education.
Recent market dynamics have propelled Stride's stock price with a notable 30% surge following the surpassing of analyst earnings expectations. This upward trajectory suggests untapped potential for further growth, attesting to the company's resilience and adaptability. With an inventive business model, strategic investments, and an unwavering dedication to the future of education, Stride is well-positioned to sustain its success in the dynamic online education sector.
Zooming out to the broader EdTech landscape, Stride stands out for its unique fusion of defensive and growth-oriented features. Operational since 2000, the company has made a profound impact on over three million students. However, Stride recognizes that its reach is just the tip of the iceberg, with recent U.S. survey results indicating a notable shift in parental consideration toward changing their child's school, and a substantial percentage exploring online alternatives. According to NHERI:
The homeschool population had been growing at an estimated 2% to 8% per annum over the past several years, but it grew drastically from 2019-2020 to 2020-202.
Strategic acquisitions , (Medcerts, Tech Elevator and Galvanize) have positioned Stride to tap into the adult learning sector, aligning with the demands of a robust labor market. The U.S. Bureau of Labor's projection of higher growth rates for expertise requiring non-degree education aligns seamlessly with Stride's specialized offerings, underscoring its adaptability to evolving market demands.
Financially, Stride's trajectory to profitability in 2006 has been marked by robust growth, boasting an impressive growth in revenues and profits from 2009 to 2023. Notably, even amidst the tumultuous times of the COVID-19 pandemic, Stride's growth momentum accelerated, and the company continues to thrive post-lockdowns in the U.S.
Despite consistent profitability, Stride's strategic decision to reinvest in growth rather than distributing dividends has yielded positive outcomes. This approach facilitated financing for three significant acquisitions totaling $260 million in cash.
In terms of market outlook, Stride's recent quarterly earnings surpassed expectations, triggering a 30% surge in its stock price to $59.
It's noteworthy that Stride appears considerably undervalued when compared to its direct competitors.
Analysts expect a target price for Stride of $64 which has a significant upside of 12%, but Stride can potentially double in the next several years with the adoption of online education becoming more mainstream .
The threat of cyberattacks or malware looms large over Stride as a result of its prevalent online operations. Remarkably, the company demonstrated adept handling of such incidents in 2020, highlighting its ability to navigate cybersecurity challenges with resilience. Operating within a meticulously regulated industry, Stride must adhere to a range of regulations, including ESSA, IDEA, FERPA, among others, posing potential obstacles. Moreover, the anticipation of intensified competition in the future raises concerns about potential impacts on revenues, margins, and overall growth for the company.
In summary, Stride not only stands as a powerful player in the ever-evolving EdTech realm but also serves as a catalytic force, actively shaping the trajectory of education in the future. Through its unwavering commitment to consistent financial growth, a flexible and responsive business model, and visionary leadership, Stride positions itself on the cusp of enduring success and substantial influence within the dynamic educational landscape. As it continues to navigate the challenges and opportunities of the educational sphere, Stride is well-positioned to be a key driver of positive change, setting new standards and contributing significantly to the transformative journey of education on a global scale.
This article was written by
Analyst’s Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.
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Looking For Online Test Scoring Jobs? Here are 5 Legit Options.
Posted: October 17, 2023 | Last updated: October 22, 2023
Are you looking for a non-phone job? Would you like something that challenges your mind and reasoning abilities more? How would scoring student essays sound to you? Well, then this post may be of interest to you. Five online test scoring jobs will be briefly reviewed below.
Keep in mind that if none of the options below interest you, FlexJobs (a site we've used and trust at Real Ways to Earn) lists many different companies in the education/teaching field that hire for work at home.
Online Test Scoring Jobs
1 – scoring student essays for writescore.
You may have already heard of this one as it is one of the more popular companies we've listed. While the company does have a website for potential clients to sign up, lately it is directing potential workers to a waitlist.
As an independent contractor, they pay you to score essays written by elementary, middle school, and high school students. The pay varies depending on how quickly you move through your workload.
From what I have seen on CareerBuilder and on Indeed, most scorers average from $9 to $15 an hour. While there really aren't any scheduled hours, you are given deadlines — some of which can be tight.
One major downside is that you aren't paid for your training time, and it is intense.
The only computer/education requirements are a validated email account, a 2-year degree, and high-speed Internet on your PC or laptop.
You can go here to apply and add your name to their waitlist.
2 – Scoring Test Results For ETS
ETS hires part-time employees to score test results for various online and offline educational institutions — including SAT scores.
Each scoring opportunity has its own requirements, and you must commit to a specific schedule.
Pay is twice weekly and ranges from $10 to $20 an hour, but this is dependent on how many hours you're able to get. Even though you have to commit to a schedule, you a little bit more freedom in deciding when that is.
Some scoring tasks have a minimum requirement of 4 hours. Training may last up to two weeks before you take your final certification, and you may start work immediately upon completion of training if there are available projects.
The training is reportedly difficult, and many potential scorers must retake the final tests, so you might want to really slow down during testing.
ETS gives you two tries, and you're paid for both attempts. You do NOT need to live in the USA to apply.
You can apply if you're interested.
3 – Work at Home Test Scoring Jobs With Pearson
There is also a review of Pearson's work at home scoring jobs on this blog. Pearson has been around for over 50 years, and they are recognized by many well-known educational institutions as a leader in the scoring process for tests at all levels.
With Pearson, you are a part-time employee (health benefits included), and you must work at least 20 hours a week.
Pay is via direct deposit at around $10 an hour with the chance to earn more if you are bi-lingual or willing to work past 7 p.m. You can also earn more if you're high performer.
While the computer requirements are relaxed, you must have at least a Bachelor's Degree in any field and be a US citizen. Sorry, no hiring outside of the US.
We've written more about Pearson here if you are interested in learning more. You can also go ahead and put in your application via this link .
4 – Score Essays, Tests, and Performance Assessments With Measurement, Inc.
Measurement, Inc. offers work at home test scoring jobs regularly.
If hired, you score all levels of essays, tests, and performance assessments for both government agencies and educational institutions.
The work is usually temporary and done project-by-project with the busiest times being from January to June. The company considers you a temporary staff member (employee) without benefits, and pay is estimated at around $10.70 an hour via direct deposit.
A Bachelor's Degree in any field is required to work for Measurement, Inc. They are currently accepting applicants in multiple US states.
You can learn more in our Measurement, Inc. review . And if you want to apply, go here for the job listing .
5 – ACT Writing Test Scorer
ACT is often looking for “readers” to score student writing tests.
To qualify for this job, you must have a bachelor's degree or higher, have U.S. citizenship, resident alien status, or be authorized to work in the U.S. ACT also prefers current teaching experience and experience teaching high school English to juniors and seniors.
According to Glassdoor, ACT scorers earn between $12 and $13 hourly.
If you'd like to go ahead and apply, go here .
6 – Marco Learning
This is a newer company I've just learned about. Go here to apply , or read our Marco Learning review.
Note that right now, applications are closed, but they do have a waitlist so you can be considered as a grader this fall.
So, there you have it. Another way to make money may be to become a scorer/evaluator at any one or all of these sites. Good luck!
Good luck if you apply!
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