thesis about distance learning

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Student's perspective on distance learning during COVID-19 pandemic: A case study of Western Michigan University, United States

Wassnaa al-mawee.

a Department of Computer Science, Western Michigan University, 1903 W. Michigan Ave., Kalamazoo, MI 49008-5466, USA

Keneth Morgan Kwayu

b Department of Civil and Transportation Engineering, Western Michigan University, 1903 W. Michigan Ave., Kalamazoo, MI 49008-5466, USA

Tasnim Gharaibeh

As the distance learning process has become more prevalent in the USA due to the COVID-19 pandemic, it is important to understand students’ experiences, perspectives, and preferences. Our study's purpose is to reveal students’ perspectives and preferences on distance learning due to the dramatic change that happened in the education process. Western Michigan University is used as the case study to achieve that purpose. Participants completed an online survey that investigated two measures: distance learning and instructional methods with a set of scales associated with each. Students reported negative experiences of distance learning such as lack of social interaction and positive experiences such as time and location flexibility. These findings may help WMU and higher educational institutions to improve distance learning education.

1. Introduction

The benefits and challenges of distance learning have been a subject of continuous discussion in the past. Of recent, the topic of distance learning has become more relevant and imminent due to the COVID-19 pandemic. The COVID-19 has compelled most of the higher education institutions to shift to either distance learning and/or some form of hybrid teaching model ( Smalley, 2020 ). This has disrupted the natural ecosystem of conventional learning environments where students live and study in close proximity. Challenges that have been raised in the previous studies about distance learning include variation in the quality of educational instructions, students’ unequal access to the essential technologies for distance learning, and technology readiness of students ( Ratliff, 2009 ). For example, one study found that 20% of students reported having issues in accessing essential technology for distance learning such as laptops and high-speed internet ( Gonzales, Calarco, & Lynch, 2018 ). Also, it has been found that students who were already suffering academically in face-to-face instruction are more likely to obtain lower grade points in distance learning ( Xu & Jaggars, 2014 ). Despite the challenges, this sudden and unexpected change in the learning environment offers opportunities for academic institutions to reimage innovative modes of learning that take advantage of the current technologies. Therefore, the challenges and opportunities of shifting from in-person instruction mode to remote/distance instruction mode need a thorough assessment. This study intends to explore the benefits and challenges of distance learning based on student's perspectives. The case study selected 5000 students randomly from all undergraduate and graduate students at Western Michigan University to participate in the survey and we got 420 responses.

2. Related work

Distance education, or remote learning, refers to technology-based teaching in which students during the entire course of learning are physically removed from teachers at a place. It is learning from outside the normal classroom and involves online education ( Lei & Gupta, 2010 ) A distance learning program can be completely distance learning, or a combination of distance learning and traditional classroom instruction (called hybrid) ( Tabor, 2007 ). This form of teaching helps teachers to access a considerably broader audience and facilitates greater versatility in the curriculum for students. Online education is a term under the distance education umbrella. It is education that takes place over the Internet. It is often referred to as “e-learning” in other terms. However, it is just one type of “distance learning”.

Many works and research were made to study the students’ perceptions of distance learning. In one of them, especially related to students’ perceived impacts of the COVID-19 pandemic, Aristovnik, Keržič, Ravšelj, Tomaževič, and Umek (2020) introduced a comprehensive and large-scale study of students’ perceived impacts of the COVID-19 pandemic on different aspects of their lives on a global level. Their study sample contains 30,383 students enrolled in higher education institutions, who were at least 18 years old from 62 countries, where a multi-lingual web-based comprehensive questionnaire composed of 39 predominantly closed-ended questions was used to collect the data. The questionnaire addressed socio-demographic, geographic, and other characteristics, in addition to the various features and elements of higher education student life, such as online academic work and life, emotional life, social life, personal situations, changing habits, responsibilities, as well as personal thoughts on COVID-19.

Under the online academic, as part of the distance learning, work, and life element, an ordinal logistic regression analysis was used to indicate which factors influence the students’ satisfaction with the role of the university. This logistic regression model implemented in Python programming language using libraries Pandas and Numpy which is the same language that they used to prepare, clean, and aggregate their data. The results emphasize that satisfaction with asynchronous online teaching methods such as recorded videos (p<0.001), information on exams oqr the procedure of examination in times of crisis (p<0.001), teaching staff (lecturers), and websites, social media information have a positive effect on students’ satisfaction with the role of the university during the COVID-19 pandemic. The result also showed that the students’ workload was larger or significantly larger in online teaching, in addition to some difficulty in using online teaching platforms ( Aristovnik et al., 2020 ).

On the other hand, to answer the question of how students experience distance learning, Blackmon and Major (2012) introduced an investigation using qualitative research synthesis to collect the data. They ended with 10 studies focusing on online learning. To analyze the data, they summarized the articles and extracted findings. The findings were grouped into student factors that influenced experience and instructor factors that influenced student experience. Students must combine work and families, handle time and devote themselves individually. In the absence of physical copresence, teachers can strive to develop academic relationships with students and to create a sense of community. The balance between student and teacher considerations affects the classroom and student interactions. According to their theoretical framework suggestion, the students are more abstract and understandingly observing their academic experiences. In some situations, students appeared to miss the physical markers and signals that make social interactions easier to discuss. In other situations, some students seemed to succeed in the new environment. Although the student must be responsible, the teacher also has a significant role to do to generate creative online environments that facilitate the delivery and use of new intellectual skills.

Another survey of professors, staff, and students was commissioned by Illinois Community Colleges Online in 2005 to determine the pressing concerns affecting quality, retention, and capacity building related to online learning. About one thousand people from seventeen Illinois community colleges presented data relating to these three problems over six months ( Hutti, 2007 ). Three separate methods were used in the data collection method: an electronic survey of faculty, employees, and students; a focus group including faculty, employees, and students; and interviews with select faculty, employees, and students. The findings of the review of the collected data showed that the consistency benchmarks that were most important and least important for distance learning, especially online learning, were decided by faculty, staff, and students. Using a four-point Likert Scale (Strongly Agree = 4, Agree = 3, Disagree = 2, and Strongly Disagree = 1), all three groups of respondents were asked to rate the importance of each quality benchmark. The top 5 quality benchmarks rated most important based on highest means where technical assistance in course development is available to faculty, a college-wide system (such as Blackboard or WebCT) supports and facilitates the online courses, faculty are encouraged to use technical assistance in course development, faculty give constructive feedback on student assignments and to their questions, and faculty are assisted in the transition from classroom teaching to online instruction ( Hutti, 2007 ).

To focus on a specific level college, Fedynich, Bradley and Bradley (2015) studied the graduate students’ perceptions regarding distance learning using the analysis of an online survey. Their findings indicate that the role of the teacher, the contact between students and with the teacher, and feedback and assessment were identified as being essential to the satisfaction of the students. Other difficulties found included technical support for learners connected to campus services, and the need for differing educational design and implementation to promote the ability of students to study. Students, on the other hand, were highly pleased with the consistency and organization of teaching using the right tools.

In order to find ways to improve and support distance learning, faculty members in the Distance Education Center at the University of West Georgia came together to form the “Online Refresh Faculty Learning Community” (FLC) ( Rath, Olmstead, Zhang, & Beach, 2019 ). They introduced a study conducted at a public comprehensive university located in the northeastern United States. The participants were invited to answer an online survey through Qualtrics that collected quantitative and qualitative data. Coding sheets in Excel and SPSS were used for analyzing quantitative data where qualitative data were analyzed using grounded theory procedures. In the quantitative data, the result under the factor of comfort level using technology showed 55% of participants were extremely comfortable using technology and only 2% were uncomfortable. Under the preferred course modality factor, students preferred the in-person courses followed by the online courses, and at last, the hybrid/blind courses. Four factors were addressed in the qualitative data results, set-up of the course; learner characteristics and sense of course learning; social interactions; and technology issues. Regarding how the course set up by the instructor influenced the perceptions of students about the quality and efficacy of distance learning environments, successful contact was considered as a key to an online course's progress. Next, the clear due dates and understandable instructions on assignments came as important components of the course organization. Under learner characteristics, distance learning works best for the students who demonstrate strong self-regulatory behaviors and managing their time. Also, many students in their study surveyed reported frustration with learning online applications and with the lack of reliability of the internet. On the other hand, their result showed clearly, the social aspect of face-to-face classes is very important and valuable to most students.

Students stated some advantages for distance learning such as saving time, fitting in better with schedules, enabling students to take more courses, self-paced study, time and space flexibility, distance learning course often costs less ( O'Malley & McCraw, 1999 ). The disadvantages of distance learning that were mentioned include the need for consistent access to technology, the absence of face-to-face contact ( Young & Norgard, 2006 ), the feeling of isolation, the challenge to remain focused, and the difficulty of obtaining immediate feedback ( Lei & Gupta, 2010 ; Paepe, Zhu, & Depryck, 2017 ; Venter, 2010 ; Zuhairi, Zuhairi, Wahyono, & Suratinah, 2006 ).

Many recommendations arising from the previous studies include the following suggestions; continue to offer the courses in many formats (in-person and online) to provide a choice for students, continue to offer professional development and training for instructors ( Burns, 2013 ), providing the learners with social support and sufficient motivation, instead of providing only synchronous or only asynchronous practices, using these environments together ( Allen, 2017 ; Cankaya & Yunkul, 2018 ) consider the students who have complex and special needs with special education support, try to open communication channels among administrators, educators, and students and improve mental wellness programs and provide proactive psychosocial help to students ( Allen, 2017 ).

The purpose of the present study was to share information and experiences that can positively impact distance learning in WMU, besides revealing the factors that affect the students’ experience and investigating the impact of student and college characteristics on perceptions of online learning. The study examined two key college characteristics – namely, college-level and college type to reveal the students’ preferences and experiences of distance learning at WMU. The study pursued to address the following explicit research questions:

• 1 What are the WMU students' general perceptions about distance learning?
• 2 What are the significant differences in perceptions of distance learning when comparing different college types?
• 3 How are perceptions of graduate-level students differ from the perceptions of undergraduate-level students of distance learning?
• 4 What are the students’ preferences regarding instructional methods of distance learning?

4.1. Data collection procedure

The survey was administered online through Western Michigan University's official website, Qualtrics. Qualtrics platform is a powerful platform for survey design, and it was available on the WMU official website to all WMU students, faculty, and staff. Informed consent and a link to the survey were distributed to students through the university e-mail. Students were asked to state their perspectives and preferences by choosing one choice in a Likert scale survey. An option is also provided for the subject to input additional comments. Students were able to complete the survey in approximately 10-15 minutes at their own convenience within two weeks. No identifiable private information was obtained from the participants.

4.2. Participants

The participants in this study were 420 undergraduate and graduate students enrolled in different distance learning - education courses during the 2019-2020 academic year at Western Michigan University, the U.S. Of the participants, 251 were female (59.76%), 160 were male (38.10%), and 9 (2.14%) were identified as other, with an age range of 18-55 years and above. In terms of college-level, 72 (17.14%) of participants were freshmen, 57 (13.57%) were sophomores, 74 (17.62%) were juniors, 105 (25.00%) were seniors, 107 (25.48%) were graduate students, and 5 (1.19%) were identified as other. The study considered all 11 colleges at WMU. Most of the participants, 107 (25.48%) from the College of Arts and Sciences (CAS), 22 (5.24%) from College of Aviation (CA), 51 (12.14%) from Haworth College of Business (HCB), 61 (14.52%) from College of Education and Human Development (CEHD), 81 (19.29%) from College of Engineering and Applied Sciences (CEAS), 29 (6.90%) from College of Fine Arts (CFA), 48 (11.43%) College of Health and Human Services (CHHS), 3 (0.71%) from Lee Honors College (LHC), 14 (3.33%) from Graduate College (GC), 0 (0.00%) from Thomas M. Cooley Law School (TMCLS) and Homer Stryker M.D. School of Medicine, respectively. Tables 1 and ​ and2 depict 2 depict the participants’ gender and age by college level and college type, respectively.

Participants’ gender and age by college level,

Participants’ gender and age by college type,

To assess the sample representativeness, the survey sample size was compared with the total number of students in WMU by college level and age. Out of 22,562 students at WMU, 4802 (21.28%) were graduate students and 17,760 (78.72%) were undergraduate students. The total percentage by college-level aligned well with the survey sample size, whereby out of 420 participants, 107 (25.48%) were graduate students and 313 (74.52%) were graduate students. In terms of age group, most of the WMU students were below 24 years old (75%), followed by 24-34 years (17%) and greater than 34 years (8%). The same pattern was observed in the survey sample size with students below 24 years constituting 69% followed by 24-34 years (19%) and greater than 34 years (12%).

4.3. Measures

The survey incorporated demographic questions, Likert scale questions, and open-end questions. Participants answered five demographic questions regarding gender, age, college level, college type, and department types. Also, they were asked to rate the items using a five-point scale (“Strongly Agree”, “Agree”, “Neutral”, “Disagree”, “Strongly Disagree”). In addition, the participants were asked to input additional comments as open-end questions. The Likert scale and text-based measurements are reconstructed into scales and items as shown in Table 3 and Table 4 , respectively.

Measures for distance learning,

Measures for instructional methods,

5. Statistical Methods

The distributions of student's responses to distance learning were analyzed using cross-tabulations and statistical tests. The Chi-square test of independence was used to test if there was a significant association between students’ response to the distance learning experience by college level and college type. The Chi-Square test is a non-parametric test, and it is suitable for categorical data analysis to assess the probability of association or independence of facts ( McHugh, 2012 ). It does not impose prior conditions to the data such as equality of variance or residual homoscedasticity ( Pandis, 2016 ). The test measures how much difference exists between the observed counts and the counts that would be expected if there were no relationship at all in the population. In this study, the null hypothesis (H o ) stated that there is no difference in student rating of a given question related to distance learning across college level or college type. The alternative hypothesis (H 1 ) is the inverse of the null hypothesis stating that there is a difference in student ratings by college type or college level. The null hypothesis was rejected if the p -value was less than 0.05. The Chi-square statistics can be computed using Eq. (1 );

whereby, O i j is the observed frequency and E i j is the expected frequency. The computed χ 2 is compared with the critical value obtained from the Chi-square distribution. The degrees of freedom ( df ) for the critical value can be computed as (c-1) (r-1) , where c is the number of columns and r is the number of rows in the contingency table.

The Cramer's V is also used in conjunction with Chi-Squared statistics. It is used to indicate the strength of association between two variables ( Allen, 2017 ). The Cramer's V values range from 0 which corresponds to no association to 1 which corresponds to complete association. It can be computed by taking the square root of the chi-square statics divided by the sample size and normalized by the minimum of rows or columns in the contingency table as shown in Eq. (2 )

whereby χ 2 is the Chi-squared statistics, n is the sample size involved in the test, c is the number of columns and r is the number of rows.

The result section is subdivided into two subsections namely students’ perceptions of distance learning and students’ perception of instructional methods. For each subsection, the students’ rating results are discussed based on college level and college type. Data were analyzed by calculating Chi-square values, , and p-values as discussed in the statistical methods section.

6.1. Students’ perceptions of distance learning

In this study, WMU students were asked to share their experience of distance learning as the WMU campuses were compelled to move from in-person class to distance learning class during the COVID-19 pandemic. The questions for this section were designed to capture four main aspects of distance learning which were collaboration and interactions, improvement associated with distance learning, flexible options associated with distance learning, and availability of required resources such as personal laptops and the internet for distance learning. Fig. 1 provides an overall of students’ ratings ranging from strongly agree (5 points) to strongly disagree(0 points) on the four main aspects of distance learning that were explored in this study. Distance learning flexibility had the highest ratings while student interaction and collaboration had the least ratings.

Overall student's perception of distance learning during the COVID-19 pandemic,

Figs. 2 and ​ and3 present 3 present the results of students’ view of distance learning by college level and college type, respectively. Table 5 provides the Chi-square test results of students’ ratings by college level and college type. Most of the students felt distance learning disrupted and diminished interactions and collaboration with classmates and instructors. The student ratings significantly varied across college level (? 2 =44.517, p=0.001) and college type (? 2 =49.941, p=0.023) as shown in Table 5 . For the college level, about 95% of freshmen disagree with the statement that distance learning provides more interactions with other students. However, the percent of disagreement diminished with a higher college level as shown in Fig. 2 . Only 75% of the graduate student disagree with the statement while 12% felt that distance learning increases interactions with classmates. Only 12% of the graduate students felt that distance learning increases interactions with classmates while 75% of the graduate student disagree with the statement. The same trend was observed when comparing the rate of agreement about the interaction with the instructors. Most of freshmen (87%) felt distance learning has reduced the interaction compared to only 66% of graduate students. Sophomore, Juniors, and Seniors' percentage of disagreement with the students’ interaction ranged from 76% to 82%. From the results, it can be observed that most of the students perceived a lack of interaction among students and the instructor as the result of shifting to distance education during the pandemic, mostly the freshman. The effect was less severe to higher college level especially graduate students. College experience may have contributed to the observed pattern.

Overall student's perception of distance learning during the COVID-19 pandemic by college level,

Overall student's perception of distance learning during the COVID-19 pandemic by college type,

Chi-Squared test of association students rating of instructional methods with college level and college type,

It was also the aim of this study to assess student's perspectives on how distance learning affected their academic progress and success. Four different questions were asked under the “distance learning improvement” category as shown in Fig. 2 . Most of the students indicated that distance learning did not improve on-campus classes or instructions. Further, the rating indicated that most of the students did not learn as much as they would have learned in in-person classes. On the issues of academic success, most students stated that distance learning did not improve their grades compared to if the classes were done in person. The students' rating of academic progress and success during distance learning significantly vary by college level but not college type as shown in Table 5 . The majority of graduate students (41%) agreed that they have learned as much as they learned before the COVID-19 pandemic during in-person classes compared to 27% of students who disagreed or strongly disagreed with the statement. For the undergraduate level, most of the students felt the academic progress and success were negatively affected by the transition to distance learning.

Among the strength of distance learning is the location and time flexibility in class attendance and doing assignments. Students were asked to rate how distance learning has impacted the time they spent completing their assignments. Further, the students were asked if distance learning is effective due to location and time flexibility. The distribution of the results by college level and college type shows that most of the students agreed that distance education offered time and location flexibility. Their responses were in most cases uniform across college level and college type except for location flexibility (? 2 =34.700, p=0.010). The flexibility option offered by distance learning was much appreciated by graduate students (84%) compared to undergraduates.

For distance learning to be effective, students need to have essential resources such as reliable internet access and personal computer resources. The results indicated some minor concerns on the issues of internet at home. About 93% of students that were surveyed reported having a computer or a device to use for distance learning. Only 4% of the student indicated that they lacked personal computers with 4% being neutral on the subject. This was a good indicator for an effective distance learning experience despite the concerns that were raised in the area of interaction and collaboration and improvement in academic progress and success.

6.2. Students’ perceptions of instructional methods

The study assessed student's perception of distance learning instructional methods that were offered by WMU. Instructional methods are the teaching and learning techniques, used by teachers to create learning environments and to specify the nature of the activity in which the teacher and learner will be involved during the education process. Distance education requires different instructor's efforts, special tools, and teaching methods than those needed in traditional classrooms.

The importance of the instructor in distance learning is growing and should be more intensive to the adaptation of new learning environments. Instructor availability, communication, and feedback are some factors the impact distance learning ( Yengin, Karahoca, Karahoca, & Yücel, 2010 ).

A total of ten questions were asked and grouped into three main groups namely instructors, distance learning tools, and distance learning methods preferences as shown in Fig. 4 . The Chi-square test results of students rating of instruction methods by college level and college type presented in Table 6 .

Overall student's perception of instructors and instructions methods during the COVID-19 pandemic,

Chi-Squared test of association students rating of instructional methods with college-level and college type,

For the issues of instructors, the study intent was to discern how students rated the availability of instructors in cases where they needed help, and whether the instructors were able to provide clear guidance to students on how they can access the course material online. The distribution of student's ratings showed that the student preferred face-to-face meetings that online meetings with the instructors. The results were consistent across college level and college type as shown in Figs. 5 and ​ and6 respectively 6 respectively under the “distance learning methods’ preference” subsection. From Table 6 , Significant variation of students’ ratings by college-level was observed when students were asked whether they disagree or disagree about the availability of instructors(? 2 =41.765, p=0.003), clear instruction provided by the instructors (? 2 =33.900, p=0.027) and methods of assessing students learning (? 2 =37.753, p=0.009). In both cases, the graduate students had a higher percentage of agreement with above-mentioned statements as shown in Fig. 5 . Significant variation of students’ ratings by college type was observed on the issues of instructors’ availability when students needed help (? 2 =51.197, p=0.017). The availability of instructors was highly rated by graduate college followed by the college of health and human services while poor ratings of instructors’ availability were observed in Haworth college of business. The observed variation by college type and college level on the issue of instructor availability offers WMU a clear spectrum of which colleges and students need special attention to improve the effectiveness of distance learning.

Overall student's perception of instructors and instructions methods during the COVID-19 pandemic by college level,

Overall student's perception of instructors and instructions methods during the COVID-19 pandemic by college type,

The study also examined the efficacy of distance learning tools such as WebEx, and Microsoft team from the students’ perceptive. Graduate students’ ratings of these tools were slightly higher than undergraduate level with 61% agreeing that distance learning effective and easy to use (68%) as shown in Fig. 5 under the “distance learning tool” subsection. The undergraduate student's rating leaned towards disagreement and neutrality. The distribution of ratings by college type showed a poor rating of the distance learning tools by the college of aviation followed by Haworth college of business.

Another interesting subject with was explored in this study was student's perspective of distance learning methods that were provided by WMU. The methods of learning that were examined include synchronous teaching method, asynchronous teaching method, hybrid method. Each method has its pros and cons. With synchronous learning methods, students learn and interact with instructors and classmates in real-time while asynchronous learning instructors provide all the necessary material, and students can read and complete assignments and exams in their own schedule. Students were asked to rate each of the above-mentioned learning methods. Students especially freshmen strongly preferred in-person or hybrid classes over online classes (? 2 =51.197, p=0.017). Also, there was a consensus among students that online classes were the preferable choice due to the COVID-19 crises. However, there was no apparent preference for the form of distance learning method. About 42% of students prefer asynchronous learning while only 29% of students preferred synchronous learning. The rest of the students either strongly disagree, disagree, or were neutral about the subject.

6.3. Textual exploratory analysis

An open-ended question was asked to students about the best and worse experiences of online learning. The question was specifically designed to discern other important concerns that were not covered in Likert-scale questions. A text mining approach was used to extract information from the students’ opinions. Fig. 7 shows the word network diagram showing the keywords that were used by students to articulate their experience of distance learning. Each word has been reduced to its root form through the process known as stemming. The most frequent pairs of words for the best experience of distance learning are “flexible location”, “flexible schedule”, “social distance”, “park pass”, among others. The most frequent pair of words that were used to describe the worse experience of distance learning include “human interact”, “due date”, “distance learn”, “real-time” and “class synchron”. The main themes that were prevalent in students’ comments about the worse distance learning experience are lack of human interaction, social connections, self-motivation, and concentration. Also, technological glitches such poor internet connections and students’ or instructors’ inexperience using online systems were mentioned by students.

Students’ experience of distance learning: Textual exploratory analysis,

7. Discussion

The results of this study are indicative of less positive perceptions of distance learning across college level and college type. Positive attitudes and a high level of satisfaction among all students are what designers and instructors of distance learning need to achieve. The results could provide a useful understanding of what brings about less positive student perceptions of distance learning. For instance, the less positive perceptions may be related to the type of distance learning methods or tools, or they could be linked to other different factors such as college level, college type, previous distance learning experience, and interaction with instructors and classmates. In this study, we found both the college level and college type significantly impacted students’ perceptions of distance learning on the seven defined scales. These two factors influence students’ perceptions and attitudes toward distance learning. Furthermore, all the participants were actively enrolled in a distance learning class at the time when they reported their perceptions, and that may have influenced their overall negative perception of distance learning.

The findings of the study that relate to the influence of college-level showed that most freshmen perceived a lack of interaction among students and instructors as the result of shifting to distance education during the pandemic. The effect was less severe to higher college level, especially graduate students. In the area of improvement in academic progress and success, most of the undergraduate students reported a more negative view than the graduate students. The undergraduate students’ academic progress and success were negatively affected by the transition to distance learning in terms of the extent to which: distance learning did not improve on-campus classes or instructions, students did not learn as much as they would have learned in in-person classes, distance learning did not improve their grades compared if the classes were done in-person. The impediment to academic progress brought by the pandemic has also been reported elsewhere in high education institutions ( Kummitha, Kolloju, Chittoor, & Madepalli, 2021 ; Pokhrel & Chhetri, 2021 ). Much of it has been attributed to a lack of institutional preparedness to cope with the unprecedented pandemic. Also, due to the lack of best of available information on best practices( Armstrong-Mensah, Ramsey-White, Yankey, & Self-Brown, 2020 ) an almost trial and error process of gauging and supporting students has been reported during the pandemic deterred the overall academic performance and progress.

On the other hand, students across the college level reported positive perceptions about the location and time flexibility of distance learning in class attendance and doing assignments. Specifically, distance learning flexibility was much appreciated by graduate students compared to undergraduates. The benefits of distance learning in terms of location and time flexibility have been widely reported in most of the Covid-19 related papers. The benefits include but are not limited to less commuting time, savings on gas, time management, and more time to spend with family members ( Almaiah, Al-Khasawneh, & Althunibat, 2020 ; Armstrong-Mensah et al., 2020 ). Increased flexibility has also been shown to enable independent learning among students ( Müller, Goh, Lim, & Gao, 2021 ).

In terms of reliable distance learning resources, most of the students reported having internet access and a computer or a device to use for distance learning. Only a small number of the students indicated that they lacked personal computers. Similar results were obtained by Armstrong-Mensah (2020) with the majority of students at Georgia State University reported having internet access and digital devices which support distance learning. However, other studies have reported the disparity in digital tools and internet access among students ( Coello, Salazar, & Taborda, 2020 ) Equitable access to the internet and other supporting tools is of paramount importance to students enrolled in distance learning. Each institution should aim at setting out measures that ensure the pandemic does not widen the digital divide between students

The finding that all the students reported a highly positive perception of the face-to-face meeting with instructors’ subscale is an important one that the instructors of distance learning classes need to consider. Similarly, a positive perception was reported by college levels in terms of the availability of instructors, clear instruction provided by the instructors, and methods of assessing students learning. The study also tested the efficiency of distance learning tools such as WebEx and Microsoft teams from the students’ perceptive. Graduate students reported high positive perception than undergraduate students on using and learning through these tools. The perception and acceptance of distance learning tools can be enhanced by training educators and students on the use of digital technology which has now become an integral part of higher education institutions and universities ( Coello et al., 2020 ; Lazarova, Miteva, & Zenku, 2020 ; Rashid & Yadav, 2020 ).

The findings of students’ perspective of distance learning methods that were provided by WMU showed that most of the students, especially the freshman reported a highly positive perception of preferring in-person or hybrid classes over online classes. The preference for hybrid or blended classes has also been reported elsewhere among educators and students ( Müller et al., 2021 ). It has been shown to provide a better understanding of the courses due to an increase in social interaction among peers and instructors( Kimkong & Koemhong, 2020 ). In the meantime, most of the students, especially the graduate students, reported a positive perception of the preference for online classes due to the COVID-19 crisis. However, there was no apparent preference for the form of distance learning method. Seniors and juniors reported more negative perceptions of the synchronous learning method than other college levels, while freshmen reported a highly negative perception of the asynchronous learning method than other students. Synchronous learning has been reported in previous studies to improve instructor-teacher interaction. A study by Müller et al (2021) reported an increased level of engagement among students in distance learning who were normally quiet during in-person classes. A continuous assessment of student readiness to various forms of online learning is needed based on equipment capability, technology skills, self-directed learning, motivation, and perceived usefulness (Widodo, 2020).

The findings of the study that rely on the influence of college type showed that the interaction with classmates was poorly rated by all colleges. However, the College of Aviation and College of Fine Arts reported a highly negative perspective comparing to other colleges. On the distance learning flexibility scale, most of the colleges, especially Haworth College of Business, positively rated the statement: “distance learning causes spending more time doing your work.” A highly positive rating on having internet access at home was reported by the College of Health and Human Services, followed by the College of Fine Arts. In addition, the availability of instructors was highly rated by Graduate College followed by College of Health and Human Services, while poor ratings of instructors’ availability were observed in Haworth College of Business. The issue of instructor availability offers WMU a clear spectrum of which college and students that need special attention to improve the effectiveness of distance learning. Conclusively, the distance learning tools were negatively rated by the College of Aviation followed by Haworth College of Business. The observed disparity in distance learning rating across college types emphasizes the key challenge of distance learning which is to create a holistic and inclusive learning experience that suffices the diverse student needs. These needs tend to vary mostly by college type or nature of the subjects ( Kimkong & Koemhong, 2020 ; Müller et al., 2021 ).

8. Conclusions

In just a few months, The COVID-19 pandemic, caused by the latest coronavirus, resulted in the sudden closure of the universities globally and moved face-to-face classes to distance or online learning, which changed the lives of masses across the globe, including higher education students. In this respect, we introduce this study to reveal students’ perspectives and understand their preferences and needs on distance learning at Western Michigan University (WMU). All students in all different colleges and departments were invited to participate in this study. The findings have important implications for distance learning educators and may help the top management of the university to assess distance learning and make future decisions to enhance the weakness of this type of learning.

Considering the present study, the findings could be split into instructor factors that influenced the experience and student factors that influenced the experience. The instructors need to implement strategies that are influenced by the college's level and type to address students’ needs for better instructions, a proper teaching method, a suitable grading schema to assess student work and comprehension, face-to-face interaction, small group discussion, collaborative projects, and group presentation. These strategies may help boost students’ achievement and overcome their difficulties with distance learning.

On the student side, the capacity to adjust to school and life, acceptance of personal responsibility, connection with peers, and time management skills are the most factors that influenced the student's experience.

Future studies could examine perceptions of distance learning at the departmental level. Generally, the findings and discussion of this study have important implications for future research. As the survey for this study was done during the pandemic's initial period, the finding is essential and points to the overall higher levels of awareness and comfortability with the distance learning among the students in general. So, studies could be established to determine whether WMU students’ perceptions of distance learning are affected by the impact of previous enrollment in distance learning courses comparing to the current study results. Finally, further research could be examined how students’ perceptions will change over academic years.

Conflict of Interest

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• Research article
• Open access
• Published: 20 May 2020

Students’ perceptions on distance education: A multinational study

• Patricia Fidalgo 1 ,
• Joan Thormann 2 ,
• Oleksandr Kulyk 3 &
• José Alberto Lencastre 4  

International Journal of Educational Technology in Higher Education volume  17 , Article number:  18 ( 2020 ) Cite this article

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Many universities offer Distance Education (DE) courses and programs to address the diverse educational needs of students and to stay current with advancing technology. Some Institutions of Higher Education (IHE) that do not offer DE find it difficult to navigate through the steps that are needed to provide such courses and programs. Investigating learners’ perceptions, attitudes and willingness to try DE can provide guidance and recommendations for IHEs that are considering expanding use of DE formats. A survey was distributed to undergraduate students in Portugal, UAE and Ukraine. The results of this pilot study showed that in all three countries, students’ major concerns about such programs were time management, motivation, and English language skills. Although students were somewhat apprehensive many indicated they were interested in taking DE courses. Six recommendations informed by interpretation of students’ responses and the literature, are offered to assist institutions who want to offer DE as part of their educational strategy.

Introduction

The World Wide Web has made information access and distribution of educational content available to a large fraction of the world’s population and helped to move Distance Education (DE) to the digital era. DE has become increasingly common in many universities worldwide (Allen & Seaman, 2017 ). Nonetheless, there are still many universities that do not provide this opportunity because it is not part of their institutional culture. As DE becomes more prevalent, countries and Institutions of Higher Education (IHE) that do not provide DE courses will need to look at this option to retain and expand their student population. (Keegan, 1994 ; Nakamura, 2017 ).

In order to develop such programs, it is useful to determine if students are receptive to taking such online courses and are prepared to do so. This study addresses students’ perceptions and their interest in DE. In addition, it provides a comparative analysis across three countries whose IHEs do not have extensive offerings in DE. The results of this research provide some strategies to encourage and support students to take DE courses.

Literature review

A seminal article by Keegan ( 1980 ) presents key aspects of DE. Some of the elements are: physical separation of teacher and learner, learning occurs in the context of an educational institution, technical media are used, teacher and learner communicate, face to face meetings are possible, and an industrial model of providing education is used. More recently varying definitions of DE seem to be based on the perspective of various educators and to reflect the educational culture of each country and IHE. However, some common descriptors seem to be accepted by most stakeholders in the field. Distance education is an educational experience where instructors and learners are separated in time and space (Keegan, 2002 ) which means it can happen away from an academic institution and can lead to a degree or credential (Gunawardena, McIsaac, & Jonassen, 2008 ).

Although there are different types of DE, this research focuses on online learning. The following types of online learning will be investigated: synchronous, asynchronous, blended, massive online open courses (MOOC), and open schedule online courses. In synchronous instruction, teachers and learners meet (usually online) for a session at a predetermined time. According to Watts ( 2016 ) live streaming video and/or audio are used for synchronous interaction. Although videoconferencing allows participants to see each other this is not considered a face-to-face interaction because of the physical separation (Keegan, 1980 ).

Asynchronous instruction means that teachers and learners do not have synchronous sessions and that students have access to course content through the Internet at any time they want or need. Communication among the participants occurs mainly through email and online forums and is typically moderated by the instructor (Watts, 2016 ). According to Garrison ( 2000 ) “Asynchronous collaborative learning may well be the defining technology of the postindustrial era of distance education.” (p.12) Yet another type of DE is blended learning (BL). Garrison and Kanuka ( 2004 ) define BL as combining face-to-face classroom time with online learning experiences. Although it is not clear as to how much time is allocated to online in the blended model “the real test of blended learning is the effective integration of the two main components (face-to-face and Internet technology) such that we are not just adding on to the existing dominant approach or method.” (p.97) In the BL format different teaching strategies and instructional technology can be used to help individuals who have different learning styles, needs and interests (Tseng & Walsh Jr., 2016 ).

Another type of DE is MOOCs (Massive Online Open Courses). This format was first introduced in 2006 and offers distributed open online courses that are available without cost to a very large number of participants (Cormier, McAuley, Siemens, & Stewart, 2010 ). MOOCs origins can be traced to the Open Access Initiative in 2002 which advocates sharing knowledge freely through the Internet. By providing educational opportunities MOOCs can address the increasing demand for training and education (Zawacki-Richter & Naidu, 2016 ). Finally, in open schedule online courses students work asynchronously with all the materials being provided digitally. Although there are deadlines for submitting assignments, students working at their own pace have some independence as to when they do their coursework (Campus Explorer, 2019 ).

There are advantages and disadvantages in taking DE courses. Some of the advantages are self-paced study, time and space flexibility, time saving (no commute between home and school) and the fact that a distance learning course often costs less. Disadvantages include a sense of isolation, the struggle with staying motivated, lack of face-to-face interaction, difficulty in getting immediate feedback, the need for constant and reliable access to technology, and occasionally some difficulty with accreditation (De Paepe, Zhu, & Depryck, 2018 ; Lei & Gupta, 2010 ; Venter, 2003 ; Zuhairi, Wahyono, & Suratinah, 2006 ).

Most of the literature concerning student perception of DE courses, both blended and entirely online, involves students who have enrolled in online courses. Some articles address comparisons of perceptions between face-to-face and online students regarding DE (Daniels & Feather, 2002 ; Dobbs, del Carmen, & Waid-Lindberg, 2017 ; Hannay & Newvine, 2006 ; Lanier, 2006 ). Additional studies address adult and undergraduate students and cover many aspects of the online experience (Dobbs et al., 2017 ; Horspool & Lange, 2012 ; Seok, DaCosta, Kinsell, & Tung, 2010b , a ). However, little, if any research has been conducted that only addresses perceptions of students who live in countries in which few IHEs offer online courses.

In a study comparing online and face-to-face learning, Horspool and Lange ( 2012 ) found that students chose to take online courses to avoid travel time to class and scheduling problems. A majority of both face-to-face and online students did not experience technological issues. Both groups also found that communication with the instructor was adequate. Online students indicated that instructor response time to questions was prompt. By contrast online students perceived peer communication as occurring much less often. Course satisfaction was comparable for both formats (Horspool & Lange, 2012 ). Responses to another survey concerning online and traditional course formats found that students’ reasons for taking online courses included flexibility to accommodate work and family schedules, the ability to avoid commuting to the university and more online courses being available to them (Dobbs et al., 2017 ). Both online and traditional students agreed that traditional courses were easier, and they learned more in that format. They also concurred that online courses required more effort. Experienced online students indicated that the quality of their courses was good while traditional students who had never taken an online course felt that the quality of online courses was lower.

There is additional research that focuses on students including those enrolled in community colleges, MOOCs, blended learning as well as adult learners. Community college students’ and instructors’ perceptions of effectiveness of online courses were compared by Seok et al. ( 2010b , a ). The researchers focused on pedagogical characteristics (management, Universal Design for Learning, interaction, teaching design and content) and technical features (interface, navigation and support). In addition, responses were examined based on various aspects of the subjects’ demographics. Two surveys with 99 items were distributed electronically. One survey was for instructors and the other for students. In general, instructors and students indicated that teaching and learning online was effective. Female students responded more positively to most questions concerning effectiveness, and instructors also found it more positive (Seok et al., 2010b , a ).

Students who enrolled in a MOOC were motivated to take other courses in this format based on their perception that it was useful for achieving their goals. In addition, their motivation was high if the course was posted on a platform that was easy to use (Aharony & Bar-Ilan, 2016 ). This study also found that as students proceeded through the course, they gained confidence.

Blended learning was examined by Kurt and Yildirim ( 2018 ) to determine student satisfaction and what they considered to be important features of the blended format. The results indicated that the Turkish students who participated, almost unanimously felt that BL was beneficial and that their own role and the instructors’ role was central to their satisfaction. The authors stated, “the prominent components in the process have been identified as face-to-face lessons, the features of online course materials, LMS used, design-specific activities, process-based measurement and evaluation, student-student interaction and out-of-class sharing respectively.” (p. 439) DE has a growth potential and offers the opportunity to reach many people (Fidalgo, 2012 ), hence it can be used as a technique for mass education (Perraton, 2008 ). According to Perraton ( 2008 ) DE can be adapted to the needs of current and previous generations who did not complete their education. DE can also reach individuals who live in remote locations and do not have the means to attend school.

Methodology

Study goals.

The goal of this pilot study is to examine what undergraduate students’ perceptions are concerning DE and their willingness to enroll in this type of course. This study focuses on three countries that do not offer extensive DE accredited programs. By comparing three countries with similar DE profiles, commonalties and differences that are relevant and useful can be found. When the IHEs from these countries decide or have the conditions to move towards DE, the results of this study may help them adapt this format to their particular context and students’ needs. Results may also help IHEs plan their strategy for offering online courses to current and future students and attract prospective students who otherwise would not be able to enroll in the face-to-face courses that are available.

Research questions

Have undergraduate students taken an online course previously?

What are undergraduate students’ perceptions of distance education?

What are the reasons for undergraduate students to enroll/not enroll is distance education courses?

What preparation do undergraduate students feel they need to have before taking distance education courses?

What is the undergraduate students’ receptivity towards enrolling in distance education courses?

What types of distance education would undergraduate students be interested in taking?

This research was conducted at IHEs in three countries (Portugal, Ukraine and UAE). A description of each country’s sociodemographic and technological use provides a context for this study.

Portugal, a country located at the western end of the European continent, has a resident population of just over 10 million people (Instituto Nacional de Estatistica, 2019 ). Data collected by Instituto Nacional de Estatistica in 2019 indicated that almost 81% of households in Portugal had Internet access at home. According to the Portuguese National Statistical Institute ( 2019 ), the rate of Internet use by the adult population is about 76%. Among this population, people who attend or have completed secondary and higher education have a higher percentage of Internet use (98%) (Instituto Nacional de Estatistica, 2019 ).

The most used devices to access the Internet are smartphones and laptops. Regarding computer tasks, the most frequent ones are copying and moving files and folders and transferring files from the computer to other devices (PORDATA - Base de Dados Portugal Contemporâneo, 2017 ).

Among Internet users, 80% use social networks, which is a higher percentage than the European Union (EU) average. Mobile Internet access (outside the home and workplace and on portable devices) is 84% and maintains a strong growth trend (Instituto Nacional de Estatistica, 2019 ).

Ukraine is one of the post-soviet countries located in Eastern Europe and it strives to be integrated in economic and political structures of the EU. The current population of the country is 42 million. Despite the low incomes of many Ukrainians, modern technological devices are widespread among the population. The State Statistics Service of Ukraine ( 2019 ) reported that there were 26 million Internet subscribers in the country in the beginning of 2019. However, Ukrainians do not have a high level of digital literacy yet. According to the Digital Transformation Ministry of Ukraine (Communications Department of the Secretariat of the CMU, 2019 ), almost 38% of Ukrainian people aged from 18 to 70 have poor skills in computer literacy and 15.1% of the citizens have no computer skills.

According to the survey conducted by the Digital Transformation Ministry of Ukraine (The Cabinet of Ministers of Ukraine, 2019 ) 27.5% Ukrainian families have a tablet, and 30.6% have one smart phone, 26.4% have two smart phones, 16.5% have three smart phones and 10.8% have four and more smart phones. As for laptops, 42.7% Ukrainian families have a laptop and 45.6% have a desktop computer (The Cabinet of Ministers of Ukraine, 2019 ). The data from the ministry did not indicate if families have multiple devices, however the data shows that technological devices are widespread.

The United Arab Emirates (UAE) is a country located in the Persian Gulf that borders with Oman and Saudi Arabia. The UAE has a population of 9.77 million and is one of the richest countries in the world based on gross domestic product (GDP) per capita. The resident population consists of 11,5% Emiratis and the remaining residents are expats from countries such as India, Pakistan, Philippines, Egypt and others (Global Media Insight, 2020 ).

Regarding technology use, 91% of the residents use mobile Internetand over 98% of the households have Internet access (Knoema, 2018 ). Mobile devices such as smartphones are used to access the Internet mainly at home or at work (Federal Competitiveness and Statistics Authority, 2017 ).

In 2017 the most frequent Internet activities were: sending/receiving emails (61%), posting information or instant messaging (55%), getting information about goods or services (45%), reading or downloading online newspapers, magazines or electronic books (41%) and telephoning over the Internet/VOIP (33%). Downloading movies, images, music, watching TV or video, or listening to radio or music is also a frequent activity performed by 27% of the Internet users followed by Internet banking (25%) and purchasing or ordering good and services (22%) (Federal Competitiveness and Statistics Authority, 2017 ).

While these three countries were selected due to the location of the researchers and thus provided convenience samples, the three countries have a similar lack of DE offerings. Online surveys were emailed to students enrolled in a variety of undergraduate face-to-face courses during the fall semester of 2018. The students in Portugal and the UAE were enrolled in a teacher education program and the survey was emailed to two course sections in Portugal (73 students) and four course sections in the UAE (108 students). At the IHE in Ukraine, students were majoring in applied mathematics, philology, diagnostics, social work and philosophy, and surveys were emailed to 102 students who were enrolled in five course sections. In Portugal and Ukraine, the URL for the online survey was emailed by the instructor of all the course sections. In the UAE the instructor who emailed the URL for the survey taught two of the course sections. The students in the other two sections knew this instructor from taking courses with her previously. The students participating in this study were a convenience sample based on the disciplines taught by the researchers.

Data collection

An online survey with 10 closed questions about undergraduate students’ perception and receptivity towards enrolling in DE courses was developed by the researchers. Ary, Jacobs, Sorensen, and Walker ( 2010 ) compared traditional methods (i.e. face-to-face, paper and pencil) with web-based surveys and found the latter to be are more effective for gathering data from many participants. The questions designed by the researchers were informed by their experience/practice as well as in-depth literature review. The survey was created to respond to the research questions that guided this study. Response choices to the multiple-choice questions were based on issues and concerns related to DE. Students’ responses were collected towards the end of the first semester of the 2018/19 academic year.

The survey was developed to address research questions that assess undergraduate students’ perceptions of DE and students’ receptivity towards enrolling in DE courses (c.f. Appendix ). The use of surveys allows researchers to “obtain information about thoughts, feelings, attitudes, beliefs, values, perceptions, personality and behavioral intentions of research participants.” (Johnson & Christensen, 2014 , p. 192) The survey questions included multiple response formats: Likert scale, select more than one response and multiple choice. Surveys for Portugal were presented in Portuguese. In Ukraine the surveys were translated into Ukrainian. Since English is the language of instruction at the UAE institution, their survey was in English. The URL for the survey was emailed to students by their instructors and was available in an online Google Form. The survey took approximately 10 min to complete. The study consisted of a “self-selected” convenience sample.

Data analysis

Survey results were recorded in Google Forms and an Excel spreadsheet was used to collect students’ responses. Descriptive statistics of the responses to the survey are presented in graphs and tables with percentages of responses displayed. The descriptive statistics provide summaries about the sample’s answers to each of the questions as well as measures of variability (or spread) and central tendency.

Research approval and data management

The research proposal was submitted to the Research and Grants Committee and approved by the Institutional Review Board of the college in the UAE. No personal information (name, College ID number or any other type of information that allows the identification of students) was asked from the students in the surveys. The surveys were anonymous. Only the Principal Investigator (PI) had access to all the data collected. The data will be stored in the PI’s password protected computer for 5 years.

Fifty five of the 73 Portuguese students who received the survey responded and 98 of the 108 UAE students responded. In the Ukraine 102 students were sent surveys and 70 responded. Below are participants’ responses to questions concerning age, gender, as well as level of confidence using the computer and the Internet.

Students’ age range was from 17 to 50 years old. Most students’ age ranges were between 17 and 29 years. Survey responses indicated that 7% of the students in the UAE were male and 93% female, in the Ukraine 43% were male and 57% female and in Portugal 9% male, and 91% female.

Participants were asked about their level of confidence using a computer and the Internet. Results are presented in Table  1 .

The use of participants from three countries allows the study of trends and to determine differences and/or similarities of perceptions about DE. Although the students were enrolled in courses in diverse content areas, they were all undergraduates, almost all under 30 years old, and most were confident using the computer and Internet. These demographic similarities provided a relatively cohesive group for this study while allowing a comparison across countries.

A range of questions were asked about students’ attitudes towards and experience with DE. To determine the participants’ experience with DE two questions were asked.

The data indicates that out of 223 students who responded to the survey, a total of 63 students have taken DE courses. Half of the Ukraine students, about one quarter of the UAE students and only 5% of students in the group from Portugal had taken DE courses (Fig.  1 ). As shown in Fig.  2 , of the students who have had previous experience in DE, most Ukraine students have taken one or two online courses, most UAE students have taken one course and a few Portuguese students have taken one course.

Students that have taken distance education courses

Number of distance education courses taken

More than half of Portuguese students, about two thirds of the Ukraine students and a little over one third of UAE students had a Very favorable or Favorable attitude towards DE. Approximately one third of Portuguese and Ukraine students were Neutral/Unable to judge their attitude. A little less than half of UAE students also indicated this. A small percentage of Portuguese, and one fifth of UAE students indicated their attitude was Very unfavorable or Unfavorable and no Ukraine students reported this (Table 2 ).

More than one third of Portuguese students shared that managing class and study time, saving time by choosing study location and working at their own pace were reasons to enroll in DE. About two thirds of the students from Ukraine reported that working at their own pace and managing their study time were reasons to enroll. A little more than half of these students reported that reasons for enrolling in DE included managing class time, saving time by selecting study location and not having to travel to school as well as having more options for courses or colleges to attend. Almost half of the UAE students had similar reasons for enrolling in a DE courses including managing class and study time, saving time by choosing study location and working at their own pace. In addition, a little more than half of the UAE students also shared that having more options for courses or colleges to attend were reasons to enroll. The reasons that were selected the least by all three groups were that courses were less expensive and enrolling in a preferred program (Tables  3 and 4 ).

Students were given eleven options as to why they would not enroll in DE courses, which are displayed in Tables  5 and 6 . Two reasons that were chosen most often were difficulty staying motivated and preferring face-to-face classes. A small number of Ukraine students reported this as a reason to not enroll in DE courses. Difficulty getting immediate feedback was also a concern for UAE students. Close to one third in the three groups indicated that difficulty contacting the instructor and interacting with peers as well as missing campus life are reasons for not enrolling. About one tenth of Portuguese, one fifth of Ukraine and one fifth of the UAE students reported difficulty getting accreditation as a reason for not enrolling. Not knowing enough about DE was indicated by one tenth of Portuguese, one fifth of Ukraine and one fifth of the UAE students. Only a small number of all the students indicated three categories that are frequently cited in the literature as preventing students from enrolling, these include access to technology, feeling of isolation and too great an expense.

Tables  7 and 8 show student responses to a question regarding the preparation they think they would need before enrolling in a DE course. A little over one tenth of the Portuguese students indicated that they needed better computer equipment, writing skills and a dedicated study space. About one quarter of these students reported they need better skills in the following areas: time management, computer and English language skills, as well as needing to have learning goals and objectives. Having a better Internet connection and the need to develop a study plan was shared by approximately one third of these students. Finally, the highest rated prerequisite for these Portuguese students was to be more motivated.

Few of the Ukraine students felt that they needed better computer equipment or skills, a dedicated study space or a better Internet connection at home. Their concerns focused on their behaviors as students since half or a little more than half felt they needed to be more motivated, have learning objectives and goals, a study plan and better management skills. About one third of these students also reported that they needed better English language skills.

The UAE students were less confident than the Ukraine students about computer skills and needing better equipment and a better Internet connection at home. Almost half of these UAE students reported their need for a study plan and motivation as their most pressing needs. Better management and English language skills were recorded by about one third of the students. One quarter of the UAE students felt they needed better writing skills and a dedicated study space.

Table 9 shows students’ interest in enrolling in DE courses. Almost one quarter of the Ukraine students are Extremely interested in taking DE courses and almost half are Somewhat interested. This contrasts with the students from Portugal who indicated that only 5% are Extremely interested and almost a quarter Somewhat interested. The UAE students’ interest in enrolling fell in between the students from the two other countries. One fifth to almost one third of all three groups were Neutral/Unable to judge. About one tenth of students from Ukraine reported Not being very interested or Not at all interested which contrasts with the Portuguese and UAE students whose numbers were about one half and one quarter respectively.

Tables  10 and 11 show the types of DE that the students were interested in trying. Portuguese students favored Open schedule courses, followed by Blended learning and Synchronous. Few of these students were interested in MOOCs and Asynchronous. More than half of the students from Ukraine were interested in MOOCs and Blended learning followed by Open schedule. About one third of these students were interested in Synchronous and Asynchronous. UAE students most popular formats were Open schedule and Blended learning followed by Synchronous and Asynchronous. There was little interest in MOOCs by the UAE students. Few Portuguese and Ukraine students indicated that they would not take a DE course, however, almost a quarter of the UAE students indicated this.

Data indicates close to a 100% of the UAE residents use the Internet at home or on their mobile devices (Knoema, 2018 ). By contrast a smaller percentage of individuals use the Internet in Portugal and the Ukraine (Infographics, 2019 ). Internet use in each country does not seem to greatly impact UAE students’ opinions regarding DE.

Students’ perceptions of DE vary across the participants from the three countries. Portuguese and Ukrainian students rated DE more favorably than UAE students. Half of the Ukrainian students have experience with DE which might account for their favorable attitude. In contrast, in Portugal only a very small percentage of the students had experience. However, this does not seem to have negatively influenced their attitude towards DE. The interest level and engagement with new technologies by Portuguese students may help explain the favorable perception the participants had toward DE. A study by Costa, Faria, and Neto ( 2018 ) found that 90% of Portuguese students use new technologies and 69% of them use new technologies more than an hour and a half a day. Based on three European studies, Diário de Noticias ( 2011 ) stated that Portuguese students “appear at the forefront of those who best master information and communication technologies (ICT).” (para.1) Another factor influencing respondents might be that currently, and for the first time, the Portuguese government has passed a law that will regulate DE in the country. This new law will open the possibility for other IHEs to provide DE courses that lead to a degree.

Ukrainian students reported a high level of confidence in operating technological devices. The reason for this may be, in part, because of state educational requirements. Since the end of the 1990s, all Ukrainian students in secondary schools have at least one computer course as a mandatory element of their curriculum. This course covers a wide range of issues, which vary from information society theory to applied aspects of computer usage. Among the seven learning goals of this course three address digital literacy (Ministry of Education and Science of Ukraine, 2017 ). Ukrainian students who responded to the survey have taken computer courses for at least 5 years.

In the UAE, most DE courses and programs are not accredited by the Ministry of Education (United Arab Emirates Ministry of Education, 2016 ), which may account for UAE students lack of experience and their inability to judge this type of instruction.

It is worth analyzing the reasons why students enrolled or would enroll in DE courses. The reasons for taking DE courses, such as time management issues, are supported by studies concerning self-regulation and higher retention rates (Bradley, Browne, & Kelley, 2017 ; Peck, Stefaniak, & Shah, 2018 ). Students’ interest in having more control of their study time is also mentioned as one of the primary benefits of DE (Alahmari, 2017 ; Lei & Gupta, 2010 ). Regarding the reasons for not enrolling in DE courses, participants from the three countries mentioned difficulty contacting instructors and peers. Also, more than half of the students in Portugal and the UAE indicated they preferred face-to-face classes. Most students have spent their entire academic lives in traditional classes where interaction and immediate feedback from instructors and peers are more common. These concerns may be why students perceive they would lose a familiar type of interaction and have to engage with classroom participants in a new and different way (Carver & Kosloski Jr., 2015 ; Morris & Clark, 2018 ; Robinson & Hullinger, 2008 ; Summers, Waigandt, & Whittaker, 2005 ). It should be noted that the Portuguese and UAE students were enrolled in teacher education programs and are training to be face-to-face teachers. They may not understand the potential of DE format and are not preparing or expecting to use DE in their professional careers.

Difficulty being motivated was another reason chosen by the participants of the three countries to not enroll in DE courses. The lack of experience in this type of educational format may help explain student lack of confidence with their ability to study and stay on task. This response contrasts with the reasons reported for enrolling in DE courses such as controlling their study time. On one hand, participants like the prospect of having the ability to manage their own time. On the other hand, they are concerned they may lack the discipline they need to be successful.

Although the literature indicates that access to technology, isolation and expense are reasons frequently cited as preventing students from enrolling in DE courses (Lei & Gupta, 2010 ; Venter, 2003 ; Zuhairi et al., 2006 ), these reasons were selected by a very small percentage of the participants of this study. Access and affordability of technology has rapidly increased over the last decade which may help explain this inconsistency. Students may understand that DE courses are now less expensive than traditional university courses (Piletic, 2018 ) and they do not cite this as a reason for not enrolling. Relatively few students indicated they would feel isolated. Since this generation is in constant communication using technology (Diário de Notícias, 2011 ) they may not associate DE learning with isolation. However, it is interesting to note that there was a greater concern for interacting with instructors and peers than isolation.

The Ukrainian students are the most receptive to enrolling in DE courses. This is consistent with their positive perception of this type of learning. In addition, the previous experience of half of the participants may influence their interest as well as encourage their peers’ receptivity. UAE students do not have much experience and fewer than half are open to enrolling in DE courses. This may be due to their lack of experience and other concerns previously mentioned. Only one third of the Portuguese participants indicated their interest in enrolling in DE courses. This is in contrast with almost two thirds saying they had a favorable or very favorable attitude. The reasons for this inconsistency are not evident.

In terms of preparation needed to take DE courses, technical concerns were less of an issue for the participants of all three countries than skills and behaviors. Most participants’ answers focused on student skills including computer, English language and time management. Behaviors such as developing a study plan, having learning goals and objectives and being more motivated were also mentioned. The perceived need for better English language skills was expressed by about one third of the participants, none of whom have English as their native language. English speaking countries have been dominant in DE making English the most commonly used language in online learning (Sadykova & Dautermann, 2009 ). Regarding time management, half of the Ukrainian students expressed their need for improvement in contrast to approximately one third of the participants from the other countries. The difference among responses may be because the Ukrainian students are more self-reflective, or the others are more disciplined. Although both DE and face-to-face courses have deadlines for tasks and assessments, in the face-to-face courses, students meet in person with their instructors who may support and press them to do their work. Lack of in person contact may account for the participants feeling they need to improve these skills when taking DE courses (De Paepe et al., 2018 ). Students expressed concerns about lacking certain skills and having certain behaviors that would lead them to be reluctant to enroll in DE courses. The need for help and preparation are some of the concerns that participants reported. Perceived needs may account for the students’ apprehensions regarding taking DE courses. To promote this type of instruction, IHEs could address students’ concerns (Mahlangu, 2018 ).

Open schedule and blended learning courses were the two preferred formats stated by the participants. The reason that Open schedule is the most popular may be that it provides more freedom than other types of courses. Blended learning offers the familiar face-to-face instruction and some of the conveniences of DE which may be why participants are interested in this model.

Studies regarding the use of MOOCs in all three countries have been conducted indicating that researchers in these locations are aware that this course format is of potential interest to local students (Eppard & Reddy, 2017 ; Gallacher, 2014 ; Gonçalves, Chumbo, Torres, & Gonçalves, 2016 ; Sharov, Liapunova, & Sharova, 2019 ; Strutynska & Umryk, 2016 ). Ukrainian students selected MOOCs much more than students in the other countries. The reason for this may be that these students are more knowledgeable about MOOCs, because this type of course is usually at no cost and/or offered by prestigious IHEs (Cormier et al., 2010 ). However, this study did not ask why students were interested in MOOCs or other types of DE courses.

Limitations and future research

While this study offers useful information regarding undergraduate students’ perception and receptivity in taking DE courses, it has limited generalizability because of the size of the sample and the type of statistical analysis performed. Participants from two of the countries were enrolled in teacher education programs and were primarily female, thus future studies would benefit from including more students in diverse programs and a more equitable gender distribution.

Since many IHEs also offer programs for graduate students it would be useful to survey these students about their opinion and availability to enroll in DE courses. This would provide additional information for IHEs that are interested in developing DE programs.

There were some inconsistencies in the students’ responses such as Portuguese students’ interest in enrolling in DE courses not matching their favorable/ very favorable attitude towards DE. It would be helpful to conduct future research regarding this and other inconsistencies.

A study is currently being planned to collect data that will provide a larger and more diverse sample and include additional IHEs. This future research will potentially increase the available knowledge on how to provide DE for a greater number of students.

Conclusion and recommendations

Further development of DE courses and programs at IHEs in countries such as Portugal, UAE and Ukraine have good prospects. The students’ primary concerns regarding taking DE courses were similar among the three countries. These concerns included time management, motivation, and English language skills. However, this did not totally diminish participants interest in taking online courses especially for the Ukrainian students.

Based on this research, there are some obstacles that can be addressed to support the expansion of DE in the three countries that were studied and in other countries. The following recommendations may assist IHEs in promoting DE.

Recommendations for preparation within IHEs

IHEs can take proactive steps to prepare DE offerings, however, a one-size fit all model may not be appropriate for all countries and IHEs. Each institution needs to develop their own plan that meets the needs of their students and faculty. Data from this pilot study and the literature (Elbaum, McIntyre, & Smith, 2002 ; Hashim & Tasir, 2014 ; Hux et al., 2018 ) suggest that following steps might be taken:

Assess readiness to take DE courses through a survey and have students speak with counselors.

Provide pre-DE courses to build skills and behaviors based on students’ concerns.

Train instructors to develop and deliver DE courses that help to overcome obstacles such as motivation and time management.

Offer courses in a blended learning format to familiarize students with online learning which may provide a transitional model.

Recommendations for IHE outreach

This study shows that there is some student interest in enrolling in online courses. It is not sufficient for IHEs to make changes internally within their own institution. IHEs need to develop external strategies and actions that help advance the development of DE:

Promote DE in social media to target potential students and encourage them to take courses.

Urge government agencies to accredit DE courses and programs.

This pilot study provides some background information that may help IHEs to offer DE courses. Additional research about students’ preferences and needs regarding DE should be conducted. The sample size, IHEs included and participating countries could be expanded in order to gain a greater understanding.

Different cultural characteristics need to be taken into account in the development of online courses and programs. DE is being increasingly included by IHEs all around the world. To stay current, universities will need to find ways to offer DE to their current and prospective students.

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Patricia Fidalgo

Educational Technology Division, Lesley University, Cambridge, MA, USA

Joan Thormann

Philosophy Department, Oles Honchar Dnipro National University, Dnipropetrovs’ka oblast, Ukraine

Oleksandr Kulyk

Department of Curricular Studies and Educational Technology, University of Minho, Braga, Portugal

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Patricia Fidalgo: design of the work, data collection, analysis, interpretation of data, and draft of the work. Joan Thormann: design of the work, analysis, interpretation of data, and draft of the work. Oleksandr Kulyk: data collection, interpretation of data, and draft of the work. José Alberto Lencastre: data collection. The author(s) read and approved the final manuscript.

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Online Survey Questions

1. If the students have taken any distance education courses previously and if yes, how many;

2. What are the students’ perceptions of distance education;

3. What are the reasons students would enroll in distance education courses;

4. What are the reasons students would not enroll in a distance education course;

5. What preparation do students feel they need before taking distance education courses;

6. What is the level of students’ interest towards enrolling in distance education courses;

7. What types of distance education would students be interested in trying;

8. What is the students’ age;

9. What is the students’ gender;

10. How confident do students feel using a computer and the Internet.

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Fidalgo, P., Thormann, J., Kulyk, O. et al. Students’ perceptions on distance education: A multinational study. Int J Educ Technol High Educ 17 , 18 (2020). https://doi.org/10.1186/s41239-020-00194-2

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• Distance education
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Analysing lecturers’ perceptions on traditional vs. distance learning: A conceptual study of emergency transferring to distance learning during COVID-19 pandemic

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In recent years, and also due to the COVID-19 pandemic, education institutions worldwide have changed their education paradigm from a traditional to an online system. These institutions have rapidly accomplished their educational programs and activities by supporting various web applications, allowing the completion of the education process remotely. This motivated us to investigate the general perceptions of the faculty members who are teaching different courses for undergraduate students using the distance education system. The proposed technique is based on the use of advanced analysis methods to test the hypothesis of instructors’ perceptions of online teaching effectiveness, compared with traditional teaching, will not be affected by the following eight factors, including gender, academic major, age, academic degree, country of teaching, teaching experience in traditional classes, teaching experience in virtual classes (VCs), and whether or not the department/faculty provided e-learning courses before the COVID-19 pandemic. A total of 187 lecturers from 71 departments in 24 educational institutions located in 11 countries participated in this research. Results indicate that the perceptions of instructors regarding the online teaching system generally do not change based on the studied factors. Furthermore, the quantitative analyses illustrate that no significant differences exist in all dimension scales in terms of gender, major specification, age, country of teaching, and virtual experience. Significant differences are found in the dimension scale of distance education effectiveness in terms of academic degree and the educator status in terms of supporting VCs and traditional experience dimension scales. Additionally, the study provides various recommendations, including that the departments should encourage instructors to positively adapt with online teaching by developing the required skills and knowledge. Moreover, departments and institutions should support the teaching staff with specialized education tools. In addition, instructors should strive to decrease the communication and interaction gap between distance education and traditional in-class teaching.

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1 Introduction

Distance learning has been used before the emergence of personal computers and the Internet, but the spread of personal computers and the availability of the Internet have contributed significantly to the wide reach of distance learning Uhlig ( 2002 ). Online learning has rapidly grown, especially in the last decade Willett et al. ( 2019 ). This growth entails the merging of online learning into educational systems as part of the formal educational process Al-Shboul ( 2013 ) and Nelson ( 2003 ).

Recently, a new type of coronavirus, called COVID-19, surfaced in China, and initial reports of its spread began in mid-December 2019 in Wuhan City [1]. Since then, cases of COVID-19 infections have increased rapidly worldwide, causing massive death rates. Consequently, this has led to the implementation of strict measures by national governments to prevent its spread, including the isolation of cities, travel restrictions from one city to another, and the closure of airports, malls, restaurants, shops, and educational facilities. The pandemic has also significantly affected many research projects and studies Shambour and Gutub ( 2021 ). Nevertheless, education programs have continued in many countries without the need for physical meetings between lecturers and students through the provision of courses via remote platforms and virtual learning environments, such as Blackboard [2], Moodle [3], Webex [4], Canvas [5], and so on. The main challenge facing educators today is primarily how to effectively manage and deliver educational services and curricula to stakeholders, the education community, and the marketplace Okoye et al. ( 2021 ). Some educational institutions have faced many challenges in transferring the entire learning process from traditional to virtual classrooms, especially those who have no experience in providing online courses. However, online courses must maintain and enhance the teaching quality to ensure the educational performance of students Hsiao ( 2021 ).

Fundamentally, 187 university lecturers of various disciplines and teaching experiences participated in the current study. The perceptions of lecturers who used the traditional and online systems during their teaching processes were examined and analyzed on the basis of three scales: distance education effectiveness, distance education compared to traditional education, and educator status. This study mainly aims to explore the influences of several factors on teachers’ perspectives and explore the differences in lecturers’ views toward teaching courses in traditional and online systems.

The paper is organized as follows. Section 2 provides some related works for the traditional and online teaching paradigms. Section 3 presents the methodology. Section 4 discusses the data analysis and results. Finally, Sect. 5 concludes the paper and provides recommendations for future work.

2 Related literature

Several studies have discussed the effects of learning effectiveness in traditional and virtual classrooms. Some of them pointed out the benefits of effective learning through traditional classrooms (Arias et al., 2018 ;), some have praised the effectiveness of virtual classroom teaching (Liu, 2010 ; Narayan & Singh, 2020 ; Trakru & Jha, 2019 ), and others have recommended the use of a hybrid approach (Khatri et al., 2013 ). Lecturers play a crucial role in the learning process and they strive to deliver the knowledge to students, especially in remote teaching. Thus, teachers’ perceptions about distance education must be studied and identified to provide recommendations for the development and improvement of the quality of the educational process.

Furthermore many studies in literature have measured lecturers’ preferences and performances in online and traditional face-to-face learning systems, including Shachar and Neumann ( 2003 ), Bernard et al. ( 2004 ), Allen et al. ( 2002 ), Sitzmann et al. ( 2006 ), Hurlbut ( 2018 ), Yerby and Floyd ( 2013 ), Hannay and Newvine ( 2006 ), and Sibirskaya et al. ( 2019 ). Other studies discussed the advantages and disadvantages of using both systems, such as in Behzadi and Ghaffari ( 2011 ), Gowda and Suma ( 2017 ), and Lazou and Tsinakos ( 2019 ).

Saleh and Mrayan ( 2016 ) examined the Arab Open University in Jordan as a case study on faculty perceptions of online education programs. They examined the faculty’s perceived values of online learning effectiveness, the interaction between the teacher and student, the adequacy of the provided technology by the institute, the teaching techniques used, and the performances of students. They reported that the faculty members are generally satisfied with online education despite that they favored face-to-face and blended courses in teacher training programs.

To improve the distance education system, Gürer et al. ( 2016 ) examined the opinions of instructors who have experienced online teaching. They interviewed 12 instructors to produce some suggestions that can contribute to online learning enhancement. The study presents the positive and negative sides of online learning from the perspectives of the interviewed instructors. Meanwhile, Shreaves ( 2019 ) conducted a study on faculty perceptions of online teaching at the Pacific Lutheran University to highlight the factors that encourage and discourage online education application. The main goal of the study is to encourage and motivate the employment of online learning in Pacific Lutheran University. To provide a theoretical lens to examine the influence of attitudes, subjective norms, and perceived behavioral control, the decomposed theory of planned behavior (DTPB) is applied, and 50% of the respondents highlighted 17 factors that influence the decision on whether or not to teach online.

Samuel ( 2016 ) conducted a study on the “presence” or the false impression of being in an actual classroom within an online learning environment. The goal of that study was to investigate and examine how the faculties who applied online courses perceive and experience presence. In addition, many studies targeted instructors’ perceptions of best practices and quality outcomes Frazer et al. ( 2017 ), Plante and Asselin ( 2014 ), and Richardson et al. ( 2016 ). Frazer et al. ( 2017 ), for example, conducted a study on faculty perceptions of online teaching of nursing online education. The goal of their study was to characterize and express teaching effectiveness and quality indicators in an online environment, which did not require instructors and students to be online simultaneously. Eleven instructors were interviewed to achieve that goal. The study concluded by suggesting some useful practices that can support online education.

Meanwhile, a study that measured faculty members’ perceptual differences in terms of distance education was conducted by Ulmer et al. ( 2007 ). However, it did not consider actual learning outcomes and the quality of distance education as part of the measurement. The findings of the study indicated that some degree of distance education effectiveness might be helpful if it is considered by higher education culture. A literature exploration during the time period of 1995–2015 was conducted by Wingo et al. ( 2017 ) to investigate faculty perceptions related to online teaching. They analyzed 67 studies to achieve that goal. The investigation revealed issues encountered by the faculty encounters in online teaching, such as student success, required technical support, work load, and others. McKenzie ( 2019 ) conducted a phenomenological study, which investigated instructor/student interaction during online courses and discussed various types of interactions along with some interaction obstacles. That study provided instructors and program administrators with useful and detailed descriptions of state-of-the art techniques of instructor/student online interaction.

Previous studies have analyzed and discussed lecturers’ perception of online teaching and the effectiveness of online teaching in departments that used to support online teaching. In this study we aim to analyze and discuss lecturers’ perception of online teaching in terms of emergence transfer from traditional in-class teaching to online teaching caused by the COVID-19 pandemic. Moreover, study analyzed the effectiveness of sudden transfer from traditional in-class teaching to online teaching during the COVID-19 pandemic.

3 Methodology

The section presents the methodology used in this paper, starting from reviewing the literature, defining research hypothesis, defining the research instrument, data analysis and discussion, and reporting of the results as shown in Fig.  1 :

Research methodology

Reviewing the Literature

A descriptive literature review was conducted in which the related works, main goal, methods, and results were generally discussed briefly as in the previous section. The main focus of the literature review was directed toward studies that targeted the experience of faculty members related to distance education programmers.

Defining research hypothesis

An ANOVA statistical method, at alpha level of 0.05, is used to observe whether a significant difference exists between the results collected from lecturers’ perspectives of online teaching effectiveness compared with traditional teaching such that:

The null hypothesis (H1) states that instructors’ perception will not be affected by the factors of major, academic degree, country of teaching, age, teaching experience in traditional classes, teaching experience in virtual classes (VCs) and whether or not the department/faculty provided e-learning courses before the COVID-19 pandemic;

The alternative hypothesis (H2) rejects the null one.

Defining the research instrument

To study the lecturers’ point of view on distance learning effectiveness during COVID-19, a research instrument (questionnaire) adopted from Ulmer et al. ( 2007 ) was used to obtain lectures’ experiences and observations. The questionnaire comprises three scales, namely, distance education effectiveness, distance education compared to traditional education, and educator status. Each scale has a number of questions, as shown in Table 1 . The questionnaire was developed using a Likert-type scale with five-point responses ranging from 1 = strongly disagree to 5 = strongly agree.

Data analysis and discussion

Similar to the data analysis performed by Okoye et al. ( 2021 ), this study applied statistical inference-basis of theoretical distributions to analyze the collected data and explore the descriptive features using ANOVA statistical method that reveals the factors that cause differences in the mean between different groups and determines whether statistically significant differences exist between groups. These were then used to test the hypothesis to realize the relationships among different variables and explore the teaching effectiveness on the basis of instructors’ perceptions on practice teaching within the traditional and virtual online systems.

Reporting of the results

This is the final step wherein the results of the analyzed data are discussed and presented so that the findings can provide valuable insights to researchers with varying interests and expertise. The authors declare that they had obtained an ethical approval from the Department of Information and Scientific Services at the Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research, Umm Al-Qura University, Saudi Arabia.

4 Data analysis and results

4.1 demographic data.

The sample data were collected toward the end of the fall semester (May 27–31, 2020). A total of 187 lecturers were randomly selected to participate in this study, in which 70.9% were males and 29.1% were females, from 71 departments belonging to 24 educational institutions located in 11 countries.

The collected sample data were categorized to eight major factors: gender, participation based on general specialization, academic degree, country of teaching, age, teaching experience in traditional classes, teaching experience in VCs, and whether or not the department/faculty provided e-learning courses before the COVID-19 pandemic. The main idea behind these categorizations was to target the differences in opinions on the basis of different aspects.

Figure  2 shows the number of survey respondents in terms of general specialization. It also shows the percentage of participants in each category. Similar to a study conducted by Affouneh and Raba ( 2018 ), this study focuses several general specializations, including computer science and information technology (IT), medical/health sciences, social and human sciences, applied sciences, engineering sciences, and Sharia sciences. The majority of responses came from computer science and IT with 26% and medical/health sciences with 25% of the responses, respectively, which are in line with the results of Affouneh and Raba ( 2018 ).

Distribution of participants based on general specialization

Figure  3 provides the percentages of participants in terms of academic degree. Similar results were found in a study by Alshalawi ( 2019 ), which found that the majority of participants were associate professors (37%), followed by associate professors and lecturers (22% each). Moreover, the percentages of participants in terms of country of teaching are given in Fig.  4 , where the responses came from Jordan (48.1%), Saudi Arabia (31%), Palestine (10.7%), Egypt (3.2%), Oman (1.6%), Malaysia (1.6%), and others—Tunisia, United Arab Emirates, Australia, United Kingdom, and— Sudan(3.7%). Figure  5 shows the percentages of participants’ ages. The majority of participants were between 30–40 (32.6%) and 41–50 years (29.9%).

Distribution of participants based on academic degree

Distribution of participants based on participants’ country of teaching

Distribution of participants based on participants’ ages

A comparison between participants’ teaching experience in traditional and VCs is shown in Fig.  6 . The figure reveals that the majority of participants have higher experience in traditional classes compared with their experience in VCs in all experience years except for ‘less than a year.” The main reason behind this is the sudden decision made because of the COVID-19 pandemic wherein instructors are required to continue teaching their courses online.

Distribution of participants based on their teaching experiences in traditional and online classes

Figure  7 illustrates whether or not the department/faculty has provided e-learning courses before the COVID-19 pandemic. The answers showed that almost two-thirds of the responses were positive at 67.9%.

Department/college provides e-learning courses before the COVID-19 pandemic (yes, no)

4.2 Data analysis and discussion

ANOVA test was applied to evaluate the instructors’ perceptions of online teaching effectiveness compared to traditional teaching. Table 2 shows the ANOVA test results for instructors’ perceptions of online teaching effectiveness compared to traditional teaching in terms of gender.

The quantitative analyses show that the average response ratings did not exceed the neutrality on any of the dimensional measures across all eight factors. This indicates that instructors are unable to decide whether online teaching is more effective than traditional teaching. This uncertainty comes as a result of instructors’ experience in online teaching where 71.7% of participants have experience of less than a year, indicating that they start online teaching because of the COVID-19 pandemic taking into consideration that the survey was conducted in June 2020.

As shown in Table 2 , the P value in all dimension scales is greater than 0.05, indicating that no significant differences exist in instructors’ perceptions in terms of gender meaning that instructors’ perceptions of online teaching effectiveness—as compared to traditional teaching—do not contrast by instructors’ gender, which supports our hypothesis ( h 1 ) and in contrast to the results observed by Seok et al. ( 2010 ) who showed that female instructors have statistically significant higher perceptions than males regarding the effectiveness of the online course.

Moreover, the mean results in every dimension scale show that both gender responses are closer to neutral than disagree on distance education effectiveness and distance education vs. traditional education dimension scales, and closer to neutral than agreement for educator status dimension scale. This indicates that instructors are unable to decide whether online teaching is more effective than traditional teaching or not. In addition, instructors’ perceptions of variable 17 from the questionnaire show that instructors of both genders state that their efforts are well recognized and appreciated by the department /college /university.

Table 3 shows the ANOVA test results for instructors’ perception of online teaching effectiveness compared to traditional teaching in terms of major. As shown in Table 3 , the P value in all dimension scales is greater than 0.05, indicating that no significant differences exist in instructors’ perceptions in terms of major meaning that instructors’ perceptions of online teaching effectiveness—compared with traditional teaching—do not contrast by instructors’ major, which supports our hypothesis ( h 1 ). This is not in line with the findings observed by Alshangeeti et al. ( 2009 ), which found that a significant relationship exists between instructors’ professional specialization and their perceptions regarding the attributes of online teaching.

The results show that the mean instructors’ responses of the distance education effectiveness dimension scale are closer to neutral than disagree stating that, from instructors point of view, students’ skills, knowledge, and interactions with instructors from various majors are not improved by transferring to distance education. Moreover, the mean results of the distance education vs. traditional education dimension scale show that responses are closer to neutral than disagree for instructors in social and human sciences, computer science and IT, medical sciences/health, applied sciences, and engineering sciences majors, whereas instructors in Islamic sciences major and other majors are closer to neutral than agree. This concludes that instructors in Islamic sciences major have slightly more positive opinions toward transferring to online teaching.

Finally, the mean results of the educator status dimension scale show that the responses are closer to neutral than agree except those in the Islamic sciences major who are closer to agree than strongly agree. Meaning that instructors in the Islamic sciences major receive more positive encouragements toward adapting distance education than other majors.

Table 4 shows the ANOVA test results for instructors’ perceptions of online teaching effectiveness compared to traditional teaching in terms of age.

As shown in Table 4 , the P value in all dimension scales is greater than 0.05 indicating that no significant differences exist in instructors’ perceptions in terms of age meaning that instructors’ perceptions of online teaching effectiveness—compared with traditional teaching—do not contrast by instructors’ age, which supports our hypothesis ( h 1 ), which agreed with the results obtained by Alshangeeti et al. ( 2009 ).

Furthermore, based on the mean results of the distance education effectiveness dimension scale, responses in all ages are closer to neutral than disagree except ages that less than 30 and ages from 51 to 60, who are closer to neutral than agree and closer to disagree than neutral, respectively. This concludes that younger instructors perceive distance education more positively than elder instructors. Moreover, the mean results of the distance education vs. traditional dimension scale show that responses in all ages are closer to neutral than disagree except the ages that less than 30, who are closer to neutral than agree, indicating that younger instructors find distance education promising and full of potentials. Finally, the mean results of the educator status dimension scale show that responses in all ages are closer to neutral than agree except the ages that less than 30 and greater than 60, who are closer to agree than neutral, indicating that most younger and most elder instructors find distance education prestigious and obtain more positive encouragements toward moving to distance education than others.

Table 5 shows the ANOVA test results for instructors’ perceptions of online teaching effectiveness compared to traditional teaching in terms of country of teaching.

As shown in Table 5 , P values are greater than 0.05 for all dimension scales, indicating that no significant differences exist in instructors’ perceptions in terms of country of teaching meaning that instructors’ perceptions of online teaching effectiveness—compared with traditional teaching—do not contrast by instructors’ country of teaching, which supports our hypothesis ( h 1 ). These results are inconsistent with the results of Alenezi ( 2012 ) who stated that lecturer’s perceptions of e-learning were influenced by their nationality.

Furthermore, based on to the mean results of the distance education effectiveness dimension scale, responses from all countries are closer to neutral than disagree except responses from Egypt, Saudi Arabia, and Oman, which are closer to disagree than neutral. Meaning that instructors from Egypt, Saudi Arabia, and Oman favor conventional in-class teaching over online teaching. Moreover, the mean results of the distance to the traditional dimension scale show that responses from all countries are closer to neutral than disagree except responses from Palestine and others, which are closer to neutral than agree. This indicates that Palestinian instructors have slightly more positive opinions toward distance education. Finally, the mean results of educator status dimension scale show that responses from all countries are close to neutral, except those from Palestine, which are close to agree, indicating that Palestinian instructors obtain more encouragements toward moving to distance education.

Table 6 shows the ANOVA test results for instructors’ perceptions of online teaching effectiveness compared to traditional teaching in terms of degree/rank.

As shown in Table 6 , a significant difference is detected in instructors’ perceptions on the basis of academic degree for distance education effectiveness dimension scale, which contradict with the study’s hypothesis ( h 1 ). Meanwhile, the study’s hypothesis ( h 1 ) holds in the other two scales. This agreed with the results obtained by Alshangeeti et al. ( 2009 ), which reported that no evidence exists for any relationship between educational level and perceptions of online teaching attributes.

Moreover, based on to the mean results of the distance education effectiveness dimension scale, instructors’ opinions of associate professors, lecturers, and teaching assistants are closer to neutral than disagree, whereas the responses of professors and assistant professors are closer to disagree than neutral. These values indicate that professors and assistant professors favor conventional in-class teaching over online teaching. Furthermore, the mean results of the distance education vs. traditional dimension scale show that responses are closer to neutral than disagree except teaching assistants, who are closer to neutral than agree, indicating that lecturers have slightly more positive opinions toward distance education. Finally, the mean results of the educator status dimension scale show that the responses from all academic degrees are closer to neutral than agree except those from lecturers, which are closer to agree than neutral, indicating that lecturers are more motivated than other instructors.

Table 7 shows the ANOVA test results for instructors’ perceptions of online teaching effectiveness compared to traditional teaching in terms of supporting VCs.

As shown in Table 7 , a significant difference is detected in instructors’ perceptions on the basis of whether or not the departments used to support VCs for educator status dimension scale, which contradict with the study’s hypothesis (h1). Meanwhile, the study’s hypothesis (h1) holds in the other two scales.

Furthermore, based on the mean results of the distance education effectiveness dimension scale, the responses of participants in departments that support VCs are closer to neutral than disagree, whereas the responses of participants in departments that do not support VCs are closer to disagree than neutral. The responses indicate that instructors working in departments that suffer from lack of experience in VCs find traditional in-class teaching better than distance education. Moreover, the mean results of the distance education vs. traditional dimension scale show that participants’ responses are closer to neutral than disagree, indicating that participants from both are unable to decide which teaching mechanism is better. Meanwhile, the mean results of the educator status dimension scale show that participants’ responses are closer to neutral than agree, indicating that the instructors who work in departments used to support VCs think positively and enthusiastically toward online teaching.

Table 8 shows the ANOVA test results for instructors’ perceptions of online teaching effectiveness compared to traditional teaching in terms of traditional teaching experience.

As shown in Table 8 , a significant difference is detected in instructors’ perceptions based on traditional teaching experience for educator status dimension scale, which contradicts with the study’s hypothesis ( h 1 ). Meanwhile, the study’s hypothesis ( h 1 ) holds in the other two scales, which agreed with the results obtained by Alshangeeti et al. ( 2009 ).

Furthermore, regarding the mean results of the distance education effectiveness dimension scale, all participants’ responses are closer to neutral than disagree, except those with experience greater than 10 years, who are closer to disagree than neutral. This concludes that instructors with high experience in traditional teaching favor traditional teaching over online teaching. In addition, the mean results of the distance vs. traditional teaching dimension scale show that participants with traditional teaching experience of more than a year (92% of participants) are closer to neutral than disagree, whereas participants who have experience of less than a year (8% of participants) are closer to neutral than agree. Even though the responses are pointing toward undecided, instructors with less experience slightly tend to move from traditional teaching toward distance education. Finally, the mean results of the educator status dimension scale show that participants with traditional teaching experience of more than a year are closer to neutral than agree, whereas participants who have experience of less than a year are closer to agree than neutral, indicating that instructors with less experience find distance education prestigious and obtain more encouragements from the department toward moving to online teaching than others.

Table 9 shows the ANOVA test results for instructors’ perceptions of online teaching effectiveness compared to traditional teaching in terms of virtual teaching experience.

As shown in Table 9 , P values are greater than 0.05 in all dimension scales, indicating that no significant differences exist in instructors’ perceptions in terms of virtual teaching experience meaning that instructors’ perceptions of online teaching effectiveness—compared with traditional teaching—do not contrast by instructors’ virtual teaching experience, which supports our hypothesis ( h 1 ) and contrasted with the results obtained by Ulmer et al. ( 2007 ).

Furthermore, based on the mean results of the distance education effectiveness dimension scale, responses from all participants are closer to neutral than disagree, except those with experience greater than 10 years, who are closer to disagree than neutral. Furthermore, instructors with more experience in VCs observe that students favor traditional in-class teaching over online teaching. Moreover, the mean results of the distance education vs. traditional education dimension scale show that all participants are closer to neutral than disagree, except those with experience of 6–10 years, who are closer to neutral than agree. Finally, the mean results of the educator status dimension scale show that the responses from all participants are closer to neutral than agree except those from participants with experiences of 6–10 years, which are closer to agree than neutral, indicating that instructors with more experience in VCs find distance education prestigious and obtain more positive encouragements toward moving to distance education than others.

Table 10 summarizes the P_value results for the five-dimension scales in all factors. In total, 12.5% of the P values’ results show significant differences for instructors’ perceptions of online teaching effectiveness compared with traditional in-class teaching (highlighted in bold), whereas 87.5% of P values’ results do not show any significant differences.

5 Conclusion and future works

This study explores the perceptions of instructors on distance learning during the COVID-19 pandemic. 3D scales, namely, distance education effectiveness, distance education compared to traditional education, and educator status, are applied to analyze data on the perceptions of 187 instructors from various universities and academic degrees. The study explored the effects of eight factors on the instructors’ perspectives, including major specifications, academic degree, country of teaching, age, teaching experience in traditional classes, teaching experience in VCs, and whether or not the department/faculty provided e-learning courses before the COVID-19 pandemic.

However, the findings of studying the teaching effectiveness of instructors’ perceptions using traditional and virtual online teaching systems illustrate that no significant differences exist (87.5% of P values’ results for all factors) in all dimension scales in terms of gender, major specification, age, country of teaching, and virtual experience. In comparison, significant differences (12.5% of P values’ results for all factors) are found in the dimension scale of distance education effectiveness in terms of academic degree, the educator status of supporting VCs, and traditional experience. Moreover, the quantitative analyses show that the average response ratings did not exceed neutrality on any of the dimensional measures across all factors studied. Moreover, the dimension scale of educator status achieves the highest average score in all studied factors.

On the basis of the study, we find that: younger and less experience lecturers (less than a year) perceive distance education more positively and they are more motivated to transfer from traditional teaching to online teaching than other lecturers. Moreover, they feel that they receive more positive encouragements toward adapting distance education from their institutions than other lecturers. In addition, most of the participated lecturers feel that they are not motivated by their institutions to shift from traditional teaching to online teaching. Furthermore, lecturers and students lack awareness about the importance and advantages of distance education over traditional teaching.

On the basis of the findings, we recommend that: departments should strive toward encouraging and motivating teaching staff to transfer from traditional teaching to online teaching. Moreover, the departments must increase instructors’ and students’ awareness of online teaching importance and develop and improve their skills of how to utilize distance education.

Based on lecturer’s responses, the unexpected shift from traditional teaching to online teaching during COVID19 pandemic negatively affects teaching and learning effectiveness. This depletion of teaching and learning effectiveness are caused by several factors including; lack of lecturer’s experience in online teaching and lack of appropriate orientations and guidance for lecturers and students of online teaching importance, capabilities, and proper utilization.

Although the acceptance rate of online teaching is increasing especially among young and less experience lecturers, based on lecturer’s responses, the majority of lecturers tend to resist transfer from traditional teaching toward online teaching. Thus, it can be concluded that institutions that used to apply traditional teaching before the COVID-19 pandemic will return to normal traditional teaching after the pandemic.

Future studies should focus on exploring the effects of other factors, which influence the lecturers’ perceptions, using data mining tools that can assist researchers from diverse interests and expertise in their works.

Abbreviations

Refers to a numeric quantity computed for sample statistics within the context of hypothesis testing

Refers to a value on the F distribution

Refers to the standard deviation

Coronavirus disease 2019

Virtual Classes

Decomposed Theory of Planned Behavior

Information Technology

Analysis of Variance

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Shambour, M.K.Y., Abu-Hashem, M.A. Analysing lecturers’ perceptions on traditional vs. distance learning: A conceptual study of emergency transferring to distance learning during COVID-19 pandemic. Educ Inf Technol 27 , 3225–3245 (2022). https://doi.org/10.1007/s10639-021-10719-5

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A comparative study regarding distance learning and the conventional face-to-face approach conducted problem-based learning tutorial during the COVID-19 pandemic

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Educational pedagogies were modified during the COVID-19 pandemic to minimise interruption to teaching. One approach has been the distance learning problem-based learning (PBL) tutorial utilising the online peer-to-peer platform. The aim of this study was to compare the performance of students using distance learning PBL tutorials using with that of students utilising the conventional face-to-face approach.

This retrospective study was conducted in a single academic institution. We compared two groups of fourth-year medical students from the same class: one group used distance learning (DL); the other, the face-to-face (FF) method. We used students’ baseline performance at the preceding block for one-to-one propensity score matching. Students utilising the PBL tutorial were given grades by their tutors according to a standardised scoring system encompassing five key areas (score range: 0–10). The main outcome was a student’s total score (i.e., the sum of the scores from the five key areas, ranging from 0 to 50).

We matched 62 students in each group. With four tutorials, there were 490 observations, with 245 in each group. The mean total score for the DL group was 37.5 ± 4.6, which was significantly lower than that of the FF group (39.0 ± 4.4, p  < 0.001). We noted that students in the DL group had a significantly lower scores for all five areas of proficiency: participation, communication, preparation, critical thinking and group skills.

Findings of this study revealed that the performance of students utilising the DL PBL tutorials was lower than that of students participating in the conventional FF approach. Further studies are needed to ascertain the underlying cause.

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During the first half of 2020, the world was challenged by the coronavirus pandemic on an unprecedented scale. In response, many people adopted the practice of social distancing, and schools suspended classes and activities. Medical students were devoid of opportunities to enter hospital premises because of tightened infection control measures. Educators adopted innovative measures to maintain learning opportunities for students who stayed at home [ 1 , 2 , 3 ]. Some of these measures, including online lectures or webinars, were in place before the COVID-19 outbreak [ 4 ]. Others were hastily put into place during the pandemic. Given its user-friendly design, online peer-to-peer platforms became extremely popular. Lectures, tutorials, skills demonstrations, and even bedside teaching for medical students can be conducted via this type of platform [ 5 , 6 ]. For example, at the University of Hong Kong Li Ka Shing Faculty of Medicine offered a FF PBL tutorial using online peer-to-peer platform software. To many, such adaptations served as a lifeline to continue medical education during the coronavirus outbreak. It was also envisaged that some of these educational adaptations would persist after the pandemic. How effective these adaptations have been and how they compare with the conventional teaching method should be evaluated. A study on surgical skills teaching reported that using Web-based DL was well-received by undergraduate students [ 6 ]. The aim of this study was to evaluate the proficiencies in five key areas of students who took PBL tutorials by DL, an adaptation during the COVID-19 pandemic, and to compare them with the proficiency levels of students who learned via the conventional FF method.

This was a retrospective study conducted in May 2020 at the Li Ka Shing Faculty of Medicine, University of Hong Kong; it was approved by the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (IRB reference number: UW 20–381). The subjects were medical students who were in their fourth year of their six-year medical curriculum. These students had been exposed to the PBL teaching approach since their first and second years and were familiar with the format. In their fourth year, students in this class were split into three groups, with each rotating through three Junior Clerkship (JC) rotation blocks-- Medicine, Surgery, and Multidisciplinary clerkship-- between November 2019 and April 2020. From February to May 2020, classes were suspended because of the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The conventional FF PBL in the Surgery block was replaced by DL, using the online peer-to-peer platform software ZOOM (Zoom Video Communications, San Jose, CA, USA). The tutors, content, group size, duration, and assessment criteria remained the same. All students from rotation one had participated in conventional PBL tutorials before the class suspension, whereas students from rotation three had engaged in DL (online) PBL exclusively after the outbreak.

Eight cases were presented for discussion in a total of four tutorials. We gave the paper-based case materials to students prior to the tutorials and encouraged pre-class preparation. The PBL scenarios included breast mass, neck swelling, rectal bleeding, abdominal distension, haematuria, acute retention of urine, abdominal pain in an adult patient and abdominal pain in a paediatric patient. Each tutorial lasted for two hours and was considered sufficient for students to go through two scenarios, discuss the relevant history and physical examination findings, decide on the suitable investigations, come up with working diagnosis and suggest the appropriate management. The group size was 11–12 students. Students were randomly allocated into groups; they remained in the same groups throughout the clerkship. Tutors were randomly assigned, and students had different tutors for the four tutorials. The scenarios were described over several pages and some leading questions were given. Students discussed approaches to the clinical problems and explored related issues. They addressed one or more learning objectives that were considered relevant. Tutors acted as facilitators and played minimal roles unless students strayed from a case. At the end of the session, tutors used a standardised form for evaluating the proficiency levels of students in five key areas: participation, communication, preparation, critical thinking and group skills. Tutors expected students to demonstrate adequate preparation on the applicable topic prior to each tutorial, active engagement in group discussions, adequate communication skills for expressing their viewpoints and raising relevant questions, the ability to manage controversies rationally, and attentiveness to other members without dominating the discussion. A score from 1 to 10 was given for each of these areas, with 10 being the highest. The total score represented the sum of the scores from all five key areas.

We compared the PBL performance of students in rotation three-- the DL group using the online platform – to that of students in rotation one, the conventional FF group; the latter functioned as the control group. We retrieved their PBL outcomes and overall assessments for the preceding Clinical Foundation Block (CFB), taken during the period August to October 2019, for baseline comparison. The CFB tutorials were all conducted using the conventional FF method; for these five PBL tutorials, students were assessed with the same evaluation form (scores ranging from 0 to 10). The overall assessment comprised the PBL assessment (20%), small group/bedside skills learning (60%), and a logbook (20%). Students in the FF group and DL groups were matched by propensity scores according to their performance (i.e., using PBL scores from the CFB). Matching was one to one, using the nearest neighbour method and tolerance of 0.5. Categorical variables were compared using the χ 2 test. Continuous variables were compared with the independent sample t -test. A p -value of < 0.05 was considered statistically significant. The statistical analysis was performed using IBM SPSS version 25 (IBM, USA).

There were 77 and 75 students in the FF and DL groups, respectively. After propensity score matching, 62 students remained in each group. Matching for the remaining 15 and 13 students in the FF and DL groups, respectively, were not possible; therefore, they were excluded. Twenty-nine tutors were involved. With four tutorials, there were a total of 496 observations (248 per group). However, there were three absentees in the FF and DL groups, respectively, resulting in 245 observations per group. Gender composition, age, ethnicity and overall assessments for the CFB of the two groups are shown in Table  1 , indicating comparability between the two groups. Their PBL performance in the preceding CFB was also comparable after propensity score matching (79.5 versus 79.9, p  = 0.737).

The PBL performance of the two groups during JC is shown in Table  2 . Students in the FF group scored significantly higher. The mean total score for the DL group was 37.5, which was significantly lower than the score for the FF group (39.0, p  < 0.001). Moreover, assessments regarding participation, communication, preparation, critical thinking and group skills were uniformly lower for the DL group compared to those for the control group.

A subgroup analysis was performed to evaluate the effect of different tutorials and tutors. Table  3 shows a comparison of students’ performance for the four different tutorials. The mean total score was higher for the four tutorials; the difference was only significant for the first and third tutorials. A comparison of the two groups was also performed for individual tutors. Of the 29 tutors involved, six were excluded because they taught students in either the FF or DL group exclusively. Among the remaining 23, eight (34.8%) rated the proficiencies of students in the FF group higher and two (8.7%) rated those of students in the DL group higher (Fig.  1 ). The difference was not significant for remaining 13 tutors (56.5%).

Mean PBL scores according to tutors

E-learning has been in place for some time [ 4 ]. Many have viewed it as the preferred mode of teaching for the future, as students are given more flexibility [ 7 , 8 ]. This type of learning has become indispensable during the COVID-19 pandemic when social contact is minimal. However, e-learning has certain limitations [ 9 ]. It is reasonable to believe that many educational adaptations adopted during the pandemic will persist. Indeed some of the novel ones may result in a better overall learning experience for students. Therefore, it is worthwhile to evaluate them.

PBL was first popularised at the McMaster University in Canada [ 10 , 11 ]. Contrary to traditional lecture-based teaching, PBL encourages active and student-directed learning. Students are trained in independent learning, teamwork, and communication skills [ 12 ]. Some have suggested that students who utilised PBL curricula have emerged as better problem solvers [ 13 ]. For a PBL tutorial group to be efficient, members’ initiation is crucial, with all striving to function as a productive members.

Findings of this study revealed that students using DL method performed at a significantly lower level than students learning via the conventional FF approach. One possible explanation was that students and tutors had to adapt a new way of conducting the PBL tutorial. Wilcha cited technical challenges like establishing a reliable internet connection, problems with hardware and software learning platforms, etc. as some of the weakness of online teaching in a systematic review [ 9 ]. However, the software was relatively user-friendly, and the format of the tutorials remained the same. The time needed for students and tutors to become familiar with the new ‘environment’ should have been minimal. Technical issues such as Internet connectivity and lag time did not seem to be major problems in this locality. The fact that lower performance was also observed at the third tutorial suggested there was more than a transitional issue.

Modern digital communication technology has allowed us to trump geographical barriers [ 14 , 15 ]. Online platforms provide opportunities to meet and discuss without being physically close to each other. However, this type of technology may not reproduce the same interpersonal distance as physical presence [ 16 ]. Students may feel distant and detached from the rest of the group despite being connected via the computer screen and audio. The perception of being an outsider may reduce one’s eagerness to participate and contribute. In this study, students were required to keep the audio and video on throughout the tutorials, but there were occasions in which students only revealed or unmuted themselves when they were prompted to do so. Most students participated in the PBL tutorials from their residences via video conferencing. The casual ambiance might have appeared ‘unreal’ for learning, requiring psychological adaptation. Students were also more prone to distractions from surrounding persons or events. Prior studies have shown that DL using online platforms is associated with reduced student engagement, reduced communication and poor motivation [ 17 , 18 , 19 ].

Tutors can be affected too. Although tutors played minimal roles in this study, apart from evaluating students, they might have been inclined to intervene when needed and prone to be distracted. Nevertheless, these are only postulations; further research is warranted. A survey should be conducted to ascertain the perceptions of students and tutors regarding online tutorials and ways to improve the overall learning and teaching experience.

There were several limitations to this study. There was no randomisation, and the comparison was subjected to bias. The chance of bias was minimised by matching student performance at baseline. The tutor effect was another confounding factor. Although we used a structured evaluation form with clear guidance regarding scoring, there was a possibility of variations among tutors, with some being more stringent than others. Tutors in this study were regularly involved in PBL teaching, but there was no prior training or standardisation in terms of scoring. For some tutors, there was little variation in scores between the five areas of proficiency, which indicated that the tutors were more inclined to give an overall impression of students’ performance. This situation limited the ability to single out specific areas. There were tutors (tutors 10, 11 and 24 in Fig. 1 ) that gave every students the same score. Again this reduced the sensitivity to detect a difference, if any, between the two groups. It was postulated that this was why a lower score was observed in the DL group in tutorial two and four but the difference was insignificant. Additionally, tutorials for the two groups were conducted at different times, and students in the DL group were learning during a pandemic, which was clearly a torment to some. Thus, the negative psychological impact on them might have affected their performance. Furthermore, some classes or bedside teachings were suspended at the time. It has had been a suggested that people working from home during the pandemic may be more prone to loneliness, and hence, decreased efficiency [ 20 ].

Innovative educational adaptations have been essential during the COVID-19 pandemic. However, further evaluation before permanent adoption is warranted. A direct transition from the conventional way of teaching into an online-based format may not have the same impact. This study showed that students who used DL PBL tutorials exhivited lower levels of proficiency in key area than students who utilised the conventional FF approach. Further studies are needed to ascertain the underlying cause.

Availability of data and materials

The datasets generated and / or analysed during the current study are available from the corresponding author on request.

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This study did not receive funding support.

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Department of Surgery, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, SAR, China

Chi-chung Foo & Kent-man Chu

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All authors contributed to the study conception and design. Chi-chung Foo: Conception of work, acquisition of data, data analysis, drafting of manuscript, final approval. Billy Cheung: Conception of work, acquisition of data, data analysis, final approval. Kent-man Chu:Conception of work, data analysis, final approval.

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Correspondence to Chi-chung Foo .

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This study was performed in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. It was reviewed by the Institutional review board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (reference no: UW 20–381) and was approved WITHOUT the need of informed consent.

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Additional file 1..

The standardised form for tutors to evaluate students’ proficiency levels was attached as supplementary material.

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Foo, Cc., Cheung, B. & Chu, Km. A comparative study regarding distance learning and the conventional face-to-face approach conducted problem-based learning tutorial during the COVID-19 pandemic. BMC Med Educ 21 , 141 (2021). https://doi.org/10.1186/s12909-021-02575-1

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Received : 25 November 2020

Accepted : 16 February 2021

Published : 03 March 2021

DOI : https://doi.org/10.1186/s12909-021-02575-1

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