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The effects of online education on academic success: A meta-analysis study

• Published: 06 September 2021
• Volume 27 , pages 429–450, ( 2022 )

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• Hakan Ulum   ORCID: orcid.org/0000-0002-1398-6935 1  

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The purpose of this study is to analyze the effect of online education, which has been extensively used on student achievement since the beginning of the pandemic. In line with this purpose, a meta-analysis of the related studies focusing on the effect of online education on students’ academic achievement in several countries between the years 2010 and 2021 was carried out. Furthermore, this study will provide a source to assist future studies with comparing the effect of online education on academic achievement before and after the pandemic. This meta-analysis study consists of 27 studies in total. The meta-analysis involves the studies conducted in the USA, Taiwan, Turkey, China, Philippines, Ireland, and Georgia. The studies included in the meta-analysis are experimental studies, and the total sample size is 1772. In the study, the funnel plot, Duval and Tweedie’s Trip and Fill Analysis, Orwin’s Safe N Analysis, and Egger’s Regression Test were utilized to determine the publication bias, which has been found to be quite low. Besides, Hedge’s g statistic was employed to measure the effect size for the difference between the means performed in accordance with the random effects model. The results of the study show that the effect size of online education on academic achievement is on a medium level. The heterogeneity test results of the meta-analysis study display that the effect size does not differ in terms of class level, country, online education approaches, and lecture moderators.

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1 Introduction

Information and communication technologies have become a powerful force in transforming the educational settings around the world. The pandemic has been an important factor in transferring traditional physical classrooms settings through adopting information and communication technologies and has also accelerated the transformation. The literature supports that learning environments connected to information and communication technologies highly satisfy students. Therefore, we need to keep interest in technology-based learning environments. Clearly, technology has had a huge impact on young people's online lives. This digital revolution can synergize the educational ambitions and interests of digitally addicted students. In essence, COVID-19 has provided us with an opportunity to embrace online learning as education systems have to keep up with the rapid emergence of new technologies.

Information and communication technologies that have an effect on all spheres of life are also actively included in the education field. With the recent developments, using technology in education has become inevitable due to personal and social reasons (Usta, 2011a ). Online education may be given as an example of using information and communication technologies as a consequence of the technological developments. Also, it is crystal clear that online learning is a popular way of obtaining instruction (Demiralay et al., 2016 ; Pillay et al., 2007 ), which is defined by Horton ( 2000 ) as a way of education that is performed through a web browser or an online application without requiring an extra software or a learning source. Furthermore, online learning is described as a way of utilizing the internet to obtain the related learning sources during the learning process, to interact with the content, the teacher, and other learners, as well as to get support throughout the learning process (Ally, 2004 ). Online learning has such benefits as learning independently at any time and place (Vrasidas & MsIsaac, 2000 ), granting facility (Poole, 2000 ), flexibility (Chizmar & Walbert, 1999 ), self-regulation skills (Usta, 2011b ), learning with collaboration, and opportunity to plan self-learning process.

Even though online education practices have not been comprehensive as it is now, internet and computers have been used in education as alternative learning tools in correlation with the advances in technology. The first distance education attempt in the world was initiated by the ‘Steno Courses’ announcement published in Boston newspaper in 1728. Furthermore, in the nineteenth century, Sweden University started the “Correspondence Composition Courses” for women, and University Correspondence College was afterwards founded for the correspondence courses in 1843 (Arat & Bakan, 2011 ). Recently, distance education has been performed through computers, assisted by the facilities of the internet technologies, and soon, it has evolved into a mobile education practice that is emanating from progress in the speed of internet connection, and the development of mobile devices.

With the emergence of pandemic (Covid-19), face to face education has almost been put to a halt, and online education has gained significant importance. The Microsoft management team declared to have 750 users involved in the online education activities on the 10 th March, just before the pandemic; however, on March 24, they informed that the number of users increased significantly, reaching the number of 138,698 users (OECD, 2020 ). This event supports the view that it is better to commonly use online education rather than using it as a traditional alternative educational tool when students do not have the opportunity to have a face to face education (Geostat, 2019 ). The period of Covid-19 pandemic has emerged as a sudden state of having limited opportunities. Face to face education has stopped in this period for a long time. The global spread of Covid-19 affected more than 850 million students all around the world, and it caused the suspension of face to face education. Different countries have proposed several solutions in order to maintain the education process during the pandemic. Schools have had to change their curriculum, and many countries supported the online education practices soon after the pandemic. In other words, traditional education gave its way to online education practices. At least 96 countries have been motivated to access online libraries, TV broadcasts, instructions, sources, video lectures, and online channels (UNESCO, 2020 ). In such a painful period, educational institutions went through online education practices by the help of huge companies such as Microsoft, Google, Zoom, Skype, FaceTime, and Slack. Thus, online education has been discussed in the education agenda more intensively than ever before.

Although online education approaches were not used as comprehensively as it has been used recently, it was utilized as an alternative learning approach in education for a long time in parallel with the development of technology, internet and computers. The academic achievement of the students is often aimed to be promoted by employing online education approaches. In this regard, academicians in various countries have conducted many studies on the evaluation of online education approaches and published the related results. However, the accumulation of scientific data on online education approaches creates difficulties in keeping, organizing and synthesizing the findings. In this research area, studies are being conducted at an increasing rate making it difficult for scientists to be aware of all the research outside of their ​​expertise. Another problem encountered in the related study area is that online education studies are repetitive. Studies often utilize slightly different methods, measures, and/or examples to avoid duplication. This erroneous approach makes it difficult to distinguish between significant differences in the related results. In other words, if there are significant differences in the results of the studies, it may be difficult to express what variety explains the differences in these results. One obvious solution to these problems is to systematically review the results of various studies and uncover the sources. One method of performing such systematic syntheses is the application of meta-analysis which is a methodological and statistical approach to draw conclusions from the literature. At this point, how effective online education applications are in increasing the academic success is an important detail. Has online education, which is likely to be encountered frequently in the continuing pandemic period, been successful in the last ten years? If successful, how much was the impact? Did different variables have an impact on this effect? Academics across the globe have carried out studies on the evaluation of online education platforms and publishing the related results (Chiao et al., 2018 ). It is quite important to evaluate the results of the studies that have been published up until now, and that will be published in the future. Has the online education been successful? If it has been, how big is the impact? Do the different variables affect this impact? What should we consider in the next coming online education practices? These questions have all motivated us to carry out this study. We have conducted a comprehensive meta-analysis study that tries to provide a discussion platform on how to develop efficient online programs for educators and policy makers by reviewing the related studies on online education, presenting the effect size, and revealing the effect of diverse variables on the general impact.

There have been many critical discussions and comprehensive studies on the differences between online and face to face learning; however, the focus of this paper is different in the sense that it clarifies the magnitude of the effect of online education and teaching process, and it represents what factors should be controlled to help increase the effect size. Indeed, the purpose here is to provide conscious decisions in the implementation of the online education process.

The general impact of online education on the academic achievement will be discovered in the study. Therefore, this will provide an opportunity to get a general overview of the online education which has been practiced and discussed intensively in the pandemic period. Moreover, the general impact of online education on academic achievement will be analyzed, considering different variables. In other words, the current study will allow to totally evaluate the study results from the related literature, and to analyze the results considering several cultures, lectures, and class levels. Considering all the related points, this study seeks to answer the following research questions:

What is the effect size of online education on academic achievement?

How do the effect sizes of online education on academic achievement change according to the moderator variable of the country?

How do the effect sizes of online education on academic achievement change according to the moderator variable of the class level?

How do the effect sizes of online education on academic achievement change according to the moderator variable of the lecture?

How do the effect sizes of online education on academic achievement change according to the moderator variable of the online education approaches?

This study aims at determining the effect size of online education, which has been highly used since the beginning of the pandemic, on students’ academic achievement in different courses by using a meta-analysis method. Meta-analysis is a synthesis method that enables gathering of several study results accurately and efficiently, and getting the total results in the end (Tsagris & Fragkos, 2018 ).

2.1 Selecting and coding the data (studies)

The required literature for the meta-analysis study was reviewed in July, 2020, and the follow-up review was conducted in September, 2020. The purpose of the follow-up review was to include the studies which were published in the conduction period of this study, and which met the related inclusion criteria. However, no study was encountered to be included in the follow-up review.

In order to access the studies in the meta-analysis, the databases of Web of Science, ERIC, and SCOPUS were reviewed by utilizing the keywords ‘online learning and online education’. Not every database has a search engine that grants access to the studies by writing the keywords, and this obstacle was considered to be an important problem to be overcome. Therefore, a platform that has a special design was utilized by the researcher. With this purpose, through the open access system of Cukurova University Library, detailed reviews were practiced using EBSCO Information Services (EBSCO) that allow reviewing the whole collection of research through a sole searching box. Since the fundamental variables of this study are online education and online learning, the literature was systematically reviewed in the related databases (Web of Science, ERIC, and SCOPUS) by referring to the keywords. Within this scope, 225 articles were accessed, and the studies were included in the coding key list formed by the researcher. The name of the researchers, the year, the database (Web of Science, ERIC, and SCOPUS), the sample group and size, the lectures that the academic achievement was tested in, the country that the study was conducted in, and the class levels were all included in this coding key.

The following criteria were identified to include 225 research studies which were coded based on the theoretical basis of the meta-analysis study: (1) The studies should be published in the refereed journals between the years 2020 and 2021, (2) The studies should be experimental studies that try to determine the effect of online education and online learning on academic achievement, (3) The values of the stated variables or the required statistics to calculate these values should be stated in the results of the studies, and (4) The sample group of the study should be at a primary education level. These criteria were also used as the exclusion criteria in the sense that the studies that do not meet the required criteria were not included in the present study.

After the inclusion criteria were determined, a systematic review process was conducted, following the year criterion of the study by means of EBSCO. Within this scope, 290,365 studies that analyze the effect of online education and online learning on academic achievement were accordingly accessed. The database (Web of Science, ERIC, and SCOPUS) was also used as a filter by analyzing the inclusion criteria. Hence, the number of the studies that were analyzed was 58,616. Afterwards, the keyword ‘primary education’ was used as the filter and the number of studies included in the study decreased to 3152. Lastly, the literature was reviewed by using the keyword ‘academic achievement’ and 225 studies were accessed. All the information of 225 articles was included in the coding key.

It is necessary for the coders to review the related studies accurately and control the validity, safety, and accuracy of the studies (Stewart & Kamins, 2001 ). Within this scope, the studies that were determined based on the variables used in this study were first reviewed by three researchers from primary education field, then the accessed studies were combined and processed in the coding key by the researcher. All these studies that were processed in the coding key were analyzed in accordance with the inclusion criteria by all the researchers in the meetings, and it was decided that 27 studies met the inclusion criteria (Atici & Polat, 2010 ; Carreon, 2018 ; Ceylan & Elitok Kesici, 2017 ; Chae & Shin, 2016 ; Chiang et al. 2014 ; Ercan, 2014 ; Ercan et al., 2016 ; Gwo-Jen et al., 2018 ; Hayes & Stewart, 2016 ; Hwang et al., 2012 ; Kert et al., 2017 ; Lai & Chen, 2010 ; Lai et al., 2015 ; Meyers et al., 2015 ; Ravenel et al., 2014 ; Sung et al., 2016 ; Wang & Chen, 2013 ; Yu, 2019 ; Yu & Chen, 2014 ; Yu & Pan, 2014 ; Yu et al., 2010 ; Zhong et al., 2017 ). The data from the studies meeting the inclusion criteria were independently processed in the second coding key by three researchers, and consensus meetings were arranged for further discussion. After the meetings, researchers came to an agreement that the data were coded accurately and precisely. Having identified the effect sizes and heterogeneity of the study, moderator variables that will show the differences between the effect sizes were determined. The data related to the determined moderator variables were added to the coding key by three researchers, and a new consensus meeting was arranged. After the meeting, researchers came to an agreement that moderator variables were coded accurately and precisely.

2.2 Study group

27 studies are included in the meta-analysis. The total sample size of the studies that are included in the analysis is 1772. The characteristics of the studies included are given in Table 1 .

2.3 Publication bias

Publication bias is the low capability of published studies on a research subject to represent all completed studies on the same subject (Card, 2011 ; Littell et al., 2008 ). Similarly, publication bias is the state of having a relationship between the probability of the publication of a study on a subject, and the effect size and significance that it produces. Within this scope, publication bias may occur when the researchers do not want to publish the study as a result of failing to obtain the expected results, or not being approved by the scientific journals, and consequently not being included in the study synthesis (Makowski et al., 2019 ). The high possibility of publication bias in a meta-analysis study negatively affects (Pecoraro, 2018 ) the accuracy of the combined effect size, causing the average effect size to be reported differently than it should be (Borenstein et al., 2009 ). For this reason, the possibility of publication bias in the included studies was tested before determining the effect sizes of the relationships between the stated variables. The possibility of publication bias of this meta-analysis study was analyzed by using the funnel plot, Orwin’s Safe N Analysis, Duval and Tweedie’s Trip and Fill Analysis, and Egger’s Regression Test.

2.4 Selecting the model

After determining the probability of publication bias of this meta-analysis study, the statistical model used to calculate the effect sizes was selected. The main approaches used in the effect size calculations according to the differentiation level of inter-study variance are fixed and random effects models (Pigott, 2012 ). Fixed effects model refers to the homogeneity of the characteristics of combined studies apart from the sample sizes, while random effects model refers to the parameter diversity between the studies (Cumming, 2012 ). While calculating the average effect size in the random effects model (Deeks et al., 2008 ) that is based on the assumption that effect predictions of different studies are only the result of a similar distribution, it is necessary to consider several situations such as the effect size apart from the sample error of combined studies, characteristics of the participants, duration, scope, and pattern of the study (Littell et al., 2008 ). While deciding the model in the meta-analysis study, the assumptions on the sample characteristics of the studies included in the analysis and the inferences that the researcher aims to make should be taken into consideration. The fact that the sample characteristics of the studies conducted in the field of social sciences are affected by various parameters shows that using random effects model is more appropriate in this sense. Besides, it is stated that the inferences made with the random effects model are beyond the studies included in the meta-analysis (Field, 2003 ; Field & Gillett, 2010 ). Therefore, using random effects model also contributes to the generalization of research data. The specified criteria for the statistical model selection show that according to the nature of the meta-analysis study, the model should be selected just before the analysis (Borenstein et al., 2007 ; Littell et al., 2008 ). Within this framework, it was decided to make use of the random effects model, considering that the students who are the samples of the studies included in the meta-analysis are from different countries and cultures, the sample characteristics of the studies differ, and the patterns and scopes of the studies vary as well.

2.5 Heterogeneity

Meta-analysis facilitates analyzing the research subject with different parameters by showing the level of diversity between the included studies. Within this frame, whether there is a heterogeneous distribution between the studies included in the study or not has been evaluated in the present study. The heterogeneity of the studies combined in this meta-analysis study has been determined through Q and I 2 tests. Q test evaluates the random distribution probability of the differences between the observed results (Deeks et al., 2008 ). Q value exceeding 2 value calculated according to the degree of freedom and significance, indicates the heterogeneity of the combined effect sizes (Card, 2011 ). I 2 test, which is the complementary of the Q test, shows the heterogeneity amount of the effect sizes (Cleophas & Zwinderman, 2017 ). I 2 value being higher than 75% is explained as high level of heterogeneity.

In case of encountering heterogeneity in the studies included in the meta-analysis, the reasons of heterogeneity can be analyzed by referring to the study characteristics. The study characteristics which may be related to the heterogeneity between the included studies can be interpreted through subgroup analysis or meta-regression analysis (Deeks et al., 2008 ). While determining the moderator variables, the sufficiency of the number of variables, the relationship between the moderators, and the condition to explain the differences between the results of the studies have all been considered in the present study. Within this scope, it was predicted in this meta-analysis study that the heterogeneity can be explained with the country, class level, and lecture moderator variables of the study in terms of the effect of online education, which has been highly used since the beginning of the pandemic, and it has an impact on the students’ academic achievement in different lectures. Some subgroups were evaluated and categorized together, considering that the number of effect sizes of the sub-dimensions of the specified variables is not sufficient to perform moderator analysis (e.g. the countries where the studies were conducted).

2.6 Interpreting the effect sizes

Effect size is a factor that shows how much the independent variable affects the dependent variable positively or negatively in each included study in the meta-analysis (Dinçer, 2014 ). While interpreting the effect sizes obtained from the meta-analysis, the classifications of Cohen et al. ( 2007 ) have been utilized. The case of differentiating the specified relationships of the situation of the country, class level, and school subject variables of the study has been identified through the Q test, degree of freedom, and p significance value Fig.  1 and 2 .

3 Findings and results

The purpose of this study is to determine the effect size of online education on academic achievement. Before determining the effect sizes in the study, the probability of publication bias of this meta-analysis study was analyzed by using the funnel plot, Orwin’s Safe N Analysis, Duval and Tweedie’s Trip and Fill Analysis, and Egger’s Regression Test.

When the funnel plots are examined, it is seen that the studies included in the analysis are distributed symmetrically on both sides of the combined effect size axis, and they are generally collected in the middle and lower sections. The probability of publication bias is low according to the plots. However, since the results of the funnel scatter plots may cause subjective interpretations, they have been supported by additional analyses (Littell et al., 2008 ). Therefore, in order to provide an extra proof for the probability of publication bias, it has been analyzed through Orwin’s Safe N Analysis, Duval and Tweedie’s Trip and Fill Analysis, and Egger’s Regression Test (Table 2 ).

Table 2 consists of the results of the rates of publication bias probability before counting the effect size of online education on academic achievement. According to the table, Orwin Safe N analysis results show that it is not necessary to add new studies to the meta-analysis in order for Hedges g to reach a value outside the range of ± 0.01. The Duval and Tweedie test shows that excluding the studies that negatively affect the symmetry of the funnel scatter plots for each meta-analysis or adding their exact symmetrical equivalents does not significantly differentiate the calculated effect size. The insignificance of the Egger tests results reveals that there is no publication bias in the meta-analysis study. The results of the analysis indicate the high internal validity of the effect sizes and the adequacy of representing the studies conducted on the relevant subject.

In this study, it was aimed to determine the effect size of online education on academic achievement after testing the publication bias. In line with the first purpose of the study, the forest graph regarding the effect size of online education on academic achievement is shown in Fig.  3 , and the statistics regarding the effect size are given in Table 3 .

The flow chart of the scanning and selection process of the studies

Funnel plot graphics representing the effect size of the effects of online education on academic success

Forest graph related to the effect size of online education on academic success

The square symbols in the forest graph in Fig.  3 represent the effect sizes, while the horizontal lines show the intervals in 95% confidence of the effect sizes, and the diamond symbol shows the overall effect size. When the forest graph is analyzed, it is seen that the lower and upper limits of the combined effect sizes are generally close to each other, and the study loads are similar. This similarity in terms of study loads indicates the similarity of the contribution of the combined studies to the overall effect size.

Figure  3 clearly represents that the study of Liu and others (Liu et al., 2018 ) has the lowest, and the study of Ercan and Bilen ( 2014 ) has the highest effect sizes. The forest graph shows that all the combined studies and the overall effect are positive. Furthermore, it is simply understood from the forest graph in Fig.  3 and the effect size statistics in Table 3 that the results of the meta-analysis study conducted with 27 studies and analyzing the effect of online education on academic achievement illustrate that this relationship is on average level (= 0.409).

After the analysis of the effect size in the study, whether the studies included in the analysis are distributed heterogeneously or not has also been analyzed. The heterogeneity of the combined studies was determined through the Q and I 2 tests. As a result of the heterogeneity test, Q statistical value was calculated as 29.576. With 26 degrees of freedom at 95% significance level in the chi-square table, the critical value is accepted as 38.885. The Q statistical value (29.576) counted in this study is lower than the critical value of 38.885. The I 2 value, which is the complementary of the Q statistics, is 12.100%. This value indicates that the accurate heterogeneity or the total variability that can be attributed to variability between the studies is 12%. Besides, p value is higher than (0.285) p = 0.05. All these values [Q (26) = 29.579, p = 0.285; I2 = 12.100] indicate that there is a homogeneous distribution between the effect sizes, and fixed effects model should be used to interpret these effect sizes. However, some researchers argue that even if the heterogeneity is low, it should be evaluated based on the random effects model (Borenstein et al., 2007 ). Therefore, this study gives information about both models. The heterogeneity of the combined studies has been attempted to be explained with the characteristics of the studies included in the analysis. In this context, the final purpose of the study is to determine the effect of the country, academic level, and year variables on the findings. Accordingly, the statistics regarding the comparison of the stated relations according to the countries where the studies were conducted are given in Table 4 .

As seen in Table 4 , the effect of online education on academic achievement does not differ significantly according to the countries where the studies were conducted in. Q test results indicate the heterogeneity of the relationships between the variables in terms of countries where the studies were conducted in. According to the table, the effect of online education on academic achievement was reported as the highest in other countries, and the lowest in the US. The statistics regarding the comparison of the stated relations according to the class levels are given in Table 5 .

As seen in Table 5 , the effect of online education on academic achievement does not differ according to the class level. However, the effect of online education on academic achievement is the highest in the 4 th class. The statistics regarding the comparison of the stated relations according to the class levels are given in Table 6 .

As seen in Table 6 , the effect of online education on academic achievement does not differ according to the school subjects included in the studies. However, the effect of online education on academic achievement is the highest in ICT subject.

The obtained effect size in the study was formed as a result of the findings attained from primary studies conducted in 7 different countries. In addition, these studies are the ones on different approaches to online education (online learning environments, social networks, blended learning, etc.). In this respect, the results may raise some questions about the validity and generalizability of the results of the study. However, the moderator analyzes, whether for the country variable or for the approaches covered by online education, did not create significant differences in terms of the effect sizes. If significant differences were to occur in terms of effect sizes, we could say that the comparisons we will make by comparing countries under the umbrella of online education would raise doubts in terms of generalizability. Moreover, no study has been found in the literature that is not based on a special approach or does not contain a specific technique conducted under the name of online education alone. For instance, one of the commonly used definitions is blended education which is defined as an educational model in which online education is combined with traditional education method (Colis & Moonen, 2001 ). Similarly, Rasmussen ( 2003 ) defines blended learning as “a distance education method that combines technology (high technology such as television, internet, or low technology such as voice e-mail, conferences) with traditional education and training.” Further, Kerres and Witt (2003) define blended learning as “combining face-to-face learning with technology-assisted learning.” As it is clearly observed, online education, which has a wider scope, includes many approaches.

As seen in Table 7 , the effect of online education on academic achievement does not differ according to online education approaches included in the studies. However, the effect of online education on academic achievement is the highest in Web Based Problem Solving Approach.

4 Conclusions and discussion

Considering the developments during the pandemics, it is thought that the diversity in online education applications as an interdisciplinary pragmatist field will increase, and the learning content and processes will be enriched with the integration of new technologies into online education processes. Another prediction is that more flexible and accessible learning opportunities will be created in online education processes, and in this way, lifelong learning processes will be strengthened. As a result, it is predicted that in the near future, online education and even digital learning with a newer name will turn into the main ground of education instead of being an alternative or having a support function in face-to-face learning. The lessons learned from the early period online learning experience, which was passed with rapid adaptation due to the Covid19 epidemic, will serve to develop this method all over the world, and in the near future, online learning will become the main learning structure through increasing its functionality with the contribution of new technologies and systems. If we look at it from this point of view, there is a necessity to strengthen online education.

In this study, the effect of online learning on academic achievement is at a moderate level. To increase this effect, the implementation of online learning requires support from teachers to prepare learning materials, to design learning appropriately, and to utilize various digital-based media such as websites, software technology and various other tools to support the effectiveness of online learning (Rolisca & Achadiyah, 2014 ). According to research conducted by Rahayu et al. ( 2017 ), it has been proven that the use of various types of software increases the effectiveness and quality of online learning. Implementation of online learning can affect students' ability to adapt to technological developments in that it makes students use various learning resources on the internet to access various types of information, and enables them to get used to performing inquiry learning and active learning (Hart et al., 2019 ; Prestiadi et al., 2019 ). In addition, there may be many reasons for the low level of effect in this study. The moderator variables examined in this study could be a guide in increasing the level of practical effect. However, the effect size did not differ significantly for all moderator variables. Different moderator analyzes can be evaluated in order to increase the level of impact of online education on academic success. If confounding variables that significantly change the effect level are detected, it can be spoken more precisely in order to increase this level. In addition to the technical and financial problems, the level of impact will increase if a few other difficulties are eliminated such as students, lack of interaction with the instructor, response time, and lack of traditional classroom socialization.

In addition, COVID-19 pandemic related social distancing has posed extreme difficulties for all stakeholders to get online as they have to work in time constraints and resource constraints. Adopting the online learning environment is not just a technical issue, it is a pedagogical and instructive challenge as well. Therefore, extensive preparation of teaching materials, curriculum, and assessment is vital in online education. Technology is the delivery tool and requires close cross-collaboration between teaching, content and technology teams (CoSN, 2020 ).

Online education applications have been used for many years. However, it has come to the fore more during the pandemic process. This result of necessity has brought with it the discussion of using online education instead of traditional education methods in the future. However, with this research, it has been revealed that online education applications are moderately effective. The use of online education instead of face-to-face education applications can only be possible with an increase in the level of success. This may have been possible with the experience and knowledge gained during the pandemic process. Therefore, the meta-analysis of experimental studies conducted in the coming years will guide us. In this context, experimental studies using online education applications should be analyzed well. It would be useful to identify variables that can change the level of impacts with different moderators. Moderator analyzes are valuable in meta-analysis studies (for example, the role of moderators in Karl Pearson's typhoid vaccine studies). In this context, each analysis study sheds light on future studies. In meta-analyses to be made about online education, it would be beneficial to go beyond the moderators determined in this study. Thus, the contribution of similar studies to the field will increase more.

The purpose of this study is to determine the effect of online education on academic achievement. In line with this purpose, the studies that analyze the effect of online education approaches on academic achievement have been included in the meta-analysis. The total sample size of the studies included in the meta-analysis is 1772. While the studies included in the meta-analysis were conducted in the US, Taiwan, Turkey, China, Philippines, Ireland, and Georgia, the studies carried out in Europe could not be reached. The reason may be attributed to that there may be more use of quantitative research methods from a positivist perspective in the countries with an American academic tradition. As a result of the study, it was found out that the effect size of online education on academic achievement (g = 0.409) was moderate. In the studies included in the present research, we found that online education approaches were more effective than traditional ones. However, contrary to the present study, the analysis of comparisons between online and traditional education in some studies shows that face-to-face traditional learning is still considered effective compared to online learning (Ahmad et al., 2016 ; Hamdani & Priatna, 2020 ; Wei & Chou, 2020 ). Online education has advantages and disadvantages. The advantages of online learning compared to face-to-face learning in the classroom is the flexibility of learning time in online learning, the learning time does not include a single program, and it can be shaped according to circumstances (Lai et al., 2019 ). The next advantage is the ease of collecting assignments for students, as these can be done without having to talk to the teacher. Despite this, online education has several weaknesses, such as students having difficulty in understanding the material, teachers' inability to control students, and students’ still having difficulty interacting with teachers in case of internet network cuts (Swan, 2007 ). According to Astuti et al ( 2019 ), face-to-face education method is still considered better by students than e-learning because it is easier to understand the material and easier to interact with teachers. The results of the study illustrated that the effect size (g = 0.409) of online education on academic achievement is of medium level. Therefore, the results of the moderator analysis showed that the effect of online education on academic achievement does not differ in terms of country, lecture, class level, and online education approaches variables. After analyzing the literature, several meta-analyses on online education were published (Bernard et al., 2004 ; Machtmes & Asher, 2000 ; Zhao et al., 2005 ). Typically, these meta-analyzes also include the studies of older generation technologies such as audio, video, or satellite transmission. One of the most comprehensive studies on online education was conducted by Bernard et al. ( 2004 ). In this study, 699 independent effect sizes of 232 studies published from 1985 to 2001 were analyzed, and face-to-face education was compared to online education, with respect to success criteria and attitudes of various learners from young children to adults. In this meta-analysis, an overall effect size close to zero was found for the students' achievement (g +  = 0.01).

In another meta-analysis study carried out by Zhao et al. ( 2005 ), 98 effect sizes were examined, including 51 studies on online education conducted between 1996 and 2002. According to the study of Bernard et al. ( 2004 ), this meta-analysis focuses on the activities done in online education lectures. As a result of the research, an overall effect size close to zero was found for online education utilizing more than one generation technology for students at different levels. However, the salient point of the meta-analysis study of Zhao et al. is that it takes the average of different types of results used in a study to calculate an overall effect size. This practice is problematic because the factors that develop one type of learner outcome (e.g. learner rehabilitation), particularly course characteristics and practices, may be quite different from those that develop another type of outcome (e.g. learner's achievement), and it may even cause damage to the latter outcome. While mixing the studies with different types of results, this implementation may obscure the relationship between practices and learning.

Some meta-analytical studies have focused on the effectiveness of the new generation distance learning courses accessed through the internet for specific student populations. For instance, Sitzmann and others (Sitzmann et al., 2006 ) reviewed 96 studies published from 1996 to 2005, comparing web-based education of job-related knowledge or skills with face-to-face one. The researchers found that web-based education in general was slightly more effective than face-to-face education, but it is insufficient in terms of applicability ("knowing how to apply"). In addition, Sitzmann et al. ( 2006 ) revealed that Internet-based education has a positive effect on theoretical knowledge in quasi-experimental studies; however, it positively affects face-to-face education in experimental studies performed by random assignment. This moderator analysis emphasizes the need to pay attention to the factors of designs of the studies included in the meta-analysis. The designs of the studies included in this meta-analysis study were ignored. This can be presented as a suggestion to the new studies that will be conducted.

Another meta-analysis study was conducted by Cavanaugh et al. ( 2004 ), in which they focused on online education. In this study on internet-based distance education programs for students under 12 years of age, the researchers combined 116 results from 14 studies published between 1999 and 2004 to calculate an overall effect that was not statistically different from zero. The moderator analysis carried out in this study showed that there was no significant factor affecting the students' success. This meta-analysis used multiple results of the same study, ignoring the fact that different results of the same student would not be independent from each other.

In conclusion, some meta-analytical studies analyzed the consequences of online education for a wide range of students (Bernard et al., 2004 ; Zhao et al., 2005 ), and the effect sizes were generally low in these studies. Furthermore, none of the large-scale meta-analyzes considered the moderators, database quality standards or class levels in the selection of the studies, while some of them just referred to the country and lecture moderators. Advances in internet-based learning tools, the pandemic process, and increasing popularity in different learning contexts have required a precise meta-analysis of students' learning outcomes through online learning. Previous meta-analysis studies were typically based on the studies, involving narrow range of confounding variables. In the present study, common but significant moderators such as class level and lectures during the pandemic process were discussed. For instance, the problems have been experienced especially in terms of eligibility of class levels in online education platforms during the pandemic process. It was found that there is a need to study and make suggestions on whether online education can meet the needs of teachers and students.

Besides, the main forms of online education in the past were to watch the open lectures of famous universities and educational videos of institutions. In addition, online education is mainly a classroom-based teaching implemented by teachers in their own schools during the pandemic period, which is an extension of the original school education. This meta-analysis study will stand as a source to compare the effect size of the online education forms of the past decade with what is done today, and what will be done in the future.

Lastly, the heterogeneity test results of the meta-analysis study display that the effect size does not differ in terms of class level, country, online education approaches, and lecture moderators.

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Ulum, H. The effects of online education on academic success: A meta-analysis study. Educ Inf Technol 27 , 429–450 (2022). https://doi.org/10.1007/s10639-021-10740-8

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Students’ perceptions on distance education: A multinational study

• Patricia Fidalgo 1 ,
• Joan Thormann 2 ,
• Oleksandr Kulyk 3 &
• 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.

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

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Online Survey Questions

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

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

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

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

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

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

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

8. What is the students’ age;

9. What is the students’ gender;

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

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

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DOI : https://doi.org/10.1186/s41239-020-00194-2

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• Distance education
• Multinational study
• Perceptions of distance education
• Undergraduate students

Impact of Online Classes on Students Essay

• Introduction
• Thesis Statement

Background study

• Impacts of online education

Introduction to Online Education

Online learning is one of the new innovative study methods that have been introduced in the pedagogy field. In the last few years, there has been a great shift in the training methods. Students can now learn remotely using the internet and computers.

Online learning comes in many forms and has been developing with the introduction of new technologies. Most universities, high schools, and other institutions in the world have all instituted this form of learning, and the student population in the online class is increasing fast. There has been a lot of research on the impacts of online education as compared to ordinary classroom education.

If the goal is to draw a conclusion of online education, considerable differences between the online learning environment and classroom environment should be acknowledged. In the former, teachers and students don’t meet physically as opposed to the latter, where they interact face to face. In this essay, the challenges and impact of online classes on students, teachers, and institutions involved were examined.

Thesis Statement about Online Classes

Thus, the thesis statement about online classes will be as follows:

Online learning has a positive impact on the learners, teachers, and the institution offering these courses.

Online learning or E learning is a term used to describe various learning environments that are conducted and supported by the use of computers and the internet. There are a number of definitions and terminologies that are used to describe online learning.

These include E learning, distance learning, and computer learning, among others (Anon, 2001). Distant learning is one of the terminologies used in E learning and encompasses all learning methods that are used to train students that are geographically away from the training school. Online learning, on the other hand, is used to describe all the learning methods that are supported by the Internet (Moore et al., 2011).

Another terminology that is used is E learning which most authors have described as a learning method that is supported by the use of computers, web-enabled communication, and the use of new technological tools that enhance communication (Spector, 2008). Other terminologies that are used to describe this form of online learning are virtual learning, collaborative learning, web-based learning, and computer-supported collaborative learning (Conrad, 2006).

Impacts of Online Classes on Students

Various studies and articles document the merits, demerits, and challenges of online studies. These studies show that online study is far beneficial to the students, teachers, and the institution in general and that the current challenges can be overcome through technological advancement and increasing efficiency of the learning process.

One of the key advantages of online learning is the ability of students to study in their own comfort. For a long time, students had to leave their comfort areas and attend lectures. This change in environment causes a lack of concentration in students. In contrast, E-learning enables the students to choose the best environment for study, and this promotes their ability to understand. As a result, students enjoy the learning process as compared to conventional classroom learning.

Another benefit is time and cost savings. Online students are able to study at home, and this saves them travel and accommodation costs. This is in contrast with the classroom environment, where learners have to pay for transport and accommodation costs as well as any other costs associated with the learning process.

Online study has been found to reduce the workload on the tutors. Most of the online notes and books are availed to the students, and this reduces the teacher’s workload. Due to the availability of teaching materials online, tutors are not required to search for materials. Teachers usually prepare lessons, and this reduces the task of training students over and over again.

Accessibility to learning materials is another benefit of online learning. Students participating in online study have unlimited access to learning materials, which gives them the ability to study effectively and efficiently. On the other hand, students in the classroom environment have to take notes as the lecture progress, and these notes may not be accurate as compared to the materials uploaded on the websites.

Unlimited resources are another advantage of online study. Traditionally, learning institutions were limited in the number of students that could study in the classroom environment. The limitations of facilities such as lecture theaters and teachers limited student enrollment in schools (Burgess & Russell, 2003).

However, with the advent of online studies, physical limitations imposed by classrooms, tutors, and other resources have been eliminated. A vast number of students can now study in the same institution and be able to access the learning materials online. The use of online media for training enables a vast number of students to access materials online, and this promotes the learning process.

Promoting online study has been found by most researchers to open the students to vast resources that are found on the internet. Most of the students in the classroom environment rely on the tutors’ notes and explanations for them to understand a given concept.

However, students using the web to study most of the time are likely to be exposed to the vast online educational resources that are available. This results in the students gaining a better understanding of the concept as opposed to those in the classroom environment (Berge & Giles, 2008).

An online study environment allows tutors to update their notes and other materials much faster as compared to the classroom environment. This ensures that the students receive up-to-date information on a given study area.

One of the main benefits of E-learning to institutions is the ability to provide training to a large number of students located in any corner of the world. These students are charged training fees, and this increases the money available to the institution. This extra income can be used to develop new educational facilities, and these will promote education further (Gilli et al., 2002).

Despite the many advantages that online study has in transforming the learning process, there are some challenges imposed by the method. One of the challenges is the technological limitations of the current computers, which affect the quality of the learning materials and the learning process in general.

Low download speed and slow internet connectivity affect the availability of learning materials. This problem is, however, been reduced through the application of new software and hardware elements that have high access speeds. This makes it easier to download learning materials and applications. As computing power increases, better and faster computers are being unveiled, and these will enable better access to online study facilities.

Another disadvantage of online learning as compared to the classroom environment is the lack of feedback from the students. In the classroom environment, students listen to the lecture and ask the tutors questions and clarifications any issues they didn’t understand. In the online environment, the response by the teacher may not be immediate, and students who don’t understand a given concept may find it hard to liaise with the teachers.

The problem is, however, been circumvented by the use of simple explanation methods, slideshows, and encouraging discussion forums between the teachers and students. In the discussion forums, students who don’t understand a concept can leave a comment or question, which will be answered by the tutor later.

Like any other form of learning, online studies have a number of benefits and challenges. It is, therefore, not logical to discredit online learning due to the negative impacts of this training method. Furthermore, the benefits of e-learning far outweigh the challenges.

Conclusion about Online Education

In culmination, a comparative study between classroom study and online study was carried out. The study was done by examining the findings recorded in books and journals on the applicability of online learning to students. The study revealed that online learning has many benefits as compared to conventional learning in the classroom environment.

Though online learning has several challenges, such as a lack of feedback from students and a lack of the proper technology to effectively conduct online learning, these limitations can be overcome by upgrading the E-Leaning systems and the use of online discussion forums and new web-based software.

In conclusion, online learning is beneficial to the students, tutors, and the institution offering these courses. I would therefore recommend that online learning be implemented in all learning institutions, and research on how to improve this learning process should be carried out.

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Conrad, D. (2006). E-Learning and social change, Perspectives on higher education in the digital age . New York: Nova Science Publishers.

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

• Chi-chung Foo   ORCID: orcid.org/0000-0001-8849-6597 1 ,
• Billy Cheung 2 &
• Kent-man Chu   ORCID: orcid.org/0000-0002-0332-4321 1  

BMC Medical Education volume  21 , Article number:  141 ( 2021 ) Cite this article

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

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

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

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

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

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

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

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

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

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

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

Mean PBL scores according to tutors

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

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

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

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

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

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

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

Availability of data and materials

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

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

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

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