research paper of distance learning

ORIGINAL RESEARCH article

Insights into students’ experiences and perceptions of remote learning methods: from the covid-19 pandemic to best practice for the future.

• 1 Minerva Schools at Keck Graduate Institute, San Francisco, CA, United States
• 2 Ronin Institute for Independent Scholarship, Montclair, NJ, United States
• 3 Department of Physics, University of Toronto, Toronto, ON, Canada

This spring, students across the globe transitioned from in-person classes to remote learning as a result of the COVID-19 pandemic. This unprecedented change to undergraduate education saw institutions adopting multiple online teaching modalities and instructional platforms. We sought to understand students’ experiences with and perspectives on those methods of remote instruction in order to inform pedagogical decisions during the current pandemic and in future development of online courses and virtual learning experiences. Our survey gathered quantitative and qualitative data regarding students’ experiences with synchronous and asynchronous methods of remote learning and specific pedagogical techniques associated with each. A total of 4,789 undergraduate participants representing institutions across 95 countries were recruited via Instagram. We find that most students prefer synchronous online classes, and students whose primary mode of remote instruction has been synchronous report being more engaged and motivated. Our qualitative data show that students miss the social aspects of learning on campus, and it is possible that synchronous learning helps to mitigate some feelings of isolation. Students whose synchronous classes include active-learning techniques (which are inherently more social) report significantly higher levels of engagement, motivation, enjoyment, and satisfaction with instruction. Respondents’ recommendations for changes emphasize increased engagement, interaction, and student participation. We conclude that active-learning methods, which are known to increase motivation, engagement, and learning in traditional classrooms, also have a positive impact in the remote-learning environment. Integrating these elements into online courses will improve the student experience.

Introduction

The COVID-19 pandemic has dramatically changed the demographics of online students. Previously, almost all students engaged in online learning elected the online format, starting with individual online courses in the mid-1990s through today’s robust online degree and certificate programs. These students prioritize convenience, flexibility and ability to work while studying and are older than traditional college age students ( Harris and Martin, 2012 ; Levitz, 2016 ). These students also find asynchronous elements of a course are more useful than synchronous elements ( Gillingham and Molinari, 2012 ). In contrast, students who chose to take courses in-person prioritize face-to-face instruction and connection with others and skew considerably younger ( Harris and Martin, 2012 ). This leaves open the question of whether students who prefer to learn in-person but are forced to learn remotely will prefer synchronous or asynchronous methods. One study of student preferences following a switch to remote learning during the COVID-19 pandemic indicates that students enjoy synchronous over asynchronous course elements and find them more effective ( Gillis and Krull, 2020 ). Now that millions of traditional in-person courses have transitioned online, our survey expands the data on student preferences and explores if those preferences align with pedagogical best practices.

An extensive body of research has explored what instructional methods improve student learning outcomes (Fink. 2013). Considerable evidence indicates that active-learning or student-centered approaches result in better learning outcomes than passive-learning or instructor-centered approaches, both in-person and online ( Freeman et al., 2014 ; Chen et al., 2018 ; Davis et al., 2018 ). Active-learning approaches include student activities or discussion in class, whereas passive-learning approaches emphasize extensive exposition by the instructor ( Freeman et al., 2014 ). Constructivist learning theories argue that students must be active participants in creating their own learning, and that listening to expert explanations is seldom sufficient to trigger the neurological changes necessary for learning ( Bostock, 1998 ; Zull, 2002 ). Some studies conclude that, while students learn more via active learning, they may report greater perceptions of their learning and greater enjoyment when passive approaches are used ( Deslauriers et al., 2019 ). We examine student perceptions of remote learning experiences in light of these previous findings.

In this study, we administered a survey focused on student perceptions of remote learning in late May 2020 through the social media account of @unjadedjade to a global population of English speaking undergraduate students representing institutions across 95 countries. We aim to explore how students were being taught, the relationship between pedagogical methods and student perceptions of their experience, and the reasons behind those perceptions. Here we present an initial analysis of the results and share our data set for further inquiry. We find that positive student perceptions correlate with synchronous courses that employ a variety of interactive pedagogical techniques, and that students overwhelmingly suggest behavioral and pedagogical changes that increase social engagement and interaction. We argue that these results support the importance of active learning in an online environment.

Materials and Methods

Participant pool.

Students were recruited through the Instagram account @unjadedjade. This social media platform, run by influencer Jade Bowler, focuses on education, effective study tips, ethical lifestyle, and promotes a positive mindset. For this reason, the audience is presumably academically inclined, and interested in self-improvement. The survey was posted to her account and received 10,563 responses within the first 36 h. Here we analyze the 4,789 of those responses that came from undergraduates. While we did not collect demographic or identifying information, we suspect that women are overrepresented in these data as followers of @unjadedjade are 80% women. A large minority of respondents were from the United Kingdom as Jade Bowler is a British influencer. Specifically, 43.3% of participants attend United Kingdom institutions, followed by 6.7% attending university in the Netherlands, 6.1% in Germany, 5.8% in the United States and 4.2% in Australia. Ninety additional countries are represented in these data (see Supplementary Figure 1 ).

Survey Design

The purpose of this survey is to learn about students’ instructional experiences following the transition to remote learning in the spring of 2020.

This survey was initially created for a student assignment for the undergraduate course Empirical Analysis at Minerva Schools at KGI. That version served as a robust pre-test and allowed for identification of the primary online platforms used, and the four primary modes of learning: synchronous (live) classes, recorded lectures and videos, uploaded or emailed materials, and chat-based communication. We did not adapt any open-ended questions based on the pre-test survey to avoid biasing the results and only corrected language in questions for clarity. We used these data along with an analysis of common practices in online learning to revise the survey. Our revised survey asked students to identify the synchronous and asynchronous pedagogical methods and platforms that they were using for remote learning. Pedagogical methods were drawn from literature assessing active and passive teaching strategies in North American institutions ( Fink, 2013 ; Chen et al., 2018 ; Davis et al., 2018 ). Open-ended questions asked students to describe why they preferred certain modes of learning and how they could improve their learning experience. Students also reported on their affective response to learning and participation using a Likert scale.

The revised survey also asked whether students had responded to the earlier survey. No significant differences were found between responses of those answering for the first and second times (data not shown). See Supplementary Appendix 1 for survey questions. Survey data was collected from 5/21/20 to 5/23/20.

Qualitative Coding

We applied a qualitative coding framework adapted from Gale et al. (2013) to analyze student responses to open-ended questions. Four researchers read several hundred responses and noted themes that surfaced. We then developed a list of themes inductively from the survey data and deductively from the literature on pedagogical practice ( Garrison et al., 1999 ; Zull, 2002 ; Fink, 2013 ; Freeman et al., 2014 ). The initial codebook was revised collaboratively based on feedback from researchers after coding 20–80 qualitative comments each. Before coding their assigned questions, alignment was examined through coding of 20 additional responses. Researchers aligned in identifying the same major themes. Discrepancies in terms identified were resolved through discussion. Researchers continued to meet weekly to discuss progress and alignment. The majority of responses were coded by a single researcher using the final codebook ( Supplementary Table 1 ). All responses to questions 3 (4,318 responses) and 8 (4,704 responses), and 2,512 of 4,776 responses to question 12 were analyzed. Valence was also indicated where necessary (i.e., positive or negative discussion of terms). This paper focuses on the most prevalent themes from our initial analysis of the qualitative responses. The corresponding author reviewed codes to ensure consistency and accuracy of reported data.

Statistical Analysis

The survey included two sets of Likert-scale questions, one consisting of a set of six statements about students’ perceptions of their experiences following the transition to remote learning ( Table 1 ). For each statement, students indicated their level of agreement with the statement on a five-point scale ranging from 1 (“Strongly Disagree”) to 5 (“Strongly Agree”). The second set asked the students to respond to the same set of statements, but about their retroactive perceptions of their experiences with in-person instruction before the transition to remote learning. This set was not the subject of our analysis but is present in the published survey results. To explore correlations among student responses, we used CrossCat analysis to calculate the probability of dependence between Likert-scale responses ( Mansinghka et al., 2016 ).

Table 1. Likert-scale questions.

Mean values are calculated based on the numerical scores associated with each response. Measures of statistical significance for comparisons between different subgroups of respondents were calculated using a two-sided Mann-Whitney U -test, and p -values reported here are based on this test statistic. We report effect sizes in pairwise comparisons using the common-language effect size, f , which is the probability that the response from a random sample from subgroup 1 is greater than the response from a random sample from subgroup 2. We also examined the effects of different modes of remote learning and technological platforms using ordinal logistic regression. With the exception of the mean values, all of these analyses treat Likert-scale responses as ordinal-scale, rather than interval-scale data.

Students Prefer Synchronous Class Sessions

Students were asked to identify their primary mode of learning given four categories of remote course design that emerged from the pilot survey and across literature on online teaching: live (synchronous) classes, recorded lectures and videos, emailed or uploaded materials, and chats and discussion forums. While 42.7% ( n = 2,045) students identified live classes as their primary mode of learning, 54.6% ( n = 2613) students preferred this mode ( Figure 1 ). Both recorded lectures and live classes were preferred over uploaded materials (6.22%, n = 298) and chat (3.36%, n = 161).

Figure 1. Actual (A) and preferred (B) primary modes of learning.

In addition to a preference for live classes, students whose primary mode was synchronous were more likely to enjoy the class, feel motivated and engaged, be satisfied with instruction and report higher levels of participation ( Table 2 and Supplementary Figure 2 ). Regardless of primary mode, over two-thirds of students reported they are often distracted during remote courses.

Table 2. The effect of synchronous vs. asynchronous primary modes of learning on student perceptions.

Variation in Pedagogical Techniques for Synchronous Classes Results in More Positive Perceptions of the Student Learning Experience

To survey the use of passive vs. active instructional methods, students reported the pedagogical techniques used in their live classes. Among the synchronous methods, we identify three different categories ( National Research Council, 2000 ; Freeman et al., 2014 ). Passive methods (P) include lectures, presentations, and explanation using diagrams, white boards and/or other media. These methods all rely on instructor delivery rather than student participation. Our next category represents active learning through primarily one-on-one interactions (A). The methods in this group are in-class assessment, question-and-answer (Q&A), and classroom chat. Group interactions (F) included classroom discussions and small-group activities. Given these categories, Mann-Whitney U pairwise comparisons between the 7 possible combinations and Likert scale responses about student experience showed that the use of a variety of methods resulted in higher ratings of experience vs. the use of a single method whether or not that single method was active or passive ( Table 3 ). Indeed, students whose classes used methods from each category (PAF) had higher ratings of enjoyment, motivation, and satisfaction with instruction than those who only chose any single method ( p < 0.0001) and also rated higher rates of participation and engagement compared to students whose only method was passive (P) or active through one-on-one interactions (A) ( p < 0.00001). Student ratings of distraction were not significantly different for any comparison. Given that sets of Likert responses often appeared significant together in these comparisons, we ran a CrossCat analysis to look at the probability of dependence across Likert responses. Responses have a high probability of dependence on each other, limiting what we can claim about any discrete response ( Supplementary Figure 3 ).

Table 3. Comparison of combinations of synchronous methods on student perceptions. Effect size (f).

Mann-Whitney U pairwise comparisons were also used to check if improvement in student experience was associated with the number of methods used vs. the variety of types of methods. For every comparison, we found that more methods resulted in higher scores on all Likert measures except distraction ( Table 4 ). Even comparison between four or fewer methods and greater than four methods resulted in a 59% chance that the latter enjoyed the courses more ( p < 0.00001) and 60% chance that they felt more motivated to learn ( p < 0.00001). Students who selected more than four methods ( n = 417) were also 65.1% ( p < 0.00001), 62.9% ( p < 0.00001) and 64.3% ( p < 0.00001) more satisfied with instruction, engaged, and actively participating, respectfully. Therefore, there was an overlap between how the number and variety of methods influenced students’ experiences. Since the number of techniques per category is 2–3, we cannot fully disentangle the effect of number vs. variety. Pairwise comparisons to look at subsets of data with 2–3 methods from a single group vs. 2–3 methods across groups controlled for this but had low sample numbers in most groups and resulted in no significant findings (data not shown). Therefore, from the data we have in our survey, there seems to be an interdependence between number and variety of methods on students’ learning experiences.

Table 4. Comparison of the number of synchronous methods on student perceptions. Effect size (f).

Variation in Asynchronous Pedagogical Techniques Results in More Positive Perceptions of the Student Learning Experience

Along with synchronous pedagogical methods, students reported the asynchronous methods that were used for their classes. We divided these methods into three main categories and conducted pairwise comparisons. Learning methods include video lectures, video content, and posted study materials. Interacting methods include discussion/chat forums, live office hours, and email Q&A with professors. Testing methods include assignments and exams. Our results again show the importance of variety in students’ perceptions ( Table 5 ). For example, compared to providing learning materials only, providing learning materials, interaction, and testing improved enjoyment ( f = 0.546, p < 0.001), motivation ( f = 0.553, p < 0.0001), satisfaction with instruction ( f = 0.596, p < 0.00001), engagement ( f = 0.572, p < 0.00001) and active participation ( f = 0.563, p < 0.00001) (row 6). Similarly, compared to just being interactive with conversations, the combination of all three methods improved five out of six indicators, except for distraction in class (row 11).

Table 5. Comparison of combinations of asynchronous methods on student perceptions. Effect size (f).

Ordinal logistic regression was used to assess the likelihood that the platforms students used predicted student perceptions ( Supplementary Table 2 ). Platform choices were based on the answers to open-ended questions in the pre-test survey. The synchronous and asynchronous methods used were consistently more predictive of Likert responses than the specific platforms. Likewise, distraction continued to be our outlier with no differences across methods or platforms.

Students Prefer In-Person and Synchronous Online Learning Largely Due to Social-Emotional Reasoning

As expected, 86.1% (4,123) of survey participants report a preference for in-person courses, while 13.9% (666) prefer online courses. When asked to explain the reasons for their preference, students who prefer in-person courses most often mention the importance of social interaction (693 mentions), engagement (639 mentions), and motivation (440 mentions). These students are also more likely to mention a preference for a fixed schedule (185 mentions) vs. a flexible schedule (2 mentions).

In addition to identifying social reasons for their preference for in-person learning, students’ suggestions for improvements in online learning focus primarily on increasing interaction and engagement, with 845 mentions of live classes, 685 mentions of interaction, 126 calls for increased participation and calls for changes related to these topics such as, “Smaller teaching groups for live sessions so that everyone is encouraged to talk as some people don’t say anything and don’t participate in group work,” and “Make it less of the professor reading the pdf that was given to us and more interaction.”

Students who prefer online learning primarily identify independence and flexibility (214 mentions) and reasons related to anxiety and discomfort in in-person settings (41 mentions). Anxiety was only mentioned 12 times in the much larger group that prefers in-person learning.

The preference for synchronous vs. asynchronous modes of learning follows similar trends ( Table 6 ). Students who prefer live classes mention engagement and interaction most often while those who prefer recorded lectures mention flexibility.

Table 6. Most prevalent themes for students based on their preferred mode of remote learning.

Student Perceptions Align With Research on Active Learning

The first, and most robust, conclusion is that incorporation of active-learning methods correlates with more positive student perceptions of affect and engagement. We can see this clearly in the substantial differences on a number of measures, where students whose classes used only passive-learning techniques reported lower levels of engagement, satisfaction, participation, and motivation when compared with students whose classes incorporated at least some active-learning elements. This result is consistent with prior research on the value of active learning ( Freeman et al., 2014 ).

Though research shows that student learning improves in active learning classes, on campus, student perceptions of their learning, enjoyment, and satisfaction with instruction are often lower in active-learning courses ( Deslauriers et al., 2019 ). Our finding that students rate enjoyment and satisfaction with instruction higher for active learning online suggests that the preference for passive lectures on campus relies on elements outside of the lecture itself. That might include the lecture hall environment, the social physical presence of peers, or normalization of passive lectures as the expected mode for on-campus classes. This implies that there may be more buy-in for active learning online vs. in-person.

A second result from our survey is that student perceptions of affect and engagement are associated with students experiencing a greater diversity of learning modalities. We see this in two different results. First, in addition to the fact that classes that include active learning outperform classes that rely solely on passive methods, we find that on all measures besides distraction, the highest student ratings are associated with a combination of active and passive methods. Second, we find that these higher scores are associated with classes that make use of a larger number of different methods.

This second result suggests that students benefit from classes that make use of multiple different techniques, possibly invoking a combination of passive and active methods. However, it is unclear from our data whether this effect is associated specifically with combining active and passive methods, or if it is associated simply with the use of multiple different methods, irrespective of whether those methods are active, passive, or some combination. The problem is that the number of methods used is confounded with the diversity of methods (e.g., it is impossible for a classroom using only one method to use both active and passive methods). In an attempt to address this question, we looked separately at the effect of number and diversity of methods while holding the other constant. Across a large number of such comparisons, we found few statistically significant differences, which may be a consequence of the fact that each comparison focused on a small subset of the data.

Thus, our data suggests that using a greater diversity of learning methods in the classroom may lead to better student outcomes. This is supported by research on student attention span which suggests varying delivery after 10–15 min to retain student’s attention ( Bradbury, 2016 ). It is likely that this is more relevant for online learning where students report high levels of distraction across methods, modalities, and platforms. Given that number and variety are key, and there are few passive learning methods, we can assume that some combination of methods that includes active learning improves student experience. However, it is not clear whether we should predict that this benefit would come simply from increasing the number of different methods used, or if there are benefits specific to combining particular methods. Disentangling these effects would be an interesting avenue for future research.

Students Value Social Presence in Remote Learning

Student responses across our open-ended survey questions show a striking difference in reasons for their preferences compared with traditional online learners who prefer flexibility ( Harris and Martin, 2012 ; Levitz, 2016 ). Students reasons for preferring in-person classes and synchronous remote classes emphasize the desire for social interaction and echo the research on the importance of social presence for learning in online courses.

Short et al. (1976) outlined Social Presence Theory in depicting students’ perceptions of each other as real in different means of telecommunications. These ideas translate directly to questions surrounding online education and pedagogy in regards to educational design in networked learning where connection across learners and instructors improves learning outcomes especially with “Human-Human interaction” ( Goodyear, 2002 , 2005 ; Tu, 2002 ). These ideas play heavily into asynchronous vs. synchronous learning, where Tu reports students having positive responses to both synchronous “real-time discussion in pleasantness, responsiveness and comfort with familiar topics” and real-time discussions edging out asynchronous computer-mediated communications in immediate replies and responsiveness. Tu’s research indicates that students perceive more interaction with synchronous mediums such as discussions because of immediacy which enhances social presence and support the use of active learning techniques ( Gunawardena, 1995 ; Tu, 2002 ). Thus, verbal immediacy and communities with face-to-face interactions, such as those in synchronous learning classrooms, lessen the psychological distance of communicators online and can simultaneously improve instructional satisfaction and reported learning ( Gunawardena and Zittle, 1997 ; Richardson and Swan, 2019 ; Shea et al., 2019 ). While synchronous learning may not be ideal for traditional online students and a subset of our participants, this research suggests that non-traditional online learners are more likely to appreciate the value of social presence.

Social presence also connects to the importance of social connections in learning. Too often, current systems of education emphasize course content in narrow ways that fail to embrace the full humanity of students and instructors ( Gay, 2000 ). With the COVID-19 pandemic leading to further social isolation for many students, the importance of social presence in courses, including live interactions that build social connections with classmates and with instructors, may be increased.

Limitations of These Data

Our undergraduate data consisted of 4,789 responses from 95 different countries, an unprecedented global scale for research on online learning. However, since respondents were followers of @unjadedjade who focuses on learning and wellness, these respondents may not represent the average student. Biases in survey responses are often limited by their recruitment techniques and our bias likely resulted in more robust and thoughtful responses to free-response questions and may have influenced the preference for synchronous classes. It is unlikely that it changed students reporting on remote learning pedagogical methods since those are out of student control.

Though we surveyed a global population, our design was rooted in literature assessing pedagogy in North American institutions. Therefore, our survey may not represent a global array of teaching practices.

This survey was sent out during the initial phase of emergency remote learning for most countries. This has two important implications. First, perceptions of remote learning may be clouded by complications of the pandemic which has increased social, mental, and financial stresses globally. Future research could disaggregate the impact of the pandemic from students’ learning experiences with a more detailed and holistic analysis of the impact of the pandemic on students.

Second, instructors, students and institutions were not able to fully prepare for effective remote education in terms of infrastructure, mentality, curriculum building, and pedagogy. Therefore, student experiences reflect this emergency transition. Single-modality courses may correlate with instructors who lacked the resources or time to learn or integrate more than one modality. Regardless, the main insights of this research align well with the science of teaching and learning and can be used to inform both education during future emergencies and course development for online programs that wish to attract traditional college students.

Global Student Voices Improve Our Understanding of the Experience of Emergency Remote Learning

Our survey shows that global student perspectives on remote learning agree with pedagogical best practices, breaking with the often-found negative reactions of students to these practices in traditional classrooms ( Shekhar et al., 2020 ). Our analysis of open-ended questions and preferences show that a majority of students prefer pedagogical approaches that promote both active learning and social interaction. These results can serve as a guide to instructors as they design online classes, especially for students whose first choice may be in-person learning. Indeed, with the near ubiquitous adoption of remote learning during the COVID-19 pandemic, remote learning may be the default for colleges during temporary emergencies. This has already been used at the K-12 level as snow days become virtual learning days ( Aspergren, 2020 ).

In addition to informing pedagogical decisions, the results of this survey can be used to inform future research. Although we survey a global population, our recruitment method selected for students who are English speakers, likely majority female, and have an interest in self-improvement. Repeating this study with a more diverse and representative sample of university students could improve the generalizability of our findings. While the use of a variety of pedagogical methods is better than a single method, more research is needed to determine what the optimal combinations and implementations are for courses in different disciplines. Though we identified social presence as the major trend in student responses, the over 12,000 open-ended responses from students could be analyzed in greater detail to gain a more nuanced understanding of student preferences and suggestions for improvement. Likewise, outliers could shed light on the diversity of student perspectives that we may encounter in our own classrooms. Beyond this, our findings can inform research that collects demographic data and/or measures learning outcomes to understand the impact of remote learning on different populations.

Importantly, this paper focuses on a subset of responses from the full data set which includes 10,563 students from secondary school, undergraduate, graduate, or professional school and additional questions about in-person learning. Our full data set is available here for anyone to download for continued exploration: https://dataverse.harvard.edu/dataset.xhtml?persistentId= doi: 10.7910/DVN/2TGOPH .

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

GS: project lead, survey design, qualitative coding, writing, review, and editing. TN: data analysis, writing, review, and editing. CN and PB: qualitative coding. JW: data analysis, writing, and editing. CS: writing, review, and editing. EV and KL: original survey design and qualitative coding. PP: data analysis. JB: original survey design and survey distribution. HH: data analysis. MP: writing. All authors contributed to the article and approved the submitted version.

Conflict of Interest

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

Acknowledgments

We want to thank Minerva Schools at KGI for providing funding for summer undergraduate research internships. We also want to thank Josh Fost and Christopher V. H.-H. Chen for discussion that helped shape this project.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2021.647986/full#supplementary-material

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Keywords : online learning, COVID-19, active learning, higher education, pedagogy, survey, international

Citation: Nguyen T, Netto CLM, Wilkins JF, Bröker P, Vargas EE, Sealfon CD, Puthipiroj P, Li KS, Bowler JE, Hinson HR, Pujar M and Stein GM (2021) Insights Into Students’ Experiences and Perceptions of Remote Learning Methods: From the COVID-19 Pandemic to Best Practice for the Future. Front. Educ. 6:647986. doi: 10.3389/feduc.2021.647986

Received: 30 December 2020; Accepted: 09 March 2021; Published: 09 April 2021.

Reviewed by:

Copyright © 2021 Nguyen, Netto, Wilkins, Bröker, Vargas, Sealfon, Puthipiroj, Li, Bowler, Hinson, Pujar and Stein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Geneva M. Stein, [email protected]

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

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Research Article

Distance learning in higher education during COVID-19: The role of basic psychological needs and intrinsic motivation for persistence and procrastination–a multi-country study

Roles Conceptualization, Methodology, Writing – original draft

* E-mail: [email protected]

Affiliation Department of Developmental and Educational Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria

Roles Conceptualization, Data curation, Methodology, Project administration, Writing – review & editing

Roles Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Roles Conceptualization, Methodology, Writing – review & editing

Roles Data curation, Writing – review & editing

Affiliation Department of Mathematics, Faculty of Mathematics, University of Vienna, Vienna, Austria

Roles Conceptualization, Funding acquisition, Methodology, Writing – review & editing

Roles Conceptualization, Funding acquisition, Methodology

Affiliation Department of Psychology, Faculty of Education, Aleksandër Moisiu University, Durrës, Albania

Affiliation Department of Educational Sciences, Faculty of Philology and Education, Bedër University, Tirana, Albania

Affiliation Xiangya School of Nursing, Central South University, Changsha, China

Affiliations Xiangya School of Nursing, Central South University, Changsha, China, Department of Nursing Science, University of Turku, Turku, Finland

Affiliation Study of Nursing, University of Applied Sciences Bjelovar, Bjelovar, Croatia

Affiliation Baltic Film, Media and Arts School, Tallinn University, Tallinn, Estonia

Affiliation Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland

Affiliation Department of Psychology, University of Bonn, Bonn, Germany

Affiliation Chair of Educational Psychology, Technische Universität Berlin, Berlin, Germany

Affiliation Department of Educational Studies, University of Potsdam, Potsdam, Germany

Affiliation Faculty of Education, University of Akureyri, Akureyri, Iceland

Affiliation Department of Global Education, Tsuru University, Tsuru, Japan

Affiliation Career Center, Osaka University, Osaka University, Suita, Japan

Affiliation Graduate School of Education, Osaka Kyoiku University, Kashiwara, Japan

Affiliation Department of Psychology, Faculty of Philosophy, University of Prishtina ’Hasan Prishtina’, Pristina, Kosovo

Affiliation Department of Social Work, Faculty of Philosophy, University of Pristina ’Hasan Prishtina’, Pristina, Kosovo

Affiliation Department of Psychology, Faculty of Social Sciences and Humanities, Klaipėda University, Klaipėda, Lithuania

Affiliation Geography Department, Junior College, University of Malta, Msida, Malta

Affiliation Institute of Family Studies, Faculty of Philosophy, Ss. Cyril and Methodius University in Skopje, Skopje, North Macedonia

Affiliation Institute of Psychology, Faculty of Social Science, University of Gdańsk, Gdańsk, Poland

Affiliation Faculty of Historical and Pedagogical Sciences, University of Wrocław, Wrocław, Poland

Affiliation Faculty of Educational Studies, Adam Mickiewicz University, Poznań, Poland

Affiliation CERNESIM Environmental Research Center, Alexandru Ioan Cuza University, Iași, România

Affiliation Social Sciences and Humanities Research Department, Institute for Interdisciplinary Research, Alexandru Ioan Cuza University of Iași, Iași, România

Affiliation Department of Informatics, Örebro University School of Business, Örebro University, Örebro, Sweden

Affiliation Faculty of Social Studies, Penn State University, State College, Pennsylvania, United States of America

•  [ ... ],

Affiliations Department of Developmental and Educational Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria, Department for Teacher Education, Centre for Teacher Education, University of Vienna, Vienna, Austria

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• Elisabeth R. Pelikan, 
• Selma Korlat, 
• Julia Reiter, 
• Julia Holzer, 
• Martin Mayerhofer, 
• Barbara Schober, 
• Christiane Spiel, 
• Oriola Hamzallari, 
• Ana Uka, 

• Published: October 6, 2021
• https://doi.org/10.1371/journal.pone.0257346
• Peer Review
• Reader Comments

Due to the COVID-19 pandemic, higher educational institutions worldwide switched to emergency distance learning in early 2020. The less structured environment of distance learning forced students to regulate their learning and motivation more independently. According to self-determination theory (SDT), satisfaction of the three basic psychological needs for autonomy, competence and social relatedness affects intrinsic motivation, which in turn relates to more active or passive learning behavior. As the social context plays a major role for basic need satisfaction, distance learning may impair basic need satisfaction and thus intrinsic motivation and learning behavior. The aim of this study was to investigate the relationship between basic need satisfaction and procrastination and persistence in the context of emergency distance learning during the COVID-19 pandemic in a cross-sectional study. We also investigated the mediating role of intrinsic motivation in this relationship. Furthermore, to test the universal importance of SDT for intrinsic motivation and learning behavior under these circumstances in different countries, we collected data in Europe, Asia and North America. A total of N = 15,462 participants from Albania, Austria, China, Croatia, Estonia, Finland, Germany, Iceland, Japan, Kosovo, Lithuania, Poland, Malta, North Macedonia, Romania, Sweden, and the US answered questions regarding perceived competence, autonomy, social relatedness, intrinsic motivation, procrastination, persistence, and sociodemographic background. Our results support SDT’s claim of universality regarding the relation between basic psychological need fulfilment, intrinsic motivation, procrastination, and persistence. However, whereas perceived competence had the highest direct effect on procrastination and persistence, social relatedness was mainly influential via intrinsic motivation.

Citation: Pelikan ER, Korlat S, Reiter J, Holzer J, Mayerhofer M, Schober B, et al. (2021) Distance learning in higher education during COVID-19: The role of basic psychological needs and intrinsic motivation for persistence and procrastination–a multi-country study. PLoS ONE 16(10): e0257346. https://doi.org/10.1371/journal.pone.0257346

Editor: Shah Md Atiqul Haq, Shahjalal University of Science and Technology, BANGLADESH

Received: March 30, 2021; Accepted: August 29, 2021; Published: October 6, 2021

Copyright: © 2021 Pelikan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data is now publicly available: Pelikan ER, Korlat S, Reiter J, Lüftenegger M. Distance Learning in Higher Education During COVID-19: Basic Psychological Needs and Intrinsic Motivation 2021. doi: 10.17605/OSF.IO/8CZX3 .

Funding: This work was funded by the Vienna Science and Technology Fund (WWTF) [ https://www.wwtf.at/ ] and the MEGA Bildungsstiftung [ https://www.megabildung.at/ ] through project COV20-025, as well as the Academy of Finland [ https://www.aka.fi ] through project 308351, 336138, and 345117. BS is the grant recipient of COV20-025. KSA is the grant recipient of 308351, 336138, and 345117. Open access funding was provided by University of Vienna. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

In early 2020, countries across the world faced rising COVID-19 infection rates, and various physical and social distancing measures to contain the spread of the virus were adopted, including curfews and closures of businesses, schools, and universities. By the end of April 2020, roughly 1.3 billion learners were affected by the closure of educational institutions [ 1 ]. At universities, instruction was urgently switched to distance learning, bearing challenges for all actors involved, particularly for students [ 2 ]. Moreover, since distance teaching requires ample preparation time and situation-specific didactic adaptation to be successful, previously established concepts for and research findings on distance learning cannot be applied undifferentiated to the emergency distance learning situation at hand [ 3 ].

Generally, it has been shown that the less structured learning environment in distance learning requires students to regulate their learning and motivation more independently [ 4 ]. In distance learning in particular, high intrinsic motivation has proven to be decisive for learning success, whereas low intrinsic motivation may lead to maladaptive behavior like procrastination (delaying an intended course of action despite negative consequences) [ 5 , 6 ]. According to self-determination theory (SDT), satisfaction of the three basic psychological needs for autonomy, competence and social relatedness leads to higher intrinsic motivation [ 7 ], which in turn promotes adaptive patterns of learning behavior. On the other hand, dissatisfaction of these basic psychological needs can detrimentally affect intrinsic motivation. According to SDT, satisfaction of the basic psychological needs occurs in interaction with the social environment. The context in which learning takes place as well as the support of social interactions it encompasses play a major role for basic need satisfaction [ 7 , 8 ]. Distance learning, particularly when it occurs simultaneously with other physical and social distancing measures, may impair basic need satisfaction and, in consequence, intrinsic motivation and learning behavior.

The aim of this study was to investigate the relationship between basic need satisfaction and two important learning behaviors—procrastination (as a consequence of low or absent intrinsic motivation) and persistence (as the volitional implementation of motivation)—in the context of emergency distance learning during the COVID-19 pandemic. In line with SDT [ 7 ] and previous studies (e.g., [ 9 ]), we also investigated the mediating role of intrinsic motivation in this relationship. Furthermore, to test the universal importance of SDT for intrinsic motivation and learning behavior under these specific circumstances, we collected data in 17 countries in Europe, Asia, and North America.

The fundamental role of basic psychological needs for intrinsic motivation and learning behavior

SDT [ 7 ] provides a broad framework for understanding human motivation, proposing that the three basic psychological needs for autonomy, competence, and social relatedness must be satisfied for optimal functioning and intrinsic motivation. The need for autonomy refers to an internal perceived locus of control and a sense of agency. In an academic context, students who learn autonomously feel that they have an active choice in shaping their learning process. The need for competence refers to the feeling of being effective in one’s actions. In addition, students who perceive themselves as competent feel that they can successfully meet challenges and accomplish the tasks they are given. Finally, the need for social relatedness refers to feeling connected to and accepted by others. SDT proposes that the satisfaction of each of these three basic needs uniquely contributes to intrinsic motivation, a claim that has been proved in numerous studies and in various learning contexts. For example, Martinek and colleagues [ 10 ] found that autonomy satisfaction was positively whereas autonomy frustration was negatively related to intrinsic motivation in a sample of university students during COVID-19. The same held true for competence satisfaction and dissatisfaction. A recent study compared secondary school students who perceived themselves as highly competent in dealing with their school-related tasks during pandemic-induced distance learning to those who perceived themselves as low in competence [ 11 ]. Students with high perceived competence not only reported higher intrinsic motivation but also implemented more self-regulated learning strategies (such as goal setting, planning, time management and metacognitive strategies) and procrastinated less than students who perceived themselves as low in competence. Of the three basic psychological needs, the findings on the influence of social relatedness on intrinsic motivation have been most ambiguous. While in some studies, social relatedness enhanced intrinsic motivation (e.g., [ 12 ]), others could not establish a clear connection (e.g., [ 13 ]).

Intrinsic motivation, in turn, is regarded as particularly important for learning behavior and success (e.g., [ 6 , 14 ]). For example, students with higher intrinsic motivation tend to engage more in learning activities [ 9 , 15 ], show higher persistence [ 16 ] and procrastinate less [ 6 , 17 , 18 ]. Notably, intrinsic motivation is considered to be particularly important in distance learning, where students have to regulate their learning themselves. Distance-learning students not only have to consciously decide to engage in learning behavior but also persist despite manifold distractions and less external regulation [ 4 ].

Previous research also indicates that the satisfaction of each basic need uniquely contributes to the regulation of learning behavior [ 19 ]. Indeed, studies have shown a positive relationship between persistence and the three basic needs (autonomy [ 20 ]; competence [ 21 ]; social relatedness [ 22 ]). Furthermore, all three basic psychological needs have been found to be related to procrastination. In previous research with undergraduate students, autonomy-supportive teaching behavior was positively related to satisfaction of the needs for autonomy and competence, both of which led to less procrastination [ 23 ]. A qualitative study by Klingsieck and colleagues [ 18 ] supports the findings of previous studies on the relations of perceived competence and autonomy with procrastination, but additionally suggests a lack of social relatedness as a contributing factor to procrastination. Haghbin and colleagues [ 24 ] likewise found that people with low perceived competence avoided challenging tasks and procrastinated.

SDT has been applied in research across various contexts, including work (e.g., [ 25 ]), health (e.g., [ 26 ]), everyday life (e.g., [ 27 ]) and education (e.g., [ 15 , 28 ]). Moreover, the pivotal role of the three basic psychological needs for learning outcomes and functioning has been shown across multiple countries, including collectivistic as well as individualistic cultures (e.g., [ 29 , 30 ]), leading to the conclusion that satisfaction of the three basic needs is a fundamental and universal determinant of human motivation and consequently learning success [ 31 ].

Self-determination theory in a distance learning setting during COVID-19

As Chen and Jang [ 28 ] observed, SDT lends itself particularly well to investigating distance learning, as the three basic needs for autonomy, competence and social relatedness all relate to important aspects of distance learning. For example, distance learning usually offers students greater freedom in deciding where and when they want to learn [ 32 ]. This may provide students with a sense of agency over their learning, leading to increased perceived autonomy. At the same time, it requires students to regulate their motivation and learning more independently [ 4 ]. In the unique context of distance learning during COVID-19, it should be noted that students could not choose whether and to what extent to engage in distance learning, but had to comply with external stipulations, which in turn may have had a negative effect on perceived autonomy. Furthermore, distance learning may also influence perceived competence, as this is in part developed by receiving explicit or implicit feedback from teachers and peers [ 33 ]. Implicit feedback in particular may be harder to receive in a distance learning setting, where informal discussions and social cues are largely absent. The lack of face-to-face contact may also impede social relatedness between students and their peers as well as students and their teachers. Well-established communication practices are crucial for distance learning success (see [ 34 ] for an overview). However, providing a nurturing social context requires additional effort and guidance from teachers, which in turn necessitates sufficient skills and preparation on their part [ 34 , 35 ]. Moreover, the sudden switch to distance learning due to COVID-19 did not leave teachers and students time to gradually adjust to the new learning situation [ 36 ]. As intrinsic motivation is considered particularly relevant in the context of distance education [ 28 , 37 ], applying the SDT framework to the novel situation of pandemic-induced distance learning may lead to important insights that allow for informed recommendations for teachers and educational institutions about how to proceed in the context of continued distance teaching and learning.

In summary, the COVID-19 situation is a completely new environment, and basic need satisfaction during learning under pandemic-induced conditions has not been explored before. Considering that closures of educational institutions have affected billions of students worldwide and have been strongly debated in some countries, it seems particularly relevant to gain insights into which factors consistently influence conducive or maladaptive learning behavior in these circumstances in a wide range of countries and contextual settings.

Therefore, the overall goal of this study is to investigate the well-established relationship between the three basic needs for autonomy, competence, and social relatedness with intrinsic motivation in the new and specific situation of pandemic-induced distance learning. Firstly, we examine the relationship between each of the basic needs with intrinsic motivation. We expect that perceived satisfaction of the basic needs for autonomy (H1a), competence (H1b) and social relatedness (H1c) would be positively related to intrinsic motivation. In our second research question, we furthermore extend SDT’s predictions regarding two important aspects of learning behavior–procrastination (as a consequence of low or absent intrinsic motivation) and persistence (as the implementation of the volitional part of motivation) and hypothesize that each basic need will be positively related to persistence and negatively related to procrastination, both directly (procrastination: H2a –c; persistence: H3a –c) and mediated by intrinsic motivation (procrastination: H4a –c; persistence: H5a –c). We also proposed that perceived autonomy, competence, and social relatedness would have a direct negative relation with procrastination (H6a –c) and a direct positive relation with persistence (H7a –c). Finally, we investigate SDT’s claim of universality, and assume that the aforementioned relationships will emerge across countries we therefore expect a similar pattern of results in all observed countries (H8a –c). As previous studies have indicated that gender [ 4 , 17 , 38 ] and age [ 39 , 40 ]. May influence intrinsic motivation, persistence, and procrastination, we included participants’ gender and age as control variables.

Study design

Due to the circumstances, we opted for a cross-sectional study design across multiple countries, conducted as an online survey. We decided for an online-design due to the pandemic-related restrictions on physical contact with potential survey participants as well as due to the potential to reach a larger audience. As we were interested in the current situation in schools than in long-term development, and we were particularly interested in a large-scale section of the population in multiple countries, we decided on a cross-sectional design. In addition, a multi-country design is particularly interesting in a pandemic setting: During this global health crisis, educational institutions in all countries face the same challenge (to provide distance learning in a way that allows students to succeed) but do so within different frameworks depending on the specific measures each country has implemented. This provides a unique basis for comparing the effects of need fulfillment on students’ learning behavior cross-nationally, thus testing the universality of SDT.

Sample and procedure

The study was carried out across 17 countries, with central coordination taking place in Austria. It was approved and supported by the Austrian Federal Ministry of Education, Science and Research and conducted online. International cooperation partners were recruited from previously established research networks (e.g., European Family Support Network [COST Action 18123]; Transnational Collaboration on Bullying, Migration and Integration at School Level [COST Action 18115]; International Panel on Social), resulting in data collection in 16 countries (Albania, China, Croatia, Estonia, Finland, Germany, Iceland, Japan, Kosovo, Lithuania, Poland, Malta, North Macedonia, Romania, Sweden, USA) in addition to Austria. Data collection was carried out between April and August 2020. During this period, all participating countries were in some degree of pandemic-induced lockdown, which resulted in universities temporarily switching to distance learning. The online questionnaires were distributed among university students via online surveys by the research groups in each respective country. No restrictions were placed on participation other than being enrolled at a university in the sampling country. Participants were informed about the goals of the study, expected time it would take to fill out the questionnaire, voluntariness of participation and anonymity of the acquired data. All research partners ensured that all ethical and legal requirements related to data collection in their country context were met.

Only data from students who gave their written consent to participate, had reached the age of majority (18 or older) and filled out all questions regarding the study’s main variables were included in the analyses (for details on data cleaning rules and exclusion criteria, see [ 41 ]). Additional information on data collection in the various countries is provided in S1 Table in S1 File .

The overall sample of N = 15,462 students was predominantly female (71.7%, 27.4% male and 0.7% diverse) and ranged from 18 to 71 years, with the average participant age being 24.41 years ( SD = 6.93, Mdn = 22.00). Sample descriptives per country are presented in Table 1 .

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https://doi.org/10.1371/journal.pone.0257346.t001

The variables analyzed here were part of a more extensive questionnaire; the complete questionnaire, as well as the analysis code and the data set, can be found at OSF [ 42 ] In order to take the unique situation into account, existing scales were adapted to the current pandemic context (e.g., adding “In the current home-learning situation …”), and supplemented with a small number of newly developed items. Subsequently, the survey was revised based on expert judgements from our research group and piloted with cognitive interview testing. The items were sent to the research partners in English and translated separately by each respective research team either using the translation-back-translation method or by at least two native-speaking experts. Subsequently, any differences were discussed, and a consolidated version was established.

To assure the reliability of the scales, we analyzed them using alpha coefficients separately for each country (see S2–S18 Tables in S1 File ). All items were answered on a rating scale from 1 (= strongly agree) to 5 (= strongly disagree) and students were instructed to answer with regard to the current situation (distance learning during the COVID-19 lockdown). Analyses were conducted with recoded items so that higher values reflected higher agreement with the statements.

Perceived autonomy was measured with two newly constructed items (“Currently, I can define my own areas of focus in my studies” and “Currently, I can perform tasks in the way that best suits me”; average α = .78, ranging from .62 to .86).

Perceived competence was measured with three items, which were constructed based on the Work-related Basic Need Satisfaction Scale (W-BNS; [ 25 ]) and transferred to the learning context (“Currently, I am dealing well with the demands of my studies”, “Currently, I have no doubts about whether I am capable of doing well in my studies” and “Currently, I am managing to make progress in studying for university”; average α = .83, ranging from .74 to .91).

Perceived social relatedness was assessed with three items, based on the W-BNS [ 43 ], (“Currently, I feel connected with my fellow students”, “Currently, I feel supported by my fellow students”) and the German Basic Psychological Need Satisfaction and Frustration Scale [ 44 ]; “Currently, I feel connected with the people who are important to me (family, friends)”; average α = .73, ranging from .64 to .88).

Intrinsic motivation was measured with three items which were slightly adapted from the Scales for the Measurement of Motivational Regulation for Learning in University Students (SMR-LS; [ 45 ]; “Currently, doing work for university is really fun”, “Currently, I am really enjoying studying and doing work for university” and “Currently, I find studying for university really exciting”; average α = .91, ranging from .83 to .94).

Procrastination was measured with three items adapted from the Procrastination Questionnaire for Students (Prokrastinationsfragebogen für Studierende; PFS; [ 46 ]): “In the current home-learning situation, I postpone tasks until the last minute”, “In the current home-learning situation, I often do not manage to start a task when I set out to do so”, and “In the current home-learning situation, I only start working on a task when I really need to”; average α = .88, ranging from .74 to .91).

Persistence was measured with three items adapted from the EPOCH measure [ 47 ]: “In the current home-learning situation, I finish whatever task I begin”, “In the current home-learning situation, I keep at my tasks until I am done with them” and “In the current home-learning situation, once I make a plan to study, I stick to it”; average α = .81, ranging from .74 to .88).

Data analysis.

Data analyses were conducted using IBM SPSS version 26.0 and Mplus version 8.4. First, we tested for measurement invariance between countries prior to any substantial analyses. We conducted a multigroup confirmatory factor analysis (CFAs) for all scales individually to test for configural, metric, and scalar invariance [ 48 , 49 ] (see S19 Table in S1 File ). We used maximum likelihood parameter estimates with robust standard errors (MLR) to deal with the non-normality of the data. CFI and RMSEA were used as indicators for absolute goodness of model fit. In line with Hu and Bentler [ 50 ], the following cutoff scores were considered to reflect excellent and adequate fit to the data, respectively: (a) CFI > 0.95 and CFI > 0.90; (b) RMSEA < .06 and RMSEA < .08. Relative model fit was assessed by comparing BICs of the nested models, with smaller BIC values indicating a better trade-off between model fit and model complexity [ 51 ]. Configural invariance indicates a factor structure that is universally applicable to all subgroups in the analysis, metric invariance implies that participants across all groups attribute the same meaning to the latent constructs measured, and scalar invariance indicates that participants across groups attribute the same meaning to the levels of the individual items [ 51 ]. Consequently, the extent to which the results can be interpreted depends on the level of measurement invariance that can be established.

For the main analyses, three latent multiple group mediation models were computed, each including one of the basic psychological needs as a predictor, intrinsic motivation as the mediator and procrastination and persistence as the outcomes. These three models served to test the hypothesis that perceived autonomy, competence and social relatedness are related to levels of procrastination and persistence, both directly and mediated through intrinsic motivation. We used bootstrapping in order to provide analyses robust to non-normal distribution variations, specifying 5,000 bootstrap iterations [ 52 ]. Results were estimated using the maximum likelihood (ML) method. Bias-corrected bootstrap confidence intervals are reported.

Finally, in an exploratory step, we investigated the international applicability of the direct and mediated effects. To this end, an additional set of latent mediation models was computed where the path estimates were fixed in order to create an average model across all countries. This was prompted by the consistent patterns of results across countries we observed in the multigroup analyses. Model fit indices of these average models were compared to those of the multigroup models in order to establish the similarity of path coefficients between countries.

Statistical prerequisites

Table 2 provides overall descriptive statistics and correlations for all variables (see S2–S18 Tables in S1 File for descriptive statistics for the individual countries).

https://doi.org/10.1371/journal.pone.0257346.t002

Metric measurement variance, but not scalar measurement invariance could be established for a simple model including the three individual items and no inter-correlations between perceived competence, perceived social relatedness, intrinsic motivation, and procrastination. For these four variables, the metric invariance model had a good absolute fit, whereas the scalar model did not, due to too high RMSEA; moreover, the relative fit was best for the metric model compared to both the configural and scalar model (see S18 Table in S1 File ). Metric, but not scalar invariance could also be established for persistence after modelling residual correlations between items 1 and 2 and items 2 and 3 of the scale. This was necessary due to the similar wording of the items (see “Measures” section for item wordings). Consequently, the same residual correlations were incorporated into all mediation models.

Finally, as the perceived autonomy scale consisted of only two items, it had to be fitted in a model with a correlating factor in order to compute measurement invariance. Both perceived competence and perceived social relatedness were correlated with perceived autonomy ( r = .59** and r = .31**, respectively; see Table 2 ). Therefore, we fit two models combining perceived autonomy with each of these factors; in both cases, metric measurement invariance was established (see S19 Table in S1 File ).

In summary, these results suggest that the meaning of all constructs we aimed to measure was understood similarly by participants across different countries. Consequently, we were able to fit the same mediation model in all countries and compare the resulting path coefficients.

Both gender and age were statistically significantly correlated with perceived competence, perceived social relatedness, intrinsic motivation, procrastination, and persistence (see S20–S22 Tables in S1 File ).

Mediation analyses

Autonomy hypothesis..

We hypothesized that higher perceived autonomy would relate to less procrastination and more persistence, both directly and indirectly (mediated through intrinsic learning motivation). Indeed, perceived autonomy was related negatively to procrastination (H6a) in most countries. Confidence intervals did not include zero in 10 out of 17 countries, all effect estimates were negative and standardized effect estimates ranged from b stand = - .02 to -.46 (see Fig 1 ). Furthermore, perceived autonomy was directly positively related to persistence in most countries. Specifically, for the direct effect of perceived autonomy on persistence (H7a), all but one country (USA, b stand = -.02; p = .621; CI [-.13, .08]) exhibited distinctly positive effect estimates ranging from b stand = .18 to .72 and confidence intervals that did not include zero.

Countries are ordered by sample size from top (highest) to bottom (lowest).

https://doi.org/10.1371/journal.pone.0257346.g001

In terms of indirect effects of perceived autonomy on procrastination mediated by intrinsic motivation (H7a), confidence intervals did not include zero in 8 out of 17 countries and effect estimates were mostly negative, ranging from b stand = -.33 to .03. Indirect effects of perceived autonomy on persistence (mediated by intrinsic motivation; H5a) were distinctly positive and confidence intervals did not include zero in 12 out of 17 countries. The indirect effect estimates and confidence intervals for all remaining countries were consistently positive, with the standardized effect estimates ranging from b stand = .13 to .39, indicating a robust, positive mediated effect of autonomy on persistence. Fig 2 displays the unstandardized path coefficients and their two-sided 5% confidence intervals for the indirect effects of perceived autonomy on procrastination via intrinsic motivation (left) and of perceived autonomy on persistence via intrinsic motivation (right).

https://doi.org/10.1371/journal.pone.0257346.g002

Unstandardized and standardized path coefficients, standard errors, p-values and bias-corrected bootstrapped confidence intervals for the direct and indirect effects of perceived autonomy on procrastination and persistence for each country are provided in S23–S26 Tables in S1 File , respectively.

Competence hypothesis. Secondly, we hypothesized that higher perceived competence would relate to less procrastination and more persistence both directly and indirectly, mediated through intrinsic learning motivation. Direct effects on procrastination (H6b) were negative in most countries and confidence intervals did not include zero in 10 out of 17 countries (see Fig 3 ).

https://doi.org/10.1371/journal.pone.0257346.g003

Standardized effect estimates ranged from b stand = -.02 to -.60, with 10 out of 17 countries exhibiting at least a medium-sized effect. Correspondingly, effect estimates for the direct effects on persistence were positive everywhere except the USA and confidence intervals did not include zero in 14 out of 17 countries (see Fig 3 ). Standardized effect estimates ranged from b stand = -.05 to .64 with 14 out of 17 countries displaying an at least medium-sized positive effect.

The pattern of results for the indirect effects of perceived competence on procrastination mediated by learning motivation (H4b) is illustrated in Fig 4 : Effect estimates were negative with the exception of China and the USA. Confidence intervals did not include zero in 7 out of 17 countries. Standardized effect estimates range between b stand = .06 and -.46. Indirect effects of perceived competence on persistence were positive everywhere except for two countries and confidence intervals did not include zero in 7 out of 17 countries (see Fig 4 ). Standardized effect estimates varied between b stand = -.07 and .46 (see S23–S26 Tables in S1 File for unstandardized and standardized path coefficients).

https://doi.org/10.1371/journal.pone.0257346.g004

Social relatedness hypothesis.

Finally, we hypothesized that stronger perceived social relatedness would be both directly and indirectly (mediated through intrinsic learning motivation) related to less procrastination and more persistence. The pattern of results was more ambiguous here than for perceived autonomy and perceived competence. Direct effect estimates on procrastination (H6c) were negative in 12 countries; however, the confidence intervals included zero in 12 out of 17 countries (see Fig 5 ). Standardized effect estimates ranged from b stand = -.01 to b stand = .33. The direct relation between perceived social relatedness and persistence (H7c) yielded 14 negative and three positive effect estimates. Confidence intervals did not include zero in 7 out of 17 countries (see Fig 5 ), with standardized effect estimates ranging from b stand = -.01 to b stand = .31.

https://doi.org/10.1371/journal.pone.0257346.g005

In terms of indirect effects of perceived social relatedness being related to procrastination mediated by intrinsic motivation (H4c), the pattern of results was consistent: All effect estimates except those for the USA were clearly negative, and confidence intervals did not include zero in 15 out of 17 countries (see Fig 6 ). Standardized effect estimates ranged between b stand = .00 and b stand = -.46. Indirect paths of perceived social relatedness on persistence showed positive effect estimates and standardized effect estimates ranging from b stand = .00 to .44 and confidence intervals not including zero in 16 out of 17 countries (see Fig 6 ; see S23–S26 Tables in S1 File for unstandardized and standardized path coefficients).

https://doi.org/10.1371/journal.pone.0257346.g006

Meta-analytic approach

Due to the overall similarity of the results across many countries, we decided to compute, in an additional, exploratory step, the same models with path estimates fixed across countries. This resulted in three models with average path estimates across the entire sample. Standardized path coefficients for the direct and indirect effects of the basic psychological needs on procrastination and persistence are presented in S27 and S28 Tables in S1 File , respectively. We compared the model fits of these three average models to those of the multigroup mediation models: If the fit of the average model is better than that of the multigroup model, it indicates that the individual countries are similar enough to be combined into one model. The amount of explained variance per model, outcome variable and country are provided in S29 Table in S1 File for procrastination and S30 Table in S1 File for persistence.

Perceived autonomy.

Relative model fit was better for the perceived autonomy model with fixed paths (BIC = 432,707.89) compared to the multigroup model (BIC = 432,799.01). Absolute model fit was equally good in the multigroup model (RMSEA = 0.05, CFI = 0.98, TLI = 0.97) and in the fixed path model (RMSEA = 0.05, CFI = 0.97, TLI = 0.97). Consequently, the general model in Fig 7 describes the data from all 17 countries equally well. The average amount of explained variance, however, is slightly higher in the multigroup model, with 19.9% of the variance in procrastination and 33.7% of the variance in persistence explained, as compared to 18.3% and 27.6% in the fixed path model. The amount of variance explained increased substantially in some countries when fixing the paths: in the multigroup model, explained variance ranges from 2.2% to 44.4% for procrastination and from 0.9% to 69.9% for persistence, compared to 13.0% - 27.7% and 18.2% to 63.2% in the fixed path model. Notably, the amount of variance explained did not change much in the three countries with the largest samples, Austria, Sweden, and Finland; countries with much smaller samples and larger confidence intervals were more affected.

*** p = < .001.

https://doi.org/10.1371/journal.pone.0257346.g007

Overall, perceived autonomy had significant direct and indirect effects on both procrastination and persistence; higher perceived autonomy was related to less procrastination directly ( b unstand = -.27, SE = .02, p = < .001) and mediated by learning motivation ( b unstand = -.20, SE = .01, p = < .001) and to more persistence directly ( b unstand = .24, SE = .01, p = < .001) and mediated by learning motivation ( b unstand = .12, SE = .01, p = < .001). Direct effects for the autonomy model are shown in Fig 7 ; for the indirect effects see Table 3 .

https://doi.org/10.1371/journal.pone.0257346.t003

Effects of age and gender varied across countries (see S20 Table in S1 File ).

Perceived competence.

For the perceived competence model, relative fit decreased when fixing the path coefficient estimates (BIC = 465,830.44 to BIC = 466,020.70). The absolute fit indices were also better for the multigroup model (RMSEA = 0.05, CFI = 0.97, TLI = 0.96) than for the fixed path model (RMSEA = 0.06, CFI = 0.96, TLI = 0.96). Hence, multigroup modelling describes the data across all countries somewhat better than a fixed path model as depicted in Fig 8 . Correspondingly, the fixed path model explained less variance on average than did the multigroup model, with 23.2% instead of 24.3% of the variance in procrastination and 32.9% instead of 37.3% of the variance in persistence explained. Explained variance ranged from 1.0% to 51.9% for procrastination in the multigroup model, as compared to 13.9% - 34.4% in the fixed path model. The amount of variance in persistence explained ranged from 1.0% to 58.1% in the multigroup model and from 23.5% to 55.9% in the fixed path model (see S29 and S30 Tables in S1 File ).

https://doi.org/10.1371/journal.pone.0257346.g008

Overall, higher perceived competence was related to less procrastination ( b unstand = -.44, SE = .02, p = < .001) and to higher persistence ( b unstand = .32, SE = .01, p = < .001). These effects were partly mediated by intrinsic learning motivation ( b unstand = -.11, SE = .01, p = < .001, and b unstand = .07, SE = .01, p = < .001, respectively; see Table 3 ). Effects of gender and age varied between countries, see S21 Table in S1 File .

Perceived social relatedness.

Finally, the perceived social relatedness model with fixed paths had a relatively better model fit (BIC = 479,428.46) than the multigroup model (BIC = 479,604.61). Likewise, the absolute model fit was similar in the model with path coefficients fixed across countries (RMSEA = 0.05, CFI = 0.97, TLI = 0.96) and the multigroup model (RMSEA = 0.05, CFI = 0.97, TLI = 0.97). The multigroup model explained 17.6% of the variance in procrastination and 26.3% of the variance in persistence, as compared to 15.2% and 21.6%, respectively in the fixed path model. Explained variance for procrastination ranged between 0.5% and 48.1% in the multigroup model, and from 9.0% to 23.0% in the fixed path model. Similarly, the multigroup model explained between 1.0% and 56.5% of the variance in persistence across countries, while the fixed path model explained between 15.6% and 48.3% (see S29 and S30 Tables in S1 File ).

Hence, the fixed path model depicted in Fig 9 is well-suited for describing data across all 17 countries. Higher perceived social relatedness is related to less procrastination both directly ( b unstand = -.06, SE = .01, p = < .001) and indirectly through learning motivation ( b unstand = -.12, SE = .01, p = < .001). Likewise, it is related to higher persistence both directly ( b unstand = .07, SE = .01, p = < .001) and indirectly through learning motivation ( b unstand = .08, SE = .00, p = < .001; see Table 3 ). Effects of gender and age are shown in S22 Table in S1 File .

https://doi.org/10.1371/journal.pone.0257346.g009

The aim of this study was to extend current research on the association between the basic psychological needs for autonomy, competence, and social relatedness with intrinsic motivation and two important aspects of learning behavior—procrastination and persistence—in the new and unique situation of pandemic-induced distance learning. We also investigated SDT’s [ 7 ] postulate that the relation between basic psychological need satisfaction and active (persistence) as well as passive (procrastination) learning behavior is mediated by intrinsic motivation. To test the theory’s underlying claim of universality, we collected data from N = 15,462 students across 17 countries in Europe, Asia, and North America.

Confirming our hypothesis, we found that the three basic psychological needs were consistently and positively related to intrinsic motivation in all countries except for the USA (H1a - c). This consistent result is in line with self-determination theory [ 7 ] and other previous studies (e.g., 9), which have found that satisfaction of the three basic needs for autonomy, competence and social relatedness is related to higher intrinsic motivation. Notably, the association with intrinsic motivation was stronger for perceived autonomy and perceived competence than for perceived social relatedness. This also has been found in previous studies [ 4 , 9 , 28 ]. Pandemic-induced distance learning, where physical and subsequential social contact in all areas of life was severely constricted, might further exacerbate this discrepancy, as instructors may have not been able to establish adequate communication structures due to the rapid switch to distance learning [ 36 , 53 ]. As hypothesized, intrinsic motivation was in general negatively related to procrastination (H2a - c) and positively related to persistence (H3a - c), indicating that students who are intrinsically motivated are less prone to procrastination and more persistent when studying. This again underlines the importance of intrinsic motivation for adaptive learning behavior, even and particularly in a distance learning setting, where students are more prone to disengage from classes [ 34 ].

The mediating effect of intrinsic motivation on procrastination and persistence

Direct effects of the basic needs on the outcomes were consistently more ambiguous (with smaller effect estimates and larger confidence intervals, including zero in more countries) than indirect effects mediated by intrinsic motivation. This difference was particularly pronounced for perceived social relatedness, where a clear negative direct effect on procrastination (H6c) could be observed only in the three countries with the largest sample size (Austria, Sweden, Finland) and Romania, whereas the confidence interval in most countries included zero. Moreover, in Estonia there was even a clear positive effect. The unexpected effect in the Estonian sample may be attributed to the fact that this country collected data only from international exchange students. Since the lockdown in Estonia was declared only a few weeks after the start of the semester, international exchange students had only a very short period of time to establish contacts with fellow students on site. Accordingly, there was probably little integration into university structures and social contacts were maintained more on a personal level with contacts from the home country. Thus, such students’ fulfillment of this basic need might have required more time and effort, leading to higher procrastination and less persistence in learning.

A diametrically opposite pattern was observed for persistence (H7c), where some direct effects of social relatedness were unexpectedly negative or close to zero. We therefore conclude that evidence for a direct negative relationship between social relatedness and procrastination and a direct positive relationship between social relatedness and persistence is lacking. This could be due to the specificity of the COVID-19 situation and resulting lockdowns, in which maintaining social contact took students’ focus off learning. In line with SDT, however, indirect effects of perceived social relatedness on procrastination (H4c) and persistence (H5c) mediated via intrinsic motivation were much more visible and in the expected directions. We conclude that, while the direct relation between perceived social relatedness and procrastination is ambiguous, there is strong evidence that the relationship between social relatedness and the measured learning behaviors is mediated by intrinsic motivation. Our results strongly underscore SDT’s assumption that close social relations promote intrinsic motivation, which in turn has a positive effect on learning behavior (e.g., [ 6 , 14 ]). The effects for perceived competence exhibited a somewhat clearer and hypothesis-conforming pattern. All direct effects of perceived competence on procrastination (H6b) were in the expected negative direction, albeit with confidence intervals spanning zero in 7 out of 17 countries. Direct effects of perceived competence on persistence (H7b) were consistently positive with the exception of the USA, where we observed a very small and non-significant negative effect. Indirect effects of perceived competence on procrastination (H4b) and persistence (H5b) as mediated by intrinsic motivation were mostly consistent with our expectations as well. Considering this overall pattern of results, we conclude that there is strong evidence that perceived competence is negatively associated with procrastination and positively associated with persistence. Furthermore, our results also support SDT’s postulate that the relationship between perceived competence and the measured learning behaviors is mediated by intrinsic motivation.

It is notable that the estimated direct effects of perceived competence on procrastination and persistence were higher than the indirect effects in most countries we investigated. Although SDT proposes that perceived competence leads to higher intrinsic motivation, Deci and Ryan [ 8 ] also argue that it affects all types of motivation and regulation, including less autonomous forms such as introjected and identified motivation, indicating that if the need for competence is not satisfied, all types of motivation are negatively affected. This may result in a general amotivation and lack of action. In our study, we only investigated intrinsic motivation as a mediator. For future research, it might be advantageous to further differentiate between different types of externally and internally controlled behavior. Furthermore, perceived competence increases when tasks are experienced as optimally challenging [ 7 , 54 ]. However, in order for instructors to provide the optimal level of difficulty and support needed, frequent communication with students is essential. Considering that data collection for the present study took place at a time of great uncertainty, when many countries had only transitioned to distance learning a few weeks prior, it is reasonable to assume that both structural support as well as communication and feedback mechanisms had not yet matured to a degree that would favor individualized and competency-based work.

However, our findings corroborate those from earlier studies insofar as they underline the associations between perceived competence and positive learning behavior (e.g., [ 19 ]), that is, lower procrastination [ 18 ] and higher persistence (e.g., [ 21 ]), even in an exceptional situation like pandemic-induced distance learning.

Turning to perceived autonomy, although the confidence intervals for the direct effects of perceived autonomy on procrastination (H6a) did span zero in most countries with smaller sample sizes, all effect estimates indicated a negative relation with procrastination. We expected these relationships from previous studies [ 18 , 23 ]; however, the effect might have been even more pronounced in the relatively autonomous learning situation of distance learning, where students usually have increased autonomy in deciding when, where, and how to learn. While this bears the risk of procrastination, it also comes with the opportunity to consciously delay less pressing tasks in favor of other, more important or urgent tasks (also called strategic delay ) [ 5 ], resulting in lower procrastination. In future studies, it might be beneficial to differentiate between passive forms of procrastination and active strategic delay in order to obtain more detailed information on the mechanisms behind this relationship. Direct effects of autonomy on persistence (H7a) were consistently positive. Students who are free to choose their preferred time and place to study may engage more with their studies and therefore be more persistent.

Indirect effects of perceived autonomy on procrastination mediated by intrinsic motivation (H4a) were negative in all but two countries (China and the USA), which is generally consistent with our hypothesis and in line with previous research (e.g., [ 23 ]). Additionally, we found a positive indirect effect of autonomy on persistence (H5a), indicating that autonomy and intrinsic motivation play a crucial role in students’ persistence in a distance learning setting. Based on our results, we conclude that perceived autonomy is negatively related to procrastination and positively related to persistence, and that this relationship is mediated by intrinsic motivation. It is worth noting that, unlike with perceived competence, the direct and indirect effects of perceived autonomy on the outcomes procrastination and persistence were similarly strong, suggesting that perceived autonomy is important not only as a driver of intrinsic motivation but also at a more direct level. It is important to make the best possible use of the opportunity for greater autonomy that distance learning offers. However, autonomy is not to be equated with a lack of structure; instead, learners should be given the opportunity to make their own decisions within certain framework conditions.

The applicability of self-determination theory across countries

Overall, the results of our mediation analysis for the separate countries support the claim posited by SDT that basic need satisfaction is essential for intrinsic motivation and learning across different countries and settings. In an exploratory analysis, we tested a fixed path model including all countries at once, in order to test whether a simplified general model would yield a similar amount of explained variance. For perceived autonomy and social relatedness, the model fit increased, whereas for perceived competence it decreased slightly compared to the multigroup model. However, all fixed path models exhibited adequate model fit. Considering that the circumstances in which distance learning took place in different countries varied to some degree (see also Limitations), these findings are a strong indicator for the universality of SDT.

Study strengths and limitations

Although the current study has several strengths, including a large sample size and data from multiple countries, three limitations must be considered. First, it must be noted that sample sizes varied widely across the 17 countries in our study, with one country above 6,000 (Austria), two above 1,000 (Finland and Sweden) and the rest ranging between 104 and 905. Random sampling effects are more problematic in smaller samples; hence, this large variation weakens our ability to conduct cross-country comparisons. At the same time, small sample sizes weaken the interpretability of results within each country; thus, our results for Austria, Finland and Sweden are considerably more robust than for the remaining fourteen countries. Additionally, two participating countries collected specific subsamples: In China, participants were only recruited from one university, a nursing school. In Estonia, only international exchange students were invited to participate. Nevertheless, with the exception of the unexpected positive direct relationship between social relatedness and procrastination, all observed divergent effects were non-significant. Indeed, this adds to the support for SDT’s claims to universality regarding the relationship between perceived autonomy, competence, and social relatedness with intrinsic motivation: Results in the included countries were, despite their differing subsamples, in line with the overall trend of results, supporting the idea that SDT applies equally to different groups of learners.

Second, due to the large number of countries in our sample and the overall volatility of the situation, learning circumstances were not identical for all participants. Due to factors such as COVID-19 case counts and national governments’ political priorities, lockdown measures varied in their strictness across settings. Some universities were fully closed, some allowed on-site teaching for particular groups (e.g., students in the middle of a laboratory internship), and some switched to distance learning but held exams on site (see S1 Table in S1 File for further information). Therefore, learning conditions were not as comparable as in a strict experimental setting. On the other hand, this strengthens the ecological validity of our study. The fact that the pattern of results was similar across contexts with certain variation in learning conditions further supports the universal applicability of SDT.

Finally, due to the novelty of the COVID-19 situation, some of the measures were newly developed for this study. Due to the need to react swiftly and collect data on the constantly evolving situation, it was not possible to conduct a comprehensive validation study of the instruments. Nevertheless, we were able to confirm the validity of our instruments in several ways, including cognitive interview testing, CFAs, CR, and measurement invariance testing.

Conclusion and future directions

In general, our results further support previous research on the relation between basic psychological need fulfilment and intrinsic motivation, as proposed in self-determination theory. It also extends past findings by applying this well-established theory to the new and unique situation of pandemic-induced distance learning across 17 different countries. Moreover, it underlines the importance of perceived autonomy and competence for procrastination and persistence in this setting. However, various other directions for further research remain to be pursued. While our findings point to the relevance of social relatedness for intrinsic motivation in addition to perceived competence and autonomy, further research should explore the specific mechanisms necessary to promote social connectedness in distance learning. Furthermore, in our study, we investigated intrinsic motivation, as the most autonomous form of motivation. Future research might address different types of externally and internally regulated motivation in order to further differentiate our results regarding the relations between basic need satisfaction and motivation. Finally, a longitudinal study design could provide deeper insights into the trajectory of need satisfaction, intrinsic motivation and learning behavior during extended periods of social distancing and could provide insights into potential forms of support implemented by teachers and coping mechanisms developed by students.

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Distance education research: a review of the literature

• Published: 12 April 2011
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Distance education is defined, the various approaches for effective research are summarized, and the results of major research reviews of the field are explained in this article. Additionally, two major areas of research are included—research on barriers to the adoption of distance education and research summaries that explain and support best practices in the field. This paper concludes with the summary statement that it is not different education, it is distance education ; what is known about effectiveness in education is most often also applicable to distance education.

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Students’ perceptions on distance education: A multinational study

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• José Alberto Lencastre 4  

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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.

Acknowledgements

Not applicable.

This research was not funded.

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Authors and affiliations.

Curriculum and Instruction Division, Emirates College for Advanced Education, Abu Dhabi, United Arab Emirates

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

José Alberto Lencastre

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Contributions

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.

Corresponding author

Correspondence to Patricia Fidalgo .

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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
• Multinational study
• Perceptions of distance education
• Undergraduate students

Capturing the benefits of remote learning

How education experts are applying lessons learned in the pandemic to promote positive outcomes for all students

Vol. 52 No. 6 Print version: page 46

• Schools and Classrooms
• Technology and Design

With schools open again after more than a year of teaching students outside the classroom, the pandemic sometimes feels like a distant memory. The return to classrooms this fall brings major relief for many families and educators. Factors such as a lack of reliable technology and family support, along with an absence of school resources, resulted in significant academic setbacks, not to mention stress for everyone involved.

But for all the downsides of distance learning, educators, psychologists, and parents have seen some benefits as well. For example, certain populations of students found new ways to be more engaged in learning, without the distractions and difficulties they faced in the classroom, and the general challenges of remote learning and the pandemic brought mental health to the forefront of the classroom experience.

Peter Faustino, PsyD, a school psychologist in Scarsdale, New York, said the pandemic also prompted educators and school psychologists to find creative new ways of ensuring students’ emotional and academic well-being. “So many students were impacted by the pandemic, so we couldn’t just assume they would find resources on their own,” said Faustino. “We had to work hard at figuring out new ways to connect with them.”

Here are some of the benefits of distance learning that school psychologists and educators have observed and the ways in which they’re implementing those lessons post-pandemic, with the goal of creating a more equitable, productive environment for all students.

Prioritizing mental health

Faustino said that during the pandemic, he had more mental health conversations with students, families, and teachers than ever. “Because COVID-19 affected everyone, we’re now having mental health discussions as school leaders on a daily and weekly basis,” he said.

This renewed focus on mental health has the potential to improve students’ well-being in profound ways—starting with helping them recover from the pandemic’s effects. In New York City, for example, schools are hiring more than 600 new clinicians, including psychologists , to screen students’ mental health and help them process pandemic-related trauma and adjust to the “new normal” of attending school in person.

Educators and families are also realizing the importance of protecting students’ mental health more generally—not only for their health and safety but for their learning. “We’ve been seeing a broader appreciation for the fact that mental health is a prerequisite for learning rather than an extracurricular pursuit,” said Eric Rossen, PhD, director of professional development and standards at the National Association of School Psychologists.

As a result, Rossen hopes educators will embed social and emotional learning components into daily instruction. For example, teachers could teach mindfulness techniques in the classroom and take in-the-moment opportunities to help kids resolve conflicts or manage stress.

Improved access to mental health resources in schools is another positive effect. Because of physical distancing guidelines, school leaders had to find ways to deliver mental health services remotely, including via online referrals and teletherapy with school psychologists and counselors.

Early in the pandemic, Faustino said he was hesitant about teletherapy’s effectiveness; now, he hopes to continue offering a virtual option. Online scheduling and remote appointments make it easier for students to access mental health resources, and some students even enjoy virtual appointments more, as they can attend therapy in their own spaces rather than showing up in the counselor’s office. For older students, Faustino said that level of comfort often leads to more productive, open conversations.

Autonomy as a key to motivation

Research suggests that when students have more choices about their materials and activities, they’re more motivated—which may translate to increased learning and academic success. In a 2016 paper, psychology researcher Allan Wigfield, PhD, and colleagues make the case that control and autonomy in reading activities can improve both motivation and comprehension ( Child Development Perspectives , Vol. 10, No. 3 ).

During the period of online teaching, some students had opportunities to learn at their own pace, which educators say improved their learning outcomes—especially in older students. In a 2020 survey of more than 600 parents, researchers found the second-most-valued benefit of distance learning was flexibility—not only in schedule but in method of learning.

In a recent study, researchers found that 18% of parents pointed to greater flexibility in a child’s schedule or way of learning as the biggest benefit or positive outcome related to remote learning ( School Psychology , Roy, A., et al., in press).

This individualized learning helps students find more free time for interests and also allows them to conduct their learning at a time they’re most likely to succeed. During the pandemic, Mark Gardner, an English teacher at Hayes Freedom High School in Camas, Washington, said he realized how important student-centered learning is and that whether learning happens should take precedence over how and when it occurs.

For example, one of his students thrived when he had the choice to do work later at night because he took care of his siblings during the day. Now, Gardner posts homework online on Sundays so students can work at their own pace during the week. “Going forward, we want to create as many access points as we can for kids to engage with learning,” he said.

Rosanna Breaux , PhD, an assistant professor of psychology and assistant director of the Child Study Center at Virginia Tech, agrees. “I’d like to see this flexibility continue in some way, where—similar to college—students can guide their own learning based on their interests or when they’re most productive,” she said.

During the pandemic, many educators were forced to rethink how to keep students engaged. Rossen said because many school districts shared virtual curricula during the period of remote learning, older students could take more challenging or interesting courses than they could in person. The same is true for younger students: Megan Hibbard, a teacher in White Bear Lake, Minnesota, said many of her fifth graders enjoyed distance learning more than in-person because they could work on projects that aligned with their interests.

“So much of motivation is discovering the unique things the student finds interesting,” said Hunter Gehlbach, PhD, a professor and vice dean at the Johns Hopkins School of Education. “The more you can facilitate students spending more time on the things they’re really interested in, the better.”

Going forward, Rossen hopes virtual curricula will allow students greater opportunities to pursue their interests, such as by taking AP classes, foreign languages, or vocational electives not available at their own schools.

Conversely, Hibbard’s goal is to increase opportunities for students to pursue their interests in the in-person setting. For example, she plans to increase what she calls “Genius Hours,” a time at the end of the school day when students can focus on high-interest projects they’ll eventually share with the class.

Better understanding of children's needs

One of the most important predictors of a child’s success in school is parental involvement in their education. For example, in a meta-analysis of studies, researchers linked parental engagement in their middle schoolers’ education with greater measures of success (Hill, N. E., & Tyson, D. F., Developmental Psychology , Vol. 45, No. 3, 2009).

During the pandemic, parents had new opportunities to learn about their kids and, as a result, help them learn. According to a study by Breaux and colleagues, many parents reported that the pandemic allowed them a better understanding of their child’s learning style, needs, or curriculum.

James C. Kaufman , PhD, a professor of educational psychology at the University of Connecticut and the father of an elementary schooler and a high schooler, said he’s had a front-row seat for his sons’ learning for the first time. “Watching my kids learn and engage with classmates has given me some insight in how to parent them,” he said.

Stephen Becker , PhD, a pediatric psychologist at Cincinnati Children’s Hospital Medical Center, said some parents have observed their children’s behavior or learning needs for the first time, which could prompt them to consider assessment and Individualized Education Program (IEP) services. Across the board, Gehlbach said parents are realizing how they can better partner with schools to ensure their kids’ well-being and academic success.

For example, Samantha Marks , PsyD, a Florida-based clinical psychologist, said she realized how much help her middle school daughter, a gifted and talented student with a 504 plan (a plan for how the school will offer support for a student’s disability) for anxiety, needed with independence. “Bringing the learning home made it crystal clear what we needed to teach our daughter to be independent and improve executive functioning” she said. “My takeaway from this is that more parents need to be involved in their children’s education in a healthy, helpful way.”

Marks also gained a deeper understanding of her daughter’s mental health needs. Through her 504 plan, she received help managing her anxiety at school—at home, though, Marks wasn’t always available to help, which taught her the importance of helping her daughter manage her anxiety independently.

Along with parents gaining a deeper understanding of their kids’ needs, the pandemic also prompted greater parent participation in school. For example, Rossen said his kids’ school had virtual school board meetings; he hopes virtual options continue for events like back-to-school information sessions and parenting workshops. “These meetings are often in the evening, and if you’re a single parent or sole caregiver, you may not want to pay a babysitter in order to attend,” he said.

Brittany Greiert, PhD, a school psychologist in Aurora, Colorado, says culturally and linguistically diverse families at her schools benefited from streamlined opportunities to communicate with administrators and teachers. Her district used an app that translates parent communication into 150 languages. Parents can also remotely participate in meetings with school psychologists or teachers, which Greiert says she plans to continue post-pandemic.

Decreased bullying

During stay-at-home orders, kids with neurodevelopmental disorders experienced less bullying than pre-pandemic (McFayden, T. C., et al., Journal of Rural Mental Health , No. 45, Vol. 2, 2021). According to 2019 research, children with emotional, behavioral, and physical health needs experience increased rates of bullying victimization ( Lebrun-Harris, L. A., et al., ), and from the U.S. Department of Education suggests the majority of bullying takes place in person and in unsupervised areas (PDF) .

Scott Graves , PhD, an associate professor of educational studies at The Ohio State University and a member of APA’s Coalition for Psychology in Schools and Education (CPSE), said the supervision by parents and teachers in remote learning likely played a part in reducing bullying. As a result, he’s less worried his Black sons will be victims of microaggressions and racist behavior during online learning.

Some Asian American families also report that remote learning offered protection against racism students may have experienced in person. Shereen Naser, PhD, an associate professor of psychology at Cleveland State University and a member of CPSE, and colleagues found that students are more comfortable saying discriminatory things in school when their teachers are also doing so; Naser suspects this trickle-down effect is less likely to happen when students learn from home ( School Psychology International , 2019).

Reductions in bullying and microaggressions aren’t just beneficial for students’ long-term mental health. Breaux said less bullying at school results in less stress, which can improve students’ self-esteem and mood—both of which impact their ability to learn.

Patricia Perez, PhD, an associate professor of international psychology at The Chicago School of Professional Psychology and a member of CPSE, said it’s important for schools to be proactive in providing spaces for support and cultural expression for students from vulnerable backgrounds, whether in culture-specific clubs, all-school assemblies that address racism and other diversity-related topics, or safe spaces to process feelings with teachers.

According to Rossen, many schools are already considering how to continue supporting students at risk for bullying, including by restructuring the school environment.

One principal, Rossen said, recently switched to single-use bathrooms to avoid congregating in those spaces once in-person learning commences to maintain social distancing requirements. “The principal received feedback from students about how going to the bathroom is much less stressful for these students in part due to less bullying,” he said.

More opportunities for special needs students

In Becker and Breaux’s research, parents of students with attention-deficit/hyperactivity disorder (ADHD), particularly those with a 504 plan and IEP, reported greater difficulties with remote learning. But some students with special learning needs—including those with IEPs and 504 plans—thrived in an at-home learning environment. Recent reporting in The New York Times suggests this is one reason many students want to continue online learning.

According to Cara Laitusis, PhD, a principal research scientist at Educational Testing Service ( ETS ) and a member of CPSE, reduced distractions may improve learning outcomes for some students with disabilities that impact attention in a group setting. “In assessments, small group or individual settings are frequently requested accommodations for some students with ADHD, anxiety, or autism. Being in a quiet place alone without peers for part of the instructional day may also allow for more focus,” she said. However, she also pointed out the benefits of inclusion in the classroom for developing social skills with peers.

Remote learning has improved academic outcomes for students with different learning needs, too. Marks said her seventh-grade daughter, a visual learner, appreciated the increase in video presentations and graphics. Similarly, Hibbard said many of her students who struggle to grasp lessons on the first try have benefited from the ability to watch videos over again until they understand. Post-pandemic, she plans to record bite-size lessons—for example, a 1-minute video of a long division problem—so her students can rewatch and process at their own rate.

Learners with anxiety also appreciate the option not to be in the classroom, because the social pressures of being surrounded by peers can make it hard to focus on academics. “Several of my students have learned more in the last year simply due to the absence of anxiety,” said Rosie Reid, an English teacher at Ygnacio Valley High School in Concord, California, and a 2019 California Teacher of the Year. “It’s just one less thing to negotiate in a learning environment.”

On online learning platforms, it’s easier for kids with social anxiety or shyness to participate. One of Gardner’s students with social anxiety participated far more in virtual settings and chats. Now, Gardner is brainstorming ways to encourage students to chat in person, such as by projecting a chat screen on the blackboard.

Technology has helped school psychologists better engage students, too. For example, Greiert said the virtual setting gave her a new understanding of her students’ personalities and needs. “Typing out their thoughts, they were able to demonstrate humor or complex thoughts they never demonstrated in person,” she said. “I really want to keep incorporating technology into sessions so kids can keep building on their strengths.”

Reid says that along with the high school students she teaches, she’s seen her 6-year-old daughter benefit from learning at her own pace in the familiarity of her home. Before the pandemic, she was behind academically, but by guiding her own learning—writing poems, reading books, playing outside with her siblings—she’s blossomed. “For me, as both a mother and as a teacher, this whole phenomenon has opened the door to what education can be,” Reid said.

Eleanor Di Marino-Linnen, PhD, a psychologist and superintendent of the Rose Tree Media School District in Media, Pennsylvania, says the pandemic afforded her district a chance to rethink old routines and implement new ones. “As challenging as it is, it’s definitely an exciting time to be in education when we have a chance to reenvision what schools have looked like for many years,” she said. “We want to capitalize on what we’ve learned.”

Further reading

Why are some kids thriving during remote learning? Fleming, N., Edutopia, 2020

Remote learning has been a disaster for many students. But some kids have thrived. Gilman, A., The Washington Post , Oct. 3, 2020

A preliminary examination of key strategies, challenges, and benefits of remote learning expressed by parents during the COVID-19 pandemic Roy, A., et al., School Psychology , in press

Remote learning during COVID-19: Examining school practices, service continuation, and difficulties for adolescents with and without attention-deficit/hyperactivity disorder Becker S. P., et al., Journal of Adolescent Health , 2020

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The research on the impact of distance learning on students’ mental health

Yinghua wang.

School of Basic Science, Zhengzhou University of Technology, Zhengzhou, China

Associated Data

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

The mental health of students learning online is a critical task for many countries around the globe. The research purpose was to analyse the factors affecting the quality of mental health of young individuals who learnt under conditions of not total lockdowns but adaptive quarantine restrictions. The research involved 186 volunteers from Zhengzhou University of Technology, 94 were first-year students, and 92 were fourth-year students. The experimental group involved first-year students, and the control group involved fourth-year students. An average age of the participants in the experimental group was 18.3 years, and in the control group, the average age was 22.4 years. The scholars conducted the research after four months of distance learning under the adaptive quarantine. The students could be involved in their usual entertainment activities and interpersonal communication outside the home. The Behavioural Health Measure, better known as BHM-20, was the core psychometric tool. The research finds that distance learning is less effective for first-year students than for fourth-year students because the former cannot effectively adapt and communicate in a new social environment, and develop trusting interpersonal relationships with fellow students and teachers. The research results coincide with other research on this issue and demonstrate a low degree of mental resilience during and after the pandemic. Previous research is not suitable for the analysis of the mental health of students under adaptive quarantine, including the freshmen, considered the most vulnerable group. The article will be useful for professionals interested in distance education in higher educational institutions, workers of socio-psychological services at universities or individuals involved in adapting curriculum materials for distance learning.

Introduction

The COVID-19 pandemic has had a great impact on the mental health and well-being of individuals around the world. While some citizens successfully adapted to the reality of the pandemic and societal lockdowns, others have suffered from mental health disorders caused by a new infection (Serdakova et al., 2023 ).

Moreover, access to mental health services has been severely impeded which had an impact on the mental health of individuals and significantly increased the risk of suicide (Gunnell et al., 2020 ). Most countries on different continents have introduced immediate and drastic protective measures in the fight against the spread of infection, such as closed borders, forced isolation, quarantine restrictions, and distance learning. On the one hand, the virtualization of the educational environment and distance education have reduced inequalities in poor rural regions and ensured equitable access to the education of the population. On the other hand, social isolation in the midst of the COVID-19 pandemic required a unique educational environment but it has caused an increased number of psychological disorders around the world and mental illnesses, including depression, obsessive-compulsive disorder, long-term episodes of counterproductive anxiety, and others (Clemente-Suárez et al., 2021 ). The unexpected shift from in-person to online learning has created a lot of problems for students, teachers, and administrators because many years distance learning has not been very popular in schools and universities (Brown & Carreno-Davidson, 2020 ). At the same time, protecting the mental health of students is vital for higher education because cognitive abilities directly depend on the psychological state of the student, which affects academic motivation, the level of aspirations, involvement in learning, and the emotional and volitional spheres.

As a stage of ontogenesis (human development), higher education may cause exacerbate mental health problems. Before the pandemic, research has primarily focused on student group relationships and campus living as the most common stress factors among students (Davis et al., 2021 ). The research finds that distance learning students report psychological problems more frequently than face-to-face learners, and it is important to analyse the factors that influence mental well-being in distance learning and help to focus on the problem identification related to the transformation of the face-to-face classroom to a virtual environment. The research is important for educators because the COVID-19 infection has not yet been completely defeated, and distance learning is already seen not only as a necessary measure but also as a way to simplify access to education around the world and in China in particular.

Literature review

Since the first cases of COVID-19 were detected, countries’ authorities have tried to find possible measures and ways to fight the pandemic around the world. Face-to-face and autonomous learning systems were replaced by distance learning platforms, and it became a significant factor of mental tension while adapting to new conditions in all areas of life and influenced by inadequate communication at the interpersonal level.

Distance or online learning is the method which helps to prevent the spread of COVID-19, but it has a negative impact on the mental health of higher education students. The main problems experienced by students include anxiety, mild and severe stress, social media fatigue, and depression. At the same time, the symptoms are not always caused by mental health problems (Grigorkevich et al., 2022 ).

The literature analysis revealed the impact of distance learning on the mental health of students and showed that the most sensitive aspects included inadequate time management, the lack of a full-fledged adaptation strategy, the development of digital technologies in a new way, the burden to ensure the quality of new material learning, as well as concerns about the impossibility of funding educational activities under the COVID-19 conditions (Aditya & Ulya, 2021 ).

Some scholars have focused on fear as an emotional response of teachers and students to the distance learning model. The research confirmed that COVID-19 as a global social phenomenon increased the feeling of fear in different areas of life. First of all, it is the fear of being isolated from the family, the fear of academic failure, and the fear of losing social relationships (Al-Maroof et al., 2020 ). At the same time, modern online learning differs significantly from emergency distance learning, influenced by the mental tension decrease, in which addiction as a form of adaptation plays an important role. Under the pandemic restrictions and conditions, universities will adopt mixed or blended formats, since the problems of distance education are turned into educational opportunities. Distance learning allows easy access to education, development of different forms and methods of control, and adaptation and revision of inadequate university programmes (Adedoyin & Soykan, 2020 ).

The mental health of teachers is a part of the discussion devoted to the ecological environment of distance education. A sample of Pakistani and Malaysian teachers was used to analyse the parameters such as teacher self-efficacy and the quality of distance education. The research found that the mental well-being of teachers was a significant factor in ensuring academic success (Guoyan et al., 2021 ).

In Germany, scholars discuss the importance of psychological assistance provided by educational institutions during the crisis at the initial and final stages of distance learning. The attention of the German sociological and psychological services is on the well-being of students and burnout caused by nervous breakdown or inability to continue effective training under the COVID-19 restrictions.

In Germany, mental illness prevention strategies are introduced for first-year students who find it difficult to move into a new social environment despite the distance format. The transition to a new environment causes a high-stress level due to psychological tension, anxiety and increased learning requirements compared to previous school years.

An academic overload and a low level of knowledge among first-year students lead to learning problems, especially in specialised disciplines. Moreover, social and psychological aspects are important, such as mental exhaustion at the stage of admission, the development of new interpersonal relationships, and getting used to the university system of education and assessment (Schindler et al., 2021 ).

The factors mentioned above suggest that education during the first year of study based on the distance learning system can be more difficult for students in a situation when one problem is replaced by another. Cross-sectional research on the mental well-being of European students during the first wave of COVID-19 in May 2020 found that all university students (regardless of the year of study) had poorer mental health than before the pandemic. However, the mental health variable correlated with the belief (irrational belief) that the national government ensured effective management of the epidemic at the municipal level and reduced the risks of infection and negative macroeconomic outcomes (Allen et al., 2022 ).

The spread of the virus, long-term preventive measures and changes in daily routine have led to psychological problems such as anxiety, confusion, social deprivation, and depression. The chronic stress caused by the ongoing pandemic has a profound impact on a sharp and sustained decline of the psychological support that helped individuals cope with failure, emotional problems, disappointment, frustration, and preventing negative emotional experiences, namely resilience, optimism, psychological flexibility, and social relationships (Moroń et al., 2021 ). In China, the effectiveness of psychosocial support and the impact of COVID-19-related stressors on mental health have been investigated.

In Chinese realities, the concept of Psychosocial Support means family and social support in construct to Europe where it involves socio-psychological services.

Moreover, the assessment of the mental health of the respondents was based on the symptoms of depression and loneliness.

The scholars considered that the authorities should focus on the stress that followed the pandemic, as a serious threat to life and well-being, and the risk of infection with new and poorly researched diseases. However, the fear of infection as an independent variable was not correlated with either loneliness or depression, leading to heated debates about the impact of the pandemic on human mental health and well-being (Wang et al., 2022 ).

The COVID-19 pandemic has led to higher rates of mental disorders among the Chinese population. Many individuals have experienced increased resilience during the pandemic as a post-crisis change which had a positive impact not only on the population but on the healthcare system in the country (Zhang, 2022 ).

Restrictive measures under the quarantine have no impact on the cognitive performance of the population on different continents. However, complaints about cognitive decline increased significantly during the pandemic. High quality of life before the period of social isolation is the main factor that influences psychological disability, such as depression, anxiety, low-stress tolerance, ineffective self-regulation, and cognitive complaints (Nogueira et al., 2022 ). Reducing the negative consequences is important for young people in higher education during distance learning.

Problem identification

Only a limited number of publications covered the mental health of students during distance learning and discussed the problems faced by the post-COVID societies. This issue is of particular importance if the governments do not consider distance learning as a vital point and the only possible preventive measure against the spread of a deadly disease. The research purpose is to assess the psychological health of students learning online and investigate the factors that affect the mental health of students. Many scholars analyse the behaviour and psychological problems of schoolchildren, their parents and schoolteachers, paying less attention to the university environment.

This article considers age as the main factor to assess the opportunities and effectiveness of distance education for promoting the mental health of Chinese students in higher education. New experimental data will strengthen the debates about the opportunities promised by online education. After the weakening of quarantine measures, distance learning was no longer mandatory. This fact allowed the scholars to consider distance learning as an alternative form of education for the adult Chinese population who have already mastered social skills at earlier stages of ontogenesis and have maintained working, friendly, and romantic relationships with other people.

The scholars will complete the following tasks, such as identify the most appropriate psychometric tools to assess the quality of the student’s mental health learning remotely under weak isolation conditions; identify a sample size of first-year and fourth-year students to compare the mental health of those who entered the university and those who had experience learning online in a higher educational institution. Moreover, the research will compare the statistical data of two groups and test the null hypothesis. In this article, mental health is evaluated under conditions of adaptive quarantine, during which students have access to mobility, interpersonal communication outside their home, and quality leisure activities, which become possible due to mass vaccination and economic feasibility.

Methods and materials

The BHM-20 methodology can help to assess mental health and the psychotherapy progress used as the main diagnostic tool (Kopta et al., 2015 ). This technique is a 20-item questionnaire that evaluates three components of healthy behaviour: well-being (stress, life satisfaction, and motivation); psychological symptoms (depression, anxiety, panic disorder, mood changes caused by bipolar disorder, eating disorder, substance abuse, suicide intentions, and risk of violence); life activities (work and study, intimate relationships, social relationships, and enjoyment of life).

The full technique name is Behavioural Health Measure often used in a short form BHM. This technique can be used remotely without the direct participation of a psychologist because the respondent can insert answers using a computer or gadget, and the average time to complete the questionnaire is about three minutes. This tool is used in behavioural health clinics of primary health care (Bryan et al., 2014 ). The test consists of 20 statements rated by respondents where 0 points mean Strongly Disagree and 4 points represent Strong Agree .

The maximum total score of psychological well-being, without the suicidal scale, is 80 points, and the minimum score is 0 points, which means deep mental exhaustion. The scales do not have a separate gradation, and it means that the scale showed the overall score of mental health. Moreover, BHM-20 allows additional screening of suicidal thoughts and impulses, and it is considered six times better to identify suicidal intentions in primary care than the standard interview method. However, the research does not make use of this method, because it is secondary in importance to clinical psychological care.

In many cases, BHM-20 is used for primary psychological counselling at a certain number of higher education institutions, including Harvard University, the University of Minnesota, Indiana University, the University of Florida, and others, making this psychometric tool effective for data analysis. The tool is appropriate for adults aged 18 + with normal or high intelligence (Bryan et al., 2014 ). Express methods with a high level of reliability exist in modern methodology including BHQ-20 (Behavioural Health Questionnaire) with similar scales. The technique’s reliability was evaluated using four samples of different age groups, showing high results during the initial testing. Moreover, the high correlation between the scales in the BHQ-20 method indicated the presence of 1 key parameter of mental health. The analysis finds that the BHQ-20 is a reliable and valid mental health questionnaire, even though the number of questions is small (Kopta & Lowry, 2002 ).

Participants

The experimental group of first-year students included 94 individuals (38 females and 56 males) aged 18 to 19 years interested in this research. The control group of fourth-year students consisted of 92 individuals (48 females and 44 males) aged 21 to 23 years. All respondents had prior distance learning experience because the experiment was conducted during the second half of the academic year when both groups learnt for four months under adaptive quarantine. The distance learning experience differed across groups because for first-year students it was similar to their school experience while the control group actually continued professionalization, first under conditions of total quarantine, and then under conditions of adaptive quarantine.

Study design

This research was easy to organise and manage because it was conducted remotely and involved first-year and fourth-year volunteers of Zhengzhou University of Technology. The respondents received instructions in real time and proceeded to complete the electronic questionnaires on the Google platform at the agreed time on their personal computers. The preliminary briefing was conducted in the format of an online conference on ZOOM. The results were sent directly to the experimenter’s computer, entered into a common table, processed, and also remained anonymous. Although the participants logged in via e-mail in a Google form. In fact, the Google form presented to the respondents repeated the questions from BHM-20, greatly simplified the collection and processing of data. The well-structured methodology supported the high motivation level among the participants, immersed in the psycho-diagnostic process. The students were not informed about the research objective, which was the impact of distance learning on the mental health of young individuals. It helped the scholars to ensure the experiment’s purity and avoid bias. Moreover, all respondents could review the methodology results. The primary data processing did not take much time and the experimenter move quickly to statistical analysis.

Data analysis

Data processing was carried out using the SPSS Statistics 22 programme. To test the research hypothesis, the popular nonparametric Mann-Whitney U-test for independent samples was used. It helped to assess the statistical homogeneity of the two samples and ensured the significant differences.

Research limitations

The research had several limitations. First, the BHM-20 is a fast test without subscales. Second, the single-item suicide risk scale was not used in this experiment because this factor is usually used for the pre-responses analysis only. Third, the mental development of first-year and fourth-year students differs due to age differences and life experience, which can affect the level of mental health. Fourth, the BHM-20 method, considered an individualised one, does not have any gradations of Mental Health Normality , which limits the possibility of using this psychometric tool for large-scale research. Fifth, both samples involved volunteers only. The research did not capture the required social section of the population. Sixth, the BHM-20 was originally developed to assess the progress of individual psychotherapeutic performance. It heats the debates about the lack of standardised tests to assess the overall mental health of an individual. Tests without subscales would simplify the assessment of the impact of distance education on the mental health of Chinese youth.

The unprecedented nature of this pandemic has caused several risk factors and events not explored in this research. The overall physical health, physical training, domestic abuse, violence, and mental health problems experienced by individuals caused by the pandemic were not examined. All indicators used in this research are self-reported, so the scholars consider that some respondents may be apt to provide truthful or false answers, which therefore could influence negatively the results.

Ethical issues

This experiment was based on high ethical standards because both samples involved volunteers and their identity was kept anonymous. Some students received feedback from the researcher on an individual basis. The experiment goals were not disclosed to the participants. The students were informed about some goals without going into detail including information about voluntary mental health monitoring. The experimenter did not benefit from the research and all the financial expenses were covered by Zhengzhou University of Technology.

The research usefulness function was realised in full because distance learning under adaptive quarantine was introduced not only in China but in Europe. This is an important factor because the pandemic has not yet been completely defeated despite the mass vaccination programmes. The use of distance learning in higher education institutions, considering mental health, has been still questioned. The research finds drawbacks in policy development especially when distance learning is proposed for first-year students who integrate into a new social environment and acquire new skills and master knowledge.

This scientific discussion is of exceptional social significance, allowing academic institutions to balance live communication in the classroom and the mental health of students who experienced an academic overload. There was no risk to the physical and mental health of freshmen. Moreover, monitoring was used as a self-report measure and forced respondents to pay attention to their mental health and analyse their overall mental conditions over the past two weeks.

The results processing started with the analysis of the mean values for groups, which made it possible to produce high-quality primary research. At this stage, significant differences between the groups were manifested. Significant differences were found in the median of grouped data, and minimum and maximum values. So, the average value in the experimental group of first-year students was 35.14 points out of 80 possible points, while in the control group of fourth-year students this indicator was higher and reached 52.66 points. The data is available in Table  1 .

Primary Data Analysis

If the minimum value of the BHM index in the group of first-year students is 10 points, then in the control group it is already 33 points. The difference illustrates the high vulnerability level of former school students and a need for adaptation and effective use of psychological resources during the transition period, from one social environment to another. At the same time, the maximum intragroup values are similar. In the experimental group, the BHM score did not exceed 61 points, while in the control group, the highest value was 74 points out of 80 points. The standard deviation is lower in the group of fourth-year students, which suggests a higher homogeneity in the assessment of psychological well-being.

It proves the significance of the socio-psychological services at the stage of adaptation of first-year students so that the students can receive professional support and focus on the educational process. These strategies should be introduced into practice under adaptive quarantine. For example, one of the possible interventions is support groups organised once a week and conducted by a professional psychologist online.

The second stage of data processing involved a comparison of samples to identify the statistical differences. The classical Mann-Whitney U-test for independent samples was used. The analysis revealed that there were statistically significant differences between the groups. The data are available in Table  2 .

Secondary Statistical Analysis

The results reveal that the integrated value of BHM in the groups of first-year and fourth-year students is significantly different because an extremely low level of statistical error was detected, namely - p = 0.000 with admissible p = 0.05. This result suggests that the psychological well-being of fourth-year students is more stable compared to first-year students. The research considers that distance learning is not the only factor affecting the mental health of the respondents from the experimental group. The scholars assumed that psychological problems experienced by students were caused by many factors including adaptation processes to distance learning, personality crises and academic overload. The results showed that distance learning for first-year students was less desirable than for the fourth-year respondents. It is difficult for the socio-psychological service workers to support students and provide psychological help online, detect emotional burnout, apathy, and depressive episodes in a distance learning format. This research showed that age and the year of study significantly affected the mental health of students learning online.

Empirical research in South Africa illustrated that university professors failed to deliver adequate psychological support to isolated students. Students relied heavily on the support of both the administrative and academic staff when it came to the learning process. As a result, the high work stress felt by teachers was added to the high academic stress of students, which increased the risk of emotional burnout and nervous exhaustion in both groups (Poalses & Bezuidenhout, 2018 ).

Distance learning sabotage denial to accept a new academic environment increases the likelihood of mental disorders and reduces the cognitive abilities of schoolchildren whose parents are against this form of teaching (Davis et al., 2021 ). Distance learning under total lockdowns can cause a sense of learned helplessness with online learning technology, and worsen the quality of mental health of students of different age groups. The factors that may eliminate the negative consequences are academic motivation, reduced fatigue and a loss of interaction that cannot be restored with any online conferences (Garcia et al., 2021 ).

The U.S.-based University conducted a multi-thousand online survey involving undergraduate and graduate students based on standardised scales for assessing physical health and anxiety, as well as additional multiple-choice questions and open-ended questions about stressors and coping mechanisms under the pandemic restrictions. The results showed that half of the respondents experienced an increased level of depression and anxiety. At the same time, less than half of the participants indicated that they coped effectively with the stress factors caused by online learning and the threat of infection (Wang et al., 2020 ).

In Malaysia, the mental health of students during distance learning was evaluated using the DASS-21 methodology, designed to assess the depressive-anxiety stress factors. The questionnaire analysis showed that 30% of students in vocational schools experienced severe or extremely severe depression, 41% had anxiety, and 20% had chronic stress. At the same time, the biological sex of the respondent had a significant impact on anxiety. The research suggests investigating and combining distance learning with face-to-face education and practical work experience within the curriculum (Ahmad et al., 2022 ).

The results comparison of the mental state of students in full-time and distance learning was performed in Eurasia. This research assessed satisfaction with academic performance and the severity of depression and anxiety symptoms. The results showed that the prevalence of depressive symptoms and anxiety among students was higher during distance learning, compared with similar results obtained during full-time education. Moreover, the research results showed that the sudden transition from one learning environment to another was a major cause of chronic stress, which led to a high prevalence of depressive symptoms and anxiety among students (Lyubetsky et al., 2021 ).

In Italy, the impact of long-term online learning on the mental health of students was also researched. The second (control) experiment used the same sample and conducted the research over six months. The results reveal significant differences on scales such as students’ connection with other students and teachers, workspace organisation, and boredom between lessons. Moreover, the results show significant correlations between student academic development and the quality of distance learning, course adaptation, workspace arrangements and communication with other students and teachers, and between students’ emotions and communication with other students and teachers (Baltà-Salvador et al., 2021 ). The research finds that the social relations in distance learning can be an additional psychological resource for students that should not be underestimated.

Cross-cultural research based on a sample of thousands of students showed higher rates of depression, suicidal intentions and post-traumatic stress disorder compared to pre-pandemic levels and current rates in individuals belonging to ethnic minorities, which could also be considered as one of the factors of influence. Though the most common pandemic outcome is PTSD (Post-traumatic stress disorder ) , recorded in 62% of the respondents. However, neither age, nor personal history of mental illness, nor perceived social support was a significant risk factor of mental health (Torres et al., 2022 ).

The UK has developed a large-scale online questionnaire designed to assess mental health under the pandemic restrictions. The authors of the questionnaire considered socio-demographic variables, previous physical or mental illness, personal experience with COVID-19, information in the media, pandemic concerns, degree of personal traumatic experiences, PTSD caused by a pandemic outbreak, generalised anxiety disorder, depressive disorder, sleep quality, emotional deregulation, loneliness, social support, and the meaning of life (Armour et al., 2021 ). This questionnaire has not yet been standardised and adapted in other countries. However, all of the above factors affect the quality of mental health during and after the pandemic. There were no publications devoted to mental health under adaptive quarantine, which proved the need to start a debate on the key theoretical and empirical questions.

This article investigated the main factors that affected the mental health of students. The theory of intelligence helps to illustrate that the pandemic and distance education increase the risk of clinical depression, generalised anxiety disorder, PTSD, apathy, learned helplessness, burnout, nervous breakdown, and so on. Furthermore, non-university students more often report mental health problems than those who learn academic disciplines in a traditional format. The results prove that therapeutic and individualistic approaches to mental health cannot be the only methods used to improve students’ mental well-being.

The scholars have to investigate inclusive curriculum design and assessment methods. Moreover, educational institutions should introduce and teach advanced telecommuting skills, implement educational systems and processes that do not cause stress, and design learning environments based on professional feedback to maintain a balance between quality education and the student’s mental health. The research proposed the holistic approach to introduce mental health practices during distance learning that can influence positively the mental well-being of students. At an empirical level, the present research investigates distance learning opportunities during adaptive quarantine and finds that it is less effective for first-year students who have just entered the university. The problems that may arise are caused by the complicated adaptation process which requires a significant amount of effort, the difficulties in developing new social relations with teachers and fellow students, and academic overload, especially in learning specialised disciplines.

The experiment shows that first-year students are a more vulnerable group than fourth-year students who have learnt online at the university and feel much more competent when it comes to university education. In addition, the research finds that first-year students need high-quality psychological support being at risk with a reduced tolerance for uncertainty. The empirical research finds that age and the year of study affect the mental well-being of students. The scholars suggest that under conditions of adaptive quarantine, it is necessary to pay attention to psychological screening and psychological interventions to prevent depressive episodes, apathy, low academic motivation, low-stress resistance, ineffective self-regulation, and so on. The scientific value of the research is that it causes a worldwide discussion about the safety of distance education and its impact on the mental health of university students.

Moreover, some risks for mental health may occur when young individuals learn remotely. However, the research proves that the psychological states of undergraduate students are more stable and the students are better prepared for distance learning. This is the main practical value of the article to the university administration and teachers. This research manifests that the quality of socio-psychological services in universities is a priority for the administration, and special strategies should be developed to prevent mental disorders among students and maintain an effective and advantageous learning environment for all parties involved in the education process.

No funding was received to assist with the preparation of this manuscript.

Data availability

Declarations.

There are no competing interests to declare that are relevant to the content of this article.

The study was conducted in accordance with the ethical principles approved by the Ethics Committee of Zhengzhou University of Technology.

All participants gave their written informed consent.

Publisher’s Note

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

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Research supervision in distance learning: issues and challenges

Asian Association of Open Universities Journal

ISSN : 2414-6994

Article publication date: 28 April 2020

Issue publication date: 3 July 2020

The purpose of this study is to explore and highlight the issues and challenges teachers face while supervising thesis and projects in distance/online learning mode.

Design/methodology/approach

This is a cross-sectional qualitative study. Grounded theory approach using Gioia methodology has been applied. Semi-structured interviews of 16 research supervisors have been conducted to explore the issues and challenges faced by the supervisors in guiding research students. Purposive sampling is used to select the subjects for data collection.

Results of the study reveal that the time constraints, official restrictions, irregular contacts and technology are the main issues faced by supervisors. Whereas student–supervisor interaction, diversity, perceptions, virtual communities and academic collaboration are the biggest challenges for the supervisors in distance learning. Lastly, it is found that students' attitude and supervisors' mindset are the key success factors in distance research supervision.

Practical implications

Findings of this paper will help institutions particularly in Asia, to strategically review their research programs to make these programs more effective. Effectiveness will encompass two things, timely completion and novel research. If these two things are addressed efficiently, comparison of distance learning with conventional learning will be more favorable for distance learning.

Originality/value

This study will be helpful for the top management of distance/online learning institutes to better equip their teachers and students to complete their research endeavors accordingly. This is an empirical research based on primary data collected from the research supervisors currently supervising thesis/projects at Virtual University of Pakistan.

• Distance learning
• Higher education
• Research supervision

Zaheer, M. and Munir, S. (2020), "Research supervision in distance learning: issues and challenges", Asian Association of Open Universities Journal , Vol. 15 No. 1, pp. 131-143. https://doi.org/10.1108/AAOUJ-01-2020-0003

Emerald Publishing Limited

Copyright © 2020, Muhammad Zaheer and Saba Munir

Published in Asian Association of Open Universities Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Pakistan is a big country in terms of population as it is world's sixth-most populous country, to this large population, provision of education is a daunting task. Large population with small number of qualified faculty members resulted in shortage of institutional capacity to cater the needs of education. One of the solutions to this problem was establishing distance learning (DL) institutions and Government of Pakistan took the initiative in this regard. Currently two distance/online universities are working in Pakistan, Allama Iqbal Open University, established in 1974 and Virtual University of Pakistan established in 2002. Moreover, many conventional universities have also started DL programs.

DL improves the access to education for all the aspiring students. DL overcomes the issues of capacity, infrastructure and faculty. It provides standardized quality content to all the students without any discrimination.

Like conventional system, DL is also not free from certain shortcomings, for example, burden of learning is shifted on the learner (though flexibility is there), there is too much diversity in the same course, more importantly student and teacher are separated by time and space leading to asynchronous mode. Though, by using modern information and communication technology (ICT), universities are trying hard to be synchronous whenever possible. These issues of learning are exacerbated when students enter their research phase like research thesis or research project. Research requires a closer contact and frequent interaction between supervisor and the student. And the flexibility of DL can become an obstacle to complete research with quality within specific time period.

In research, supervisors' responsibility increases exponentially as each student is working on a different topic and requires customized mentoring. This poses a bigger challenge to the supervisors to take a student along the bumpy road of research with ease by maintaining quality and following the timeline given by the university.

This research is focused on exploring the issues and challenges faced by the research supervisors in DL. Numerous studies have been conducted to explore the problems and issues faced by the students in DL, while issues of supervisors need more attention.

Primary data have been collected from the teachers who are supervising research theses or projects in DL. Semi-structured interviews have been used for data collection with informed consent. Grounded theory has been used as qualitative technique for exploring the issues and challenges in research supervision.

2. Literature review

Students in higher education generally struggle to complete their research endeavor in specified time ( Costa, 2018 ). This problem exacerbates when it comes to students studying in DL. Irrespective of the mode of education (DL or conventional), supervisors play a vital role in research supervision. Supervisors' motivation to supervise the students is very important ( Askew et al. , 2016 ). According to Askew et al. (2016) , four factors that affect research supervisors are workload agreements, time pressures, quality of students and recognition of the supervisors' contribution.

Supervision is a social interaction between two people who might have diverging views but same objectives. Supervision is defined as “intensive, interpersonally focused one-to-one relationship between the supervisor and the student” ( Wood and Louw, 2018 ). Supervision plays vital role during thesis or research work and the relationship between the supervisor and the student determines the successful completion of the research thesis ( Da Costa, 2016 ). Increasing the throughput of thesis students is the main focus of the universities these days due to certain time restrictions imposed by the Higher Education Commissions. On the other hand, it enhances the reputation of the institutions as well as provides the economic benefits in terms of more admissions. The completion rate and the quality of thesis can be increased by improving the processes associated with thesis in organization and among those factors supervisor–student interaction is the most important one ( Aghaee, 2015 ). In online and distance learning (ODL), the role of supervisor becomes even critical where a supervisor is required to build a culture of productive interaction with his/her supervisee ( Easton, 2003 ).

In DL mode where student–teacher interaction lacks face-to-face interaction and physical absence of the supervisors hinders the quick relationship building. ODL poses various threats to the students as they might feel alone and dejected and physical distance from the supervisor may make them skeptical about the quality of their work. In such virtual mode, the responsibility of the supervisors increases in building an interactive setup where the students should feel confident and supported by the supervisor during the whole time period of research work ( Donnelly and Fitzmaurice, 2013 ). The successful completion of research work or a thesis depends on multiple factors pertaining to supervisor and supervisee. These factors can be experience, attitude toward the completion of the thesis and the ability of the student. A study conducted by Guin (2019) on the social work programs offered in Indira Gandhi National Open University (IGNOU) where it is mandatory for supervisor and the supervisee to meet, it was found that student–teacher interaction was the biggest challenge due to distance between the study center and students' residence and socioeconomic background of the students.

A graduate class usually is a mix of diverse students in terms of age, culture, experience, ability, etc. ( Abiddin et al. , 2011 ). This diversity is even more noticeable in DL where a class may consist of a student from a metropolitan city or a far flung area, a full-time student or a job holder, a student with clear idea of his research topic or a student having no idea of his topic or the methodology he/she is going to adopt. These variations in the ability and knowledge of students make supervision more challenging for the supervisors teaching in distance education. Many studies have been conducted on the issues and challenges faced by students but lesser studies are available on the difficulties of the supervisors who are the key player of research process.

According to Lessing and Schulze (2002) , a supervisor has to establish a balance among multiple factors like supporting students, having expertise in research, providing positive criticism and bringing creativity. He needs to work on various fronts to bring quality research work by providing guidance to the students in a way that leads to innovative ideas while keeping in mind the timelines and rules established by the organization. These tasks become even more horrendous in DL mode. Student persistence is a key element in ODL, Au et al. (2018) recommend that to enhance student persistence advisors should be appointed for proper guidance of students and lesson videos should be kept short for better attention.

According to MacKeogh (2006) , distance teaching mode poses many challenges for the instructors including student's access to the resources and increased chances of deception by students in their work as being distant it sometimes become difficult for a teacher to analyze that whether the work submitted by student is really done by him, in other words authenticity of student's work cannot be ensured easily as compared to conventional mode. Lack of research skills, as Lindner et al. (2001) conceptualized that lack of on-campus interpersonal dimension can be a disadvantage for research students as face-to-face interaction helps them in acquisition of research knowledge.

Social presence and interaction is enhanced by the nonverbal gestures and cues that help students understand the point of discussion more effectively. In the absence of nonverbal communication, distance supervision becomes more challenging for the supervisors and they need to exert extra efforts to compensate it ( Lindlof and Shatzer, 1998 ). In the same way, teacher cannot guess when student is bored, confused or frustrated. This makes the participants less social and more task-oriented. Moreover it takes long for a supervisor and student in DL to develop social relation as compared to conventional, face-to-face supervision. According to Stacey and Fountain (2001) , power and status differences cannot easily be perceived in DL. Although it is considered good in building trusting social interaction, but in some cases it may distort the respect element associated with a teacher. Another issue faced by off campus students is the difficulty in accessing the appropriate resources like software, research tools or articles for literature review, that ultimately affect the quality of research work; the main focus of the instructor.

Butcher and Sieminski (2006) stated that face-to-face interaction between student and teacher is vital for the motivation, confidence building and knowledge enhancement of supervisee and distance supervision sometimes becomes passive due to lack of face-to-face interaction, causing dissatisfaction among the students that becomes the biggest challenge for the supervisors ( MacKeogh, 2006 ). But, the effective and appropriate use of ICT can help providing a supportive environment to the thesis students and supervisors. According to study conducted by Iwasaki et al. (2019) no significant difference was found between face-to-face tutoring and online tutoring using ICT. ICT can be of great assistance in providing frequent feedbacks and high level of interaction between supervisor and supervisee ( Hansen and Hansson, 2015 ). Virtual meetings with supervisee can save the traveling time of supervisors and allow them to arrange meetings in flexible timings that ultimately increases the student-teacher interaction ( Aghaee et al. , 2013 ). This interaction only depends on the preference of the supervisor, for example when and how often he/she wants to meet his/her supervisee ( Karunaratne, 2018 ). So it can be concluded that with or without technology, the supervisor is the key element in the research process and universities should focus on resolving the issue and challenges faced by the supervisor if they want to provide quality supervision to the students or want to attain maximum satisfaction and motivation for them. Unfortunately most of the studies have focused on the issues faced by the students of DL while ignoring the supervisor or teacher end. This study particularly has focused on the challenges faced by the supervisors.

3. Methodology

This is a qualitative study and inductive approach has been used. Philosophical assumption is interpretivism, and grounded theory approach is used to collect and analyze the data.

How long have you been supervising thesis/research projects?

Please explain your supervision experience in DL.

Have you also supervised students in conventional system? If yes how was the experience?

What issues have you faced while supervising students in VU (both thesis and projects)?

In your opinion what are the biggest challenges of research supervision in DL?

How things can be improved? Suggestions.

Demographic data of the informants were also collected, which have been shown in Table 1 .

All the interviews were audio recorded with the permission of informants. 16 interviews were conducted, according to Steinar (2007) in qualitative research sample size ranging from 5 to 25 is sufficient. However, in grounded theory we follow theoretical sampling, which means data are collected till data saturation is achieved ( Glaser and Strauss, 1967 ). In this study, data saturation was there after 10 interviews, six more interviews were conducted to validate the findings of the previous interviews. After each interview, audio recording was transcribed and main themes were extracted. Gioia et al. 's (2013) methodology was applied, in this methodology main ideas (themes) are called first-order categories, from these categories, second-order themes are developed and at the end aggregate dimensions are extracted from second-order themes. For each question data were analyzed and compared with other responses to have constant comparison ( Glaser and Strauss, 1967 ). This adds to the validity of the data.

First-order categories are the initial codes generated from the responses of informants, these codes or categories resemble to what Corbin and Strauss (1990) termed as open coding, a large number of codes generally emerge in the beginning. As the data collection and analysis continues, similarities and differences among these initially developed codes are visible, similar categories are merged and this reduces the number of initially generated categories, these categories are second-order themes, similar to axial coding ( Corbin and Strauss, 1990 ). Second-order analysis is more abstract and theoretical in nature, it is analyzed if the emerging concepts explain the phenomena under observation ( Gioia et al. , 2013 ). After second-order analysis, second-order themes are further explored to merge into aggregate dimensions. The pictorial representation of this process is called data structure. Figures 1–3 represent the data structures of the responses of the informants.

4. Data analysis

Table 1 shows the information of informants. VUP is just 17 years old institution and it has relatively young faculty members as compared to other universities. Out of 16 informants, 12 belong to VUP and rest four belongs to conventional universities. It is noteworthy that authors of this study have 12 years of experience in DL.

VUP has a good number of females working in the faculty, which is quite representative of Pakistan's population mix. Average age of the VUP informants is 37 years approximately, which shows that VUP has quite young faculty members.

Figure 1 , represents the data structure of issues faced by the supervisors in DL. Five second-order themes emerged which made up an aggregate dimension “communication barriers”.

Time constraints are the most frequently cited problem of the students in DL by the research supervisors. DL is an opportunity for those students who cannot attend regular classes in conventional class room environment. So these students are either living in remote areas where they do not have the access to higher education institutions or they are working students. Working students have their own issues. Due to their time schedule in office they are unable to contact their supervisors as scheduled. This makes their research work a bumpy road to travel. As teachers/supervisors and students have the same working hours, so, there is a clash of time. As one of the supervisors reported “students have to take off from office to contact me for research discussion”. This is not always possible for the working students to take leave from the job, but some students do, according to one informant “my student always came for discussion on voice call whenever I had scheduled him”. These constraints prohibit students to contact their supervisors for mentoring; hence the result is delayed research.

Another factor is the official restrictions of the working students, some students are working in law enforcement agencies and have the official restriction on the use Internet and even cell phones, this aggravates the communication gap. Sometimes they are deployed in far areas where they have no access to networks. So, this becomes a hurdle in the communication.

Irregular contact with the supervisor is yet another issue, students in DL are not bound to appear in class as they are in conventional mode, and attendance is not an issue (that's why they are in DL). This also becomes an unnecessary hurdle, students sometimes become complacent, they become dormant and lose contact with their superior as one professor told “one of my students did not appear for 2 yrs then came and asked for extension, in conventional system you find student who is slow you ask him/her what's going on so you may say something, in DL it is not possible” this professor is basically teaching in conventional system and also supervising thesis in DL. Remaining away for some time has some influence on the supervisors as well, irregular contact results in dissatisfaction of the supervisor, one supervisor explained “when any student remains away for quite some time, even I forget what I had suggested and what was in my mind, I have to start from scratch and this is really depressing”. There are some genuine reasons for remaining dormant including marriage, pregnancy and official deployment in any mission.

Technological issues also restrict contact which has been termed here as tech-issues. These issues include non-availability of Internet, Internet speed, interrupted power supply and students' expertise to use IT devices and applications. Due to infrastructure issues, provision of Internet services is not up to the mark in certain areas which becomes a hurdle in contacting the supervisor. This leads to interrupted communication which damages the learning process. According to one supervisor “when they (students) come online there are issues of technology like Internet speed or students' understanding of technology”. Sometimes students are unable to use the application effectively which is being used for communication, as one supervisor complained “we are stuck in tech issues then on research, initial interactions are just focused on training the students on how to use this application for voice or video calls”. Sometimes there are issues of electricity supply, though university is well equipped to cater such issues but students in far areas face problems of irregular power supply.

Another aspect is the official restriction on the use of certain user applications by some countries especially in Gulf. This becomes a big barrier and restricts student–teacher interactions. Students use proxies to bypass these restrictions but these proxies sometimes work and sometimes not. Overall academic interaction is severely affected by these restrictions.

These second-order themes, time constraints, official restrictions, irregular contacts, tech and legal issues make up an aggregate dimension “Communication Barrier”. Communication barrier is a major issue in DL, though flexibility has its own benefits but in research endeavors distance can make a difference. If student–supervisor interactions are regular without any delays, this can foster this relationship and let students finish their research projects/theses well within time.

Figure 2 shows the data structure of challenges faced by the research supervisors during their supervision in DL mode. Five second-order themes have emerged from the data, which are discussed here.

Student–supervisor interaction is at the very heart of research endeavor in any mode. Higher the number of effective interactions, greater are the chances of good research output. Though, technology has overcome most of the issues and barriers of interactions, yet, according to some supervisors face-to-face interactions have to add value. According to one supervisor “thesis supervision is not just an academic activity it is more than that, it is an overall grooming activity for student in which student not only learns about research but other aspects of life as well.” This factor is quite peculiar and needs to be addressed for example according to another supervisor “lack of physical contact does not let student teacher relationship build, we cannot motivate them.”

Students in DL are quite diverse; Pakistan is a big country with cultural diversity and students from diverse background are present. Sometimes, this diversity is good and at times perplexing for the supervisor. Students from different regions require different levels of mentoring. Supervisors have to adjust accordingly. Moreover, this diversity is also found in the subjects, for example, Psychology, Management Sciences or Mathematics. One respondent explained “it is very difficult to explain the feedback on student's work in my subject as it requires different software.”

This is quite common that students in distance/online learning join virtual communities and groups. Not everything found on the Internet is authentic; students discuss their research topics and methodologies there, and are influenced by the discussions on these forums and they then try to convince their supervisors. These suggestions unnecessarily affect the research process. Students unintentionally, sometimes, reveal their novel research ideas in blogs/groups which are then adapted by others. This is very serious matter. As reported by one supervisor “my student who was at data analysis stage of his thesis, innocently shared the data file on Internet, which was quickly used by someone else, and wrote a paper, moreover the paper was also uploaded, when we checked the plagiarism, my student's original work was then plagiarized”. Such online communities pose an extra challenge to research supervision.

Students' perceptions regarding DL and supervision also bring a hard challenge for the supervisors. There are certain myths among the students that research in DL is tough. As revealed by a respondent “negativity regarding DL is quite common that it is difficult to complete thesis in DL, students are influenced by such remarks so ultimately it takes more time to complete.” Since there is lack of physical interaction, so supervisors feel they are not able to convince or motivate students at times. Students do spread positive and negative word of mouth about supervisors which also affects the minds of students and they request for supervisor change. Some students think that they cannot complete their research in DL, these are the students with low self-efficacy. Supervisors have to keep their students motivated that they can do it.

Research is a joint venture of student and supervisor, after successful completion of the project/thesis, next step should be the publication of the research paper. But this has been a rare phenomenon in DL as reported by the supervisors. There are some students who after the completion of their thesis got their papers published with their supervisors. But in general it does not happen. Generally, students do not remain in contact with the supervisor, according to one supervisor “once thesis is done students no more contact you, like I had a student whose work was good but he disappeared as soon as passed out, I urged him to present and publish his work, but he never did, which is really a drawback.” Student–supervisor academic collaboration is very important factor for research publications that needs to be addressed.

These five second-order themes, namely, student–supervisor interaction, diversity, perceptions, virtual communities and academic collaboration contribute to aggregate dimension challenges in DL.

These are not small challenges in a country like Pakistan where DL is still fighting for its recognition as the equally effective education mode like conventional mode.

Data structure shown in Figure 3 depicts the key success factors in distance supervision. Two second-order themes attitude and mindset were discovered form the interviews.

According to supervisors, in DL students' attitude is a critical factor. Students should be self-motivated and should have high self-efficacy. Students having internal locus of control are the best for DL as in DL burden of knowledge acquisition is borne by the learner in general, this mode requires a persistent motivational effort on the part of the students ( Zaheer, 2013 ). Students who are ready to put more efforts finish their research work well within time, according to a senior research supervisor “some of my students who were motivated enough completed their research in one semester and they were position holders of their sessions”. This is important that whether a student is a full-time student or working student, enthusiasm and self-discipline are very important. As explained by another supervisor “my working students came on the scheduled time on voice call for guidance, I seldom had to wait”. It is clear that students' own positive attitude is the key, when they follow the instructions and seek guidance they are able to complete their work accordingly.

Second important theme that emerged is the mindset of supervisors. If supervisors are of the view that supervising a research work from the distance is a difficult or uphill task they are less likely to motivate their students. As shared by one supervisor “in my opinion conventional and distance have not much difference, we have just made up our mind that virtual is difficult.” Positive mindset of the mentor is also critical; supervising from the distance may require different skills. Comments of another supervisor were “as instructors we should realize the limitations of students, our mindset needs to be changed.” And “if proper guideline is given to students they follow the supervisors”. It was also expressed “distance learning students are technically self-reliant on IT.” So it is very important to acknowledge that these students are self-confident and self-reliant. This quality of students is a quality that is hallmark of these students in general. According to another supervisor “online guidance is better than conventional face to face, you can give more time to students, they do not have to travel and bother too much, to meet the supervisor”.

Students' attitude and supervisors' mindset are the factors that are the key success factors in DL research. Positive student attitude and supervisor mindset are the factors that make DL a successful experience.

5. Conclusion and recommendations

The present study has focused on the issues and challenges of research supervision in DL. It was found that time constraints, irregular contact, technological issues, legal issues and official restrictions are the issues in DL that create communication barriers between students and supervisors. Whereas student–supervisor interaction, student diversity, virtual communities, students perceptions toward DL and academic collaboration are the main challenges in the DL supervision.

On the basis of supervisors' suggestions it is recommended that institutions should facilitate face-to-face interactions more frequently with the students who are involved in research. Though, technology has its advantages but it is not without issues. For example issues of bandwidth are always there in Asian countries, such distortions hinder communication. Institutions should adopt a two prong strategy to overcome these issues; they should increase the number of study centers where students can go and use technology to connect to their supervisors, since bandwidth of home users is not that good; and if possible, students who are geographically nearer to supervisors should be allocated to them so that more frequent face-to-face interaction may take place.

Institutions should invest more in gaining access to online research databases so that the access to online databases of students is also enhanced. Moreover, students should be facilitated to participate in research workshops, conferences and seminars to sharpen their research skills.

There is also a need of specific trainings for the teachers in DL, they are away from their students and at times they fail to exhibit empathy which may result in communication barriers. Special research initiatives are required to develop training modules for online/DL teachers and research supervisors. Similarly, at the start of study program, effective orientation sessions need to be arranged by the universities to acclimatize the students with DL environment and use of technology so that they learn how to work independently and effectively. Moreover, at the start of research projects/theses, students should be given effective orientations and refreshers regarding research, data analysis and related software.

Findings of this paper will help institutions particularly in Asia, to strategically review their research programs to make these programs more effective. Effectiveness will encompass two things, timely completion and novel research. If these two things are addressed efficiently, comparison of DL with conventional learning will be more favorable for DL.

Communication barriers

Challenges in distance learning

Key success factors

Information of supervisors

Note(s) : *AP: Assistant professor, *DL: Distance learning

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