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

Wassnaa al-mawee.

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

Keneth Morgan Kwayu

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

Tasnim Gharaibeh

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

1. Introduction

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

2. Related work

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

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

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

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

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

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

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

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

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

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

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

4.1. Data collection procedure

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

4.2. Participants

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

Participants’ gender and age by college level,

Participants’ gender and age by college type,

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

4.3. Measures

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

Measures for distance learning,

Measures for instructional methods,

5. Statistical Methods

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

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

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

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

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

6.1. Students’ perceptions of distance learning

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

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

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

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

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

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

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

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

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

6.2. Students’ perceptions of instructional methods

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

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

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

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

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

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

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

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

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

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

6.3. Textual exploratory analysis

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

Students’ experience of distance learning: Textual exploratory analysis,

7. Discussion

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

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

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

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

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

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

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

8. Conclusions

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

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

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

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

Conflict of Interest

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Perceived Effectiveness of Self Learning Modules in the Implementation of Modular Distance Learning in the Elementary Level

84 Pages Posted: 17 Aug 2021

Emerson Natividad

Felix T. Pascual Elementary School

Date Written: May 2021

The COVID-19 pandemic shifts the traditional classroom or face-to-face teaching and learning into distance learning. The district of Sto. Domingo implemented Modular Distance Learning(MDL) in which a self-learning module(SLM) is the primary tool in the teaching and learning process. This study determines the effectiveness of the SLM in the implementation of MDL at the elementary level under the new normal. The study is anchored on Moore’s Transactional Distance Theory. Descriptive correlational statistics were used to determine the factors contributing to the effectiveness of SLM in the implementation of MDL. The respondents were the 72 Grade 3 and Grade 6 permanent teachers and 72 Grades 3 and 6 learners. Factors such as the SLM quality of content, usability, and teacher interventions were analyzed to determine if they were predictors of the SLM's perceived effectiveness. The perceived effectiveness of the SLM was evaluated by teachers and learners. Teachers and learners agree to the perceived effectiveness as a teaching and learning tool of the SLM in the implementation of MDL. Using Pearson-r, the study found that quality of content, usability, and teacher implemented intervention was positively correlated to the perceived effectiveness of SLM based on teacher evaluation. Multiple regression analysis found that quality of content and usability predict the effectiveness of SLM in the implementation of MDL based on teacher evaluation. The study concludes that the quality of content and usability of the SLM will most likely determine the perceived effectiveness of the SLM in the implementation of MDL on this scale and magnitude during this time of the pandemic. Learner evaluation of the perceived effectiveness of the SLM did not show a causal relationship with the SLM quality of content, usability, and teachers’ implemented interventions. The result suggests that learners may not fully understand the context of their learning to evaluate their learning using the SLM. The study recommends the importance of the quality of content and usability of the materials particularly the SLM to effectively implement the MDL during this time of pandemic and in this scale and magnitude. While teacher implemented interventions have a positive relationship or effect on the use of SLM, it does not predict its effectiveness. Further, the study suggests the development of assessment materials and procedures to measure the actual achievement of learners under the MDL.

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Felix t. pascual elementary school ( email ).

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Distance Learning: Theory and Practice

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Distance Learning: Advantages and Limitations Essay

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Introduction

A shift from classroom to distance learning: advantages and limitations, theories of distance learning, advantages of distance learning, disadvantages of distance learning, works cited.

The theme of this study chose distance learning, which is relevant in connection with the recent coronavirus pandemic. After the searches, the three most relevant articles were selected. Namely: University Students Online Learning System During Covid-19 Pandemic: Advantages, Constraints and Solutions by Purwanto, which covers all the aspects of distance learning in terms of coronavirus (570).

Indonesia Education Readiness Conducting Distance Learning in Covid-19 Pandemic Situation by Churiyah et al. represents the Indonesian government’s attitude to this phenomenon (491). Moreover, in A Shift from Classroom to Distance Learning: Advantages and Limitations by Sadeghi, the author discusses distance learning in all its terms (80).

All three articles cover the topic of distance learning in the context of the coronavirus and everyday practice. However, Sadeghi’s article seems to be the most priority among all three articles, as it reveals this topic in a pros and cons format that is understandable to everyone.

This article consists of distance learning theory, its history, and its advantages and disadvantages. The article’s primary purpose is to familiarize itself since it does not prove anything but explains the complex in simple language. The author states that students participating in distance education may not always be present at a school (Sadeghi 80). In other words, students learn and pass their chosen subjects online without visiting a testing facility, a college campus, or a university building. The question of whether the provided education is as effective as it could be is raised because of its popularization.

The same is valid for online education, just as no single learning theory has been developed for instruction in general. Many theories have developed based on the significant learning theories we previously covered. The convergence of four overlapping lenses — community-centeredness, knowledge-centeredness, learner-centeredness, and assessment-centeredness — is one of the theories discussed in this section of the article (Sadeghi 82). These lenses served as the framework for the author’s strategy for researching an online education theory because they considered the qualities and resources the Internet offers about each of the four lenses. The author also pointed out how all types of media are now supported and readily available on the Internet, which formerly existed only as a text-based environment (Sadeghi 82). They also correctly noted that the linking function of the Internet is best suited to how human information is stored and accessed.

Speaking of the advantages of distance learning, the author suggests that remote learning may not be ideal for some students, and there will be a list of disadvantages. The best thing about remote learning is that one can take it anytime and anywhere. According to Sadeghi, a distance education degree earned online or through another method may be significantly less expensive for any given program than an on-campus degree (Sadeghi 83). Thus, one of the advantages is the lower cost of higher education in this format. The author also points out that forms of distance learning enable students to design their learning schedules at their leisure rather than adhering to a fixed course of study (Sadeghi 83). These three advantages can be called the most significant since they are most very distinguishable by remote education from traditional one.

While more people have the chance to pursue higher education due to distance learning, there are also some drawbacks. According to the author, the likelihood of being distracted and forgetting deadlines is considered when there is no teacher for face-to-face interaction and no classmates to assist with ongoing reminders about pending work (Sadeghi 84). Additionally, because training is done online, there is almost no physical interaction between students and instructors.

In conclusion, the author states that while distance learning programs and courses are here to stay and will grow in the future, many unclear concerns still need to be defined and looked at. The author believes that the other significant issue is that employers still favor traditional college or university degrees over those obtained through online or remote learning. Summing up, one can note the deep work carried out in the study of the concepts of distance learning.

Sadeghi, Manijeh. “ A shift from classroom to distance learning: Advantages and limitations .” International Journal of Research in English Education , vol. 4, no. 1, 2019, pp. 80–88., Web.

Churiyah, Madziatul, et al. “ Indonesia Education Readiness Conducting Distance Learning in Covid-19 Pandemic Situation .” International Journal of Multicultural and Multireligious Understanding, vol. 7, no. 6, 2020, p. 491., Web.

Purwanto, Agus. “ University Students Online Learning System during COVID-19 Pandemic: Advantages, Constraints, and Solutions .” Sys Rev Pharm, vol. 11, no. 7, pp. 570–576., Web.

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IvyPanda. (2024, January 26). Distance Learning: Advantages and Limitations. https://ivypanda.com/essays/distance-learning-advantages-and-limitations/

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IvyPanda . 2024. "Distance Learning: Advantages and Limitations." January 26, 2024. https://ivypanda.com/essays/distance-learning-advantages-and-limitations/.

1. IvyPanda . "Distance Learning: Advantages and Limitations." January 26, 2024. https://ivypanda.com/essays/distance-learning-advantages-and-limitations/.

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• Research article
• Open access
• Published: 29 October 2020

Student perspective of classroom and distance learning during COVID-19 pandemic in the undergraduate dental study program Universitas Indonesia

• Lisa R. Amir 1 , 2 ,
• Ira Tanti 1 , 3 ,
• Diah Ayu Maharani 4 ,
• Yuniardini Septorini Wimardhani 5 ,
• Vera Julia 6 ,
• Benso Sulijaya 7 &
• Ria Puspitawati 1 , 2  

BMC Medical Education volume  20 , Article number:  392 ( 2020 ) Cite this article

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The COVID-19 pandemic has become a global health issue and has had a major impact on education. Consequently, half way through the second semester of the academic year 2019/2020, learning methods were delivered through distance learning (DL). We aimed to evaluate the student perspective of DL compared to classroom learning (CL) in the undergraduate dentistry study program at the Faculty of Dentistry Universitas Indonesia.

An online questionnaire was sent at the end of the semester. A total of 301 students participated in the study.

Duration of study influenced student preference. Higher number of first-year students preferred DL compared to their seniors ( p  < 0.001). Students preferred CL for group discussion, as DL resulted in more difficult communication and gave less learning satisfaction. Only 44.2% students preferred DL over CL, although they agreed that DL gave a more efficient learning method (52.6%), it provided more time to study (87.9%) and to review study materials (87.3%). Challenges during DL included external factors such as unstable internet connection, extra financial burden for the internet quota and internal factors such as time management and difficulty to focus while learning online for a longer period of time.

Despite some challenges, dental students could adapt to the new learning methods of full DL and the majorities agreed blended learning that combined classroom and distance learning can be implemented henceforth. This current COVID-19 pandemic, changes not only the utilization of technology in education but the pedagogy strategies in the future.

Peer Review reports

The World Health Organization has declared the pandemic of the novel SARS-CoV2 infection early this year and it has now become a major public health challenge worldwide [ 1 ]. The infection control and physical distancing measures are crucial to prevent the virus from further spreading and to help control the pandemic situation. The policy of compulsory physical distancing has been implemented in many countries including in Indonesia [ 2 , 3 ], resulting in nationwide school and university closures. In accordance with this policy, dental academic institutions are compelled to make appropriate and timely modification in order to continue to deliver education and to sustain the continuation of student academic progress. The teaching and learning activities were immediately shifted to a full E-learning.

E-learning is defined as learning that makes use of Information and Communication Technologies (ICTs). The incorporation of technological resources and innovative education strategies has transformed the teaching and learning processes. Previous studies have shown various e-learning and online learning tools that are effective for teaching and learning in the fields of health profession, including dentistry [ 4 , 5 , 6 , 7 , 8 ]. The knowledge gain and performance of the students as a result of E-learning were shown to be equivalent to that of face to face methods [ 9 , 10 ]. Blended learning is mainly defined as the integration of classroom and distance learning to facilitate an independent, interactive and collaborative learning among students. However, to understand it in a more general perspective, blended learning approach redesign courses that are developed, scheduled and implemented through a combination of physical and virtual learning activities. It was previously reported that blended learning provides better student’s satisfaction, motivation, student engagement and performance [ 5 , 7 , 11 , 12 ]. This approach promotes active and self-directed learning and has gained acceptance in dental education as a complementary method to traditional learning.

The undergraduate curriculum of the Faculty of Dentistry Universitas Indonesia adopted Student Centered Active Learning (SCAL) using collaborative learning, question-based learning or Problem-Based Learning (PBL) since 2003. In PBL, students work in groups to construct content knowledge and develop self-directed learning skills. The activities along the steps of the chosen learning methods (group discussions, clarification sessions, the laboratory works and skills lab) were all conducted in classroom learning with online support. The university E-learning management system (LMS) was utilized to facilitate various teaching and learning activities at different academic levels in the undergraduate dental program. The organization of courses, access to resources and additional learning materials are available through LMS to support self-directed learning within an integrated PBL curriculum. During this COVID-19 pandemic, courses delivered in student-centered learning methods were immediately moved to full E-learning. In the first half of semester before the pandemic, group discussions, clarification sessions and interactive lectures were carried out in-campus classroom learning while in the second half of semester, learning activities were delivered in full distance learning employing various online meeting platforms. In order to make the format of discussion sessions stay similar as it had been conducted before the pandemic, every online session was delivered synchronously with the attendance of a facilitator in each group. Students and facilitators’ time spent on setting or accomplishing tasks was similar as in classroom learning.

Despite previous reports on the comparison of classroom and distance learning [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ], the evaluation on the student-centered active learning approaches that are delivered through blended learning methods compared to full online learning has not been widely available. The majorities of studies on distance learning method reported student perception of virtual learning modules that were integrated with classroom learning. Student feedback could provide important information for the evaluation of distance learning so as to improve future learning strategies. Therefore, the study aimed to analyze student perspective of SCAL delivered through full distance learning compared to the classroom learning in the undergraduate dentistry study program. An online questionnaire was distributed to the undergraduate dental students at the end of semester. We hypothesized students positive outcomes on the acceptance of distance learning as a new learning strategy that was implemented during COVID-19 pandemic condition.

Sampling procedures and participants

This study was performed from May to June 2020. Study participants were the first, second and third-year of undergraduate students of the dentistry study program at the Faculty of Dentistry Universitas Indonesia. The online questionnaire was given at the end of semester. They were strongly encouraged to fill out the questionnaire but their participation remained voluntary. The name and other personal information of the study participants were protected. Dental Research Ethics Committee Faculty of Dentistry Universitas Indonesia approved the study in accordance with the Helsinki Declaration (6/EA/FKGUI/VI/2020). Students were informed about the study and signed consent form.

Learning methods

Before COVID-19 pandemic, learning strategies in the dentistry academic study program (pre-clinical) at the Faculty of Dentistry Universitas Indonesia was student-centered active learning. Collaborative learning (CL) and question-based learning (QBL) approaches were mainly used in the courses of the earlier semesters such as basic oral biology and introduction of health and dental science courses for the first-year dental students. Problem-based Learning (PBL) was mainly used in the courses of the latter semesters such as clinical dental science courses for the second and third-year dental students. The group discussions of these active learning approaches and lectures for clarification were delivered in classroom learning. Each group discussion consisted of 10–13 students and was supervised by 1 facilitator/tutor. Universitas Indonesia web-based education tools (EMAS, Moodle-based learning management system) was used to support various learning activities. Students could access the syllabus, learning objectives of each studied courses as well as scenarios/list of sub-topics or questions, list of references through the EMAS system and this learning approach represents blended learning.

As the COVID-19 pandemic protocol forced the compulsory work and study from home policy, since March 17, 2020, courses with CL, QBL and PBL methods were transferred to full distance learning. Group discussions, clarification lectures and assessments were carried out using various online platforms (Microsoft Teams, Google meets, Zoom and EMAS). Practice class and skills lab courses in which the expected learning outcomes involved various psychomotor skills were either substituted with video simulation, and or live and presented the stages of work online or postponed until the university is ready to be opened for the face-to-face classroom learning.

Questionnaire

The questionnaire was developed to assess [ 1 ] the student’s perception of the distance learning method. The response options of the questionnaire items represent 4 Likert-type scales (0 = strongly disagree to 3 = strongly agree), except for questions of the most effective methods for distance learning (six options of the format of online learning) and open questions for the challenges and positive experience during distance learning. Altogether there were 22 statements in four parts: (A) general information on the student’s gender, year of study and GPA; (B) Preference; (C) Effectiveness, and; (D) Learning satisfaction.

Statistical analysis

The internal consistency reliability questionnaire was measured by Cronbach’s alpha. Descriptive statistics were computed and bivariate analyses were performed. Logistic regression analyses were conducted to identify factors associated with the students’ preference towards distance learning. The level of statistical significance was at 0.05.

General information

A total of 301 undergraduate first-, second- and third-year dental students of the Faculty of Dentistry Universitas Indonesia participated in the study. The response rate was 84.3%. Most of the participants were female (85.1%) and it reflects the majority of our undergraduate dental students (Table  1 ). Cronbach alpha of the questionnaire was 0.880. The Cronbach’s alpha coefficients of each domain were above 0.8, which was considered satisfactory. No CITC value was lower than 0.30, which allowed all items to be included in the instrument.

Preference domain

The total mean preference score was 20.3 ± 5.9, ranging from 2 to 36. Majorities of students (75.1%) agreed on the importance of classroom learning interaction for group discussion. Year of study influenced student’s perception toward distance learning. First-year students have a higher preference towards distance learning compared to their seniors ( p  < 0.001). There was no significant correlation between gender or grade point average (GPA) on students’ preference of learning methods (Table 1 ). Most students (87.4%) preferred synchronized learning sessions for group discussions and clarification sessions. Moreover, 58.8% students shared their concern on the online exams results, due to potential dishonesty of students.

Effectiveness domain

Students perceived to have more learning time with the distance learning, although technical constraints still existed when doing distance learning (Table  2 ). Only 34.2% of students did not experience problems during distance learning. Data from open questions of the challenges during distance learning revealed the majority of the problems were categorized as external factors such as unstable internet connection and extra financial burden for internet quota. Other challenges related to internal factors included student readiness to the new learning method, time management and difficulties to focus while learning through the computer for a long period of time. These challenges might be contributed to the stress experienced by 35.2% students during distance learning (Table 2 ).

Learning satisfaction domain

The results of logistic regression confirmed the suitability, preferability, communication, sustainability, efficiency, satisfaction and motivation were significant factors related to the students’ preference towards distance learning (Table  3 ). Overall, efficiency has the highest odds ratio in relation to preference towards distance learning. However, 61.7% students disagreed that distance learning gave similar learning satisfaction to classroom learning.

Correlation

The correlations between each 12 variables were shown in Table  4 . Item sub-scale correlations ranged from 0.140–0.763, indicating the multidimensionality of the questionnaire scale. Strong correlation was observed between sufficient time to prepare lessons and sufficient time to review the study materials in distance learning and efficiency related to motivation. Correlations were all significant at the p  < 0.05 level.

The COVID-19 pandemic has brought the unprecedented universities’s facilities closure, it affected millions of students worldwide. The sudden transformation in the teaching and learning activities into virtual modalities was carried out in order to continue the academic courses while avoiding people gathering and the potential risk of the spread of infection. The present study documented the student perspective of student-centered active learning delivered through full distance learning since March 17, 2020 and compared to the classroom learning in the undergraduate dentistry study program. Full distance learning whereby group discussions were carried out synchronously through the online communication platforms is a new learning method that has not been previously implemented in our dental school. This study was the first to compare the student perceptions on both types of learning methods related to the preference, effectiveness and learning satisfaction reported during the COVID-19 pandemic condition.

The survey demonstrated 44.2% students preferred distance learning over classroom learning. This result was lower than other studies comparing online and traditional learning methods which reported higher preference toward e-learning compared to traditional classroom methods [ 5 , 13 , 14 ]. Student’s attitude and acceptance toward e-learning has been shown to be more positive and favorable. However, in these studies the virtual learning modules were integrated with classroom learning, while in the present study, the distance learning was delivered in full online. It was previously reported that full online learning offers a sense of unreality and it largely depends on the students commitment to the courses [ 15 ]. Bridges and colleagues suggested the integration of learning technologies with face-to-face teaching to support access to digital resources and to enhance the visualization [ 16 ]. Blended PBL structured similarly as traditional PBL while offering the ability to use online communication tools and online environment to share materials. These differences in the learning methods and the new learning strategy experienced by our dental students might explain the lower percentage of students preferred full distance learning observed in this study.

In this study, the preference on learning methods was influenced by the year of study. Among students who preferred distance learning, the percentage of freshman students was significantly higher than the seniors. Similarly, studies conducted by Sritongthaworn et al. (2006) and Teo at al (2011) reported that younger students tend to adapt to e-learning [ 17 , 18 ]. One of the factors that contribute to this finding might be related to the curriculum implemented at the time of this study. Senior dental students learned more clinical dental science courses which involve both theory and procedural knowledge and skills. Essentially such courses require laboratory skill sessions to enhance the understanding of the learned subjects. As the execution of dental laboratory works and practical was postponed due to the university closure, this resulted in the lack of motoric skills experiences, less chance of direct consultation with the instructors and less practical assignments that were normally served as the reinforcement to the theory class. While the curriculum of first-year dental students studied more basic dental science courses which are mostly conceptual theories so that the content knowledge acquisition could still be re-enforced by laboratory activities based on online tutorial and exercises in form of video or photographs. It is well comprehended that dental education can not be carried on the same way as medical education. The reason of this difference is that the dental students requires adequate physical setting and psychomotor skills, even since in the academic years, and that could not be replaced by distance learning strategy as being conducted during the pandemic [ 2 ].

Beside the necessary preparedness of students in distance learning methods, other factors such as personality types may influence student preference for e-learning than classroom learning [ 19 , 20 , 21 ]. As the personality regulates how individuals perceive, make judgements and react in certain situations. The acceptance of students for e-learning is commonly associated with self regulation character. Self regulatory behavior includes the ability to set goals, effective time management, problem solving capacity, and awareness of time to seek advice from instructors [ 20 , 21 , 22 ]. On top of self regulatory behavior, constraint of self efficacy, e-learning motivation, and high task value are other factors which strengthen the blended/online learning preference [ 21 , 22 ]. It is interesting to note that despite the lower percentage of distance learning preference observed in this study, students agreed that distance learning could motivate them to prepare the learning materials before group discussion.

Logistic regression analysis confirmed efficiency has the highest odds ratio in relation to preference towards distance learning. Moreover, students recognized there was more time to study and to review study material in distance learning. Such results are in line with previous studies which has been demonstrated that distance learning offers higher flexibility of place of study process, saving time and cost since commuting from and to campus is no longer needed [ 23 ]. Well designed distance learning gives more time for students to access more topics and unlimited information. Such advantage suits the learning process of medical and dental students in recent decades since they have to digest increased loads of new and kept updated topics [ 5 ].

Apart from its obvious advantages, distance learning also brings some disadvantages. Increased chances of distraction, complicated technology, limited social interaction, and increased difficulty to stay in contact with instructors are several conditions that might interfere with the success of distance learning [ 24 ]. The present study showed more students felt lower learning satisfaction and more difficult communication either with instructors or with peer students in doing distance learning. Internal factors challenges of student readiness to distance learning, time management and difficulty to stay focused for long online learning duration were reported. Besides the students internal factor as mentioned above, other categories of distance learning barriers were also present in the time and environment when this study was conducted. The performance of instructors in charge in the distance learning process of this study were varied in their interactive pedagogy ability, uplifting spirit, and confidence toward utilization of innovative learning. Self efficacy character is importantly demanded not only from students but also from instructors. The quality of teaching is very important in stimulating students’ satisfaction. Special attention to communicate with students is essential since lack of personal contact may affect the development of trust [ 22 , 23 ]. Peer to peer communication and interaction in a group discussion are not often feasible in the virtual learning method. The barriers associated with infra-structure were obviously also encountered by the students complaining about unstable internet connection and extra financial burden for internet quota. Moreover, stress experienced by one-third of the participants of the study might have an impact on student perspective toward learning method. Recent study also reported students concerned on the issues of economic slowdown, potential academic delay and changes in daily life and these were associated with the level of anxiety of the college student in China during this pandemic time [ 24 ].

The present study demonstrated important findings that are essential for the improvement and development of learning strategies in the future. However, this study had some limitations. First, the generalizability of the study was limited by the use of data from a single university. Second, although students were encouraged to take part in this study, their participation was voluntary. The response rate of 84.3% was below the 90% response rate that was initially targeted. The number of non-respondents may therefore have undermined the power of the study and the potential response bias can not be completely ruled out [ 25 ]. The results of the study must therefore be interpreted with caution. Third, the study focused on the preclinical students as its respondents, while the more challenging adaptation in learning strategy in dentistry during the pandemic is critically faced by the clinical students in the profession program. Forth, the questionnaire used in this study only measured student perception. It was unclear how student academic performance was affected by distance learning strategy, whether there were any difficulties encountered by students in understanding course learning outcomes, particularly for senior-year students who received clinical dental science courses and have lower preference toward distance learning. Previously, it was reported a weak correlation between the student perception of learning with the actual gain of knowledge [ 26 ]. Student perception may not reflect student understanding of course learning outcomes. Therefore, assessing the impact of distance learning on student academic performance is as crucial for the evaluation of curriculum transformation. This should be further investigated. Despite these limitations, the results of this study offer valuable information on the current perspectives of dental students with regard to full distance learning methods implemented during the COVID-19 pandemic. As student acceptance of learning method play an important role in creating an effective learning environment [ 27 , 28 ]. Due to the uncertainty in this COVID-19 pandemic time, whereby the situation is still changes, it is essential to design the learning method that is most suited to current situation and to have appropriate plan once it is permissible for classroom teaching to resume its activities, taken into consideration all the necessary protocols for safety and health protection [ 29 ].

The study presented evidence that despite some challenges, undergraduate dental students could adapt to the new learning methods of distance learning and agreed on better efficiency experienced in distance learning than in classroom learning. This sudden closure of the university globally due to COVID-19 pandemic, albeit undesirable, presents an enormous opportunity for cultural transformation in the education system. As more “tech-savvy” generations enroll in higher education, dental educators need to incorporate blended learning in the curriculum, to design the best features of classroom and distance learning to improve the overall learning environment.

Availability of data and materials

All of the relevant raw data of this study will be available from Ria Puspitawati (corresponding author) for scientists who wish to use them for non-commercial purposes.

Abbreviations

Corrected Item Total Corrections

Classroom Learning

Distance Learning

E-learning management system

Problem-based Learning

Question-Based Learning

Student Centered Active Learning

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Acknowledgments

The authors thank the Dean Faculty of Dentistry Universitas Indonesia (Prof. Lindawati Kusdhany) for supporting study and Vice Dean of education and research Faculty of Dentistry Universitas Indonesia (Prof. Ellyza Herda) for her invaluable comments for this study.

Universitas Indonesia supported the publication of this study. Grant number for LA: #NKB-1609/UN2.RST/HKP.05.00/2020.

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Dental Education Unit, Faculty of Dentistry, Universitas Indonesia, Jakarta, Indonesia

Lisa R. Amir, Ira Tanti & Ria Puspitawati

Department of Oral Biology, Faculty of Dentistry, Universitas Indonesia, Jakarta, Indonesia

Lisa R. Amir & Ria Puspitawati

Department of Prosthodontics, Faculty of Dentistry, Universitas Indonesia, Jakarta, Indonesia

Department of Preventive and Public Health Dentistry, Faculty of Dentistry, Universitas Indonesia, Jakarta, Indonesia

Diah Ayu Maharani

Department of Oral Medicine, Faculty of Dentistry, Universitas Indonesia, Jakarta, Indonesia

Yuniardini Septorini Wimardhani

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Contributions

LA: contributed to the study concept, study design, data analysis, data interpretation and writing the manuscript. IT: contributed to the study concept, study design, data analysis, writing the manuscript. DAM: contributed to design of study, data analysis, writing the manuscript. YW: contributed to design of study, data analysis, writing the manuscript. VJ: contributed to design of study, data analysis, writing the manuscript. BS: contributed to design of study, data analysis, writing the manuscript. RP: contributed to the study concept, study design, data analysis, data interpretation and writing the manuscript. All authors read and approved the final manuscript.

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Correspondence to Ria Puspitawati .

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Students participated voluntarily in the study following the official invitation. Data confidentiality was protected. Dental Research Ethics Committee Faculty of Dentistry Universitas Indonesia approved the study in accordance with the Helsinki Declaration (Ethical Approval Letter No.6/EA/FKGUI/VI/2020). Students were informed about the study and signed consent form.

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Amir, L.R., Tanti, I., Maharani, D.A. et al. Student perspective of classroom and distance learning during COVID-19 pandemic in the undergraduate dental study program Universitas Indonesia. BMC Med Educ 20 , 392 (2020). https://doi.org/10.1186/s12909-020-02312-0

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How the Education Department Wants to Police Online Education

The department says it needs more data about online education to hold those programs accountable. Institutions say the agency is overcorrecting.

By  Katherine Knott

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More than half of U.S. students took at least one online class in the 2022–23 academic year. The Education Department is proposing a number of changes to gather more data about how students fare in those courses.

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The Education Department wants to collect much more information about distance education courses and the students enrolled in them as part of a broader effort to increase oversight of online programs.

The department’s proposal would require colleges and universities to take attendance in distance education classes, which include those offered online or via correspondence. Institutions also would have to provide more information to the agency about those classes’ enrollment. Additionally, the department proposes to end any asynchronous options for students in online clock-hour programs, which are typically workforce training programs that lead to a certificate.

The proposed changes worry some higher education groups, which say they could hamper innovation, unfairly target online classes and limit access for students who could benefit from the flexibility that online education provides. The department and advocates say the new regulations are needed to ensure oversight of online education—which increased during and following the pandemic—and track the outcomes of students in those programs. In the 2022–23 academic year, about 53 percent of U.S. students enrolled in at least one online course.

Edward Conroy, a senior policy manager at New America, a left-leaning think tank, said the additional data will shed light on whether the programs are effective—and for which students.

“Schools should want this information, because if it’s not proving to be effective, then we need to find ways to improve it,” he said. “I don’t think online education is going away, and so if it’s going to be part of our lives, then we need to make it good.”

The proposals are part of a package of draft regulations that also include provisions to open up a federal college-prep program to undocumented students. The regulations were posted on the Federal Register last week and are open for public comments until Aug. 23. If they are finalized and issued before Nov. 1, they would take effect by July 1 of next year.

With this package and other regulatory changes still in the works , the Biden administration is aiming to better protect students and give them greater control over how their financial aid is used, while increasing oversight regarding colleges. Critics say the changes reflect the Education Department’s growing skepticism of the quality of online education and whether these programs pay off for students.

Jordan DiMaggio, vice president of policy and digital strategy at UPCEA, the online and professional education association, said that the department’s goals are laudable, but this proposal and other actions raise questions about the agency’s motivations.

“There’s questions on whether the department is truly focused on protecting students’ outcomes and taxpayer dollars,” he said. “Or do they kind of reveal an antiquated bias against online education that’s framed by some suspicion and distrust of the field as a whole?”

He added that the department’s rationale for some of the changes seems to be rooted in the assumption that online education is bad—and is drawing from data from the early days of the pandemic, when universities quickly switched to remote instruction.

“It sort of feels like using last month’s weather forecast to plan today’s outfit,” he said. “We’re looking at the worst of the worst in a time when [some] institutions had no idea how to teach online … We’re in a vastly different place.”

What the Department Wants to Change

The department says it’s simply trying to ensure that students are getting what they pay for with distance education programs. The various changes will help the department “better measure and account for student outcomes, improve oversight over distance education and ensure students are receiving effective education,” according to the proposed regulations. One big change: Colleges would be required to create a virtual location to house all their programs that are offered entirely online or through correspondence, which would have to be approved by accreditors and state officials.

In 2022–23, a little over 3,700 institutions of higher education offered at least one distance education course. But current federal reporting requirements don’t distinguish between on-campus programs and those offered online or in a hybrid format. The department also can’t tell how much federal financial aid is going specifically to distance education programs. To address that information gap, the department is proposing new reporting requirements related to distance education enrollment along with the virtual location.

The reporting requirements would require colleges to break down whether students enrolled in a distance education course are fully online or hybrid, though the specific details have yet to be determined.

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Next, all distance education courses will have to take attendance as part of a proposal to more accurately determine when a student withdraws from a program, except for doctoral dissertation research courses. That withdrawal date is key to calculating how much federal financial aid should be returned to the government by either the institution or the student. The department says the proposal will help students better pay down any balance owed after they withdraw while simplifying the calculation for institutions.

DiMaggio and others said that implementing the attendance requirement will be complicated and likely require more systematic changes to institutions’ learning management systems and other software. The department is underestimating the difficulty institutions will face in complying, they say.

The department expects an institution to spend about 10 hours to initially implement the attendance requirement and then about 10 minutes a day to capture the necessary information for their records. The agency estimates that about half of the institutions offering distance education courses are already taking attendance.

“Institutions can often easily determine when students stop attending because a school’s systems can often identify when students submit assignments or interact with instructors and students during lectures and course discussions,” officials wrote.

DiMaggio said he doesn’t think that’s the case. “And many of our institutions have indicated to us that that’s not the case,” he added.

Another key change in this package rolls back a 2020 rule change that allowed asynchronous learning activities—such as watching a prerecorded video—to count toward the required number of clock hours in a distance education course. Clock-hour programs tend to be shorter term and career focused, requiring hands-on instruction to prepare students for employment in a certain field.

The 2020 change “puts students and taxpayers at risk,” officials wrote in the proposed rule, citing its oversight and compliance activities. Officials added that “asynchronous learning in clock-hour programs has often consisted of playing videos, reading assignments or scrolling through pages,” which results in a “substandard education” for students. Additionally, students have told the agency that a lack of direct engagement with instructors “hampered their ability to obtain the skills necessary to pass certification exams or obtain a job in their field.”

The department believes that “very few institutions” would be affected, though it doesn’t have data about how many programs include asynchronous elements.

Conroy of New America said that the changes to the distance education regulations reflect the “huge shift in how people go through higher education.” That includes more students enrolling in a mix of in-person and online classes.

“If that’s going to be a big part of how higher education is delivered, we need to know what’s happening with it, and we need to be able to provide students who enroll solely online with similar or the same protections if something goes sideways, as we do for students who enroll in person,” he said.

‘Needs to Be a Better Solution’

Critics of the proposal say that the department is making unnecessary and sweeping decisions in response to some bad practices, particularly when it comes to the changes to asynchronous learning activities in clock-hour programs.

“They’re right that there’s some really bad practices out there, but they’ve also said themselves that there are institutions that have spent a lot of money and spent a lot of time and effort in order to make sure that they’re right,” said Russell Poulin, executive director of the Western Interstate Commission for Higher Education’s Cooperative for Educational Technologies, or WCET. “There needs to be a better solution than this one.”

Poulin and others at WCET say the proposed changes will make it more complicated for institutions to offer distance education rather than simplifying processes. For example, complying with the attendance requirement is more complicated than just “counting noses.” For distance education, it’s not just a question of whether a student showed up or logged in but also whether they participated in the class. That would have to be determined by the faculty member reviewing a student’s file, they said, and measures of academic engagement could vary depending on how the class is structured.

“There are loads of little processes that get put into this that’s far from simplification,” Poulin said.

Emmanual Guillory, senior director of government relations at the American Council on Education, said that eliminating asynchronous instruction in the clock-hour programs could hinder students considered nontraditional, such as parents.

“Because they can do it at their own pace,” he said. “They’re working two or three jobs. They’re trying to support their families in whatever ways, and they don’t have the luxury to have a carved-out time every week to go sit in the classroom with their peers and learn. What you’re doing is you are limiting the ability of these students to access postsecondary education by using student aid funding, and this could have a huge impact on low-income students.”

Guillory added that the other changes, from the attendance requirement to the virtual location, will likely mean that colleges—some of which are already underresourced—will have to expend more resources and manpower to comply.

“It just adds more stress and burden upon the men and women on our campuses that are really trying to best produce quality academic programming, ensure teaching and learning on campuses, and it’s just more red tape that they have to deal with,” he said.

Funding Student Success: Boosting Undergrad Teaching Grants

Rice University promotes innovation among undergraduate faculty through a $60,000 annual grant.

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Advocacy Alert: USDE Releases Proposed Amendments for Distance Education, Return of Title IV Funds, and Federal TRIO Programs

The United States Department of Education has released proposed amendments to regulations regarding Distance Education, Return of Title IV, and Federal TRIO Programs. Members of the public will have until August 23, 2024, to submit comments.

As part of the Middle States Commission on Higher Education’s (MSCHE) strategic priority to promote advocacy initiatives for its members and others, we encourage our constituents to submit comments on the proposed regulations. The Federal Register includes instructions on how to submit comments through the Federal eRulemaking Portal.

Distance Education

The Department proposes to amend the definitions of several terms. The amended definition of additional location would include virtual locations for programs that are 100 percent online. The revised definition of clock hour excludes asynchronous coursework via distance education from the coursework that may apply to a student’s eligibility for Title IV funds. In addition, USDE proposes that only asynchronous coursework offered in credit-hour programs can count toward the definition of academic year . Lastly, the Department proposes to require institutions to report distance education or correspondence course enrollment.  

Return of Title IV Funds

USDE proposes several changes in regard to Return of Title IV funds. These changes include new borrowing terms and new procedures and processes for student withdrawal.  

Federal TRIO Programs

The Department proposes expanded student access to five of the nine Federal TRIO programs: Educational Opportunity Centers, Talent Search, Upward Bound, Upward Bound Math-Science, and Veterans Upward Bound.  

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Doctoral Thesis: Geometric Learning for Manipulating Scenes and Objects

By: Anthony Simeonov

Thesis Supervisors: Pulkit Agrawal and Alberto Rodriguez

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Abstract: Enabling robots to perform practical tasks in the real world requires that they be equipped with a general sense of geometric intelligence. This thesis aims to (i) understand components of geometric intelligence that are missing from current systems and (ii) propose techniques to close some of these gaps. The developed insights and techniques enable new capabilities in robotic manipulation, focusing on rigid object rearrangement tasks in real, unmodeled scenes.

First, I will discuss how the learned features of an equivariant neural field, trained offline to perform 3D reconstruction from point clouds, can be re-purposed as a representation for data-efficient manipulation with unseen objects in out-of-distribution poses. This is achieved by casting skill imitation as aligning coordinate frames detected near task-relevant object parts. The neural field representation encodes the relevant parts to detect using a few task demonstrations and supports localizing frames near the corresponding parts on new shapes. I will also present applications of our neural descriptor fields for capturing pairwise relations between object parts and chaining such relations to perform multi-step tasks. Next, I will show how rearrangement among multi-object scenes leads to additional challenges, such as generalizing to diverse scene layouts and covering the multi-modal space of rearrangement solutions. I will discuss how predicting combined object-scene 3D point clouds by de-noising relative object poses with diffusion models naturally handles these unique challenges. Finally, I will share recent results on learning closed-loop visuomotor policies that support rearrangement task execution with increased reliability and robustness by combining simulation-based reinforcement learning (sim-to-real) and 3D reconstruction (real-to-sim).

Zoom link: https://mit.zoom.us/j/94948381154

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Project 2025 Director Steps Down Amid Trump Criticism

Paul Dans oversaw the project for the Heritage Foundation, a conservative think tank behind the proposal to reshape the federal government. Democrats have used the plans to attack Donald Trump, who has sought to distance himself from it.

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By Neil Vigdor and Shane Goldmacher

• July 30, 2024

The director of Project 2025 , the right-wing policy blueprint and personnel project prepared for the next Republican president that became a political cudgel used by Democrats, is departing after the effort drew criticism from former President Donald J. Trump.

The project, which has been a collaborative effort across the conservative ecosystem led by the Heritage Foundation, has become a lightning rod on the 2024 campaign trail. The group had spent months developing an expansive set of policies, and the president of the Heritage Foundation said on Tuesday it was concluding its drafting of new ideas as planned.

“When we began Project 2025 in April 2022, we set a timeline for the project to conclude its policy drafting after the two party conventions this year, and we are sticking to that timeline,” Kevin Roberts, the president of the Heritage Foundation, said in a statement praising Paul Dans, the outgoing director.

Mr. Trump has tried to distance himself from the specifics inside the 900-page plan for months, saying the sweeping agenda to reshape the federal government is not his, though many of the proposals were crafted by people who served in the first Trump administration.

“It’s a group of very, very conservative people. And they wrote a document that many of the points are fine. Many of the points are absolutely ridiculous,” Mr. Trump said in an interview on Fox News last week. During the same interview, he insisted he had “never seen” the plan and had “nothing to do with” it.

President Biden, and now Vice President Kamala Harris, have repeatedly used some of the less popular planks to attack Mr. Trump. Ms. Harris brings up Project 2025 during almost every campaign stop. At a fund-raiser this weekend, she described it as “a plan that would return America to a very dark past.”

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