An analysis of students' perspectives on e-learning participation – the case of COVID-19 pandemic
International Journal of Information and Learning Technology
ISSN : 2056-4880
Article publication date: 17 May 2021
Issue publication date: 24 June 2021
During the COVID-19 pandemic, educational institutions were forced to shut down, causing massive disruption of the education system. This paper aims to determine the critical factors for the intention to participate in e-learning during COVID-19.
Design/methodology/approach
Data were collected by surveying 131 university students and structural equation modelling technique using PLS-SEM was employed to analysis the data.
The results showed that the COVID-19 related factors such as perceived challenges and COVID-19 awareness not only directly impact students' intention but also such effects are mediated through perceived usefulness and perceived ease of use of e-learning systems. However, the results showed that the educational institution's preparedness does not directly impact the intention of students to participate in e-learning during COVID-19. The results also showed that the gender and length of the use of e-learning systems impact students' e-learning systems use.
Originality/value
These results demonstrated that, regardless of how well the educational institutions are prepared to promote the use of e-learning systems, other COVID-19-related challenges play a crucial role in forming the intention of students to participate in e-learning during the COVID-19 pandemic. Theoretical and practical implications are provided.
- Distance learning
- Higher education
- Online education
Nikou, S. and Maslov, I. (2021), "An analysis of students' perspectives on e-learning participation – the case of COVID-19 pandemic", International Journal of Information and Learning Technology , Vol. 38 No. 3, pp. 299-315. https://doi.org/10.1108/IJILT-12-2020-0220
Emerald Publishing Limited
Copyright © 2021, Shahrokh Nikou and Ilia Maslov
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
The COVID-19 pandemic is the defining global health crisis of our time, and it is adding a fair amount of complexity in how different activities are being conducted ( Adnan and Anwar, 2020 ). Such effects are crucial on higher education, forcing all teaching and learning activities to face a sudden transition to wholly online learning contexts ( Toquero, 2020 ). While the educational environments are still struggling with the digitalisation and digital transformation challenges and finding optimal ways to adapt, the Coronavirus pandemic has fundamentally affected their core: staff and students ( Adedoyin and Soykan, 2020 ; Aristovnik et al. , 2020 ; Strauß and Rummel, 2020 ). For them, the period is inevitably very stressful as all learning and teaching activities – e.g. all classes, meetings, seminars, supervisions and exams were forced to move online within short notice ( Bao, 2020 ; Hodges et al. , 2020 ). Though such transformation is not entirely new for such institutions, they are all now forced to move away from traditional teaching and learning structures to a virtual environment as old education models are no longer adaptable to the challenges of rapidly changing educational environments ( Van Nuland et al. , 2020 ).
In the educational environments, information and communications technology (ICT) has been extensively used to deliver information for education and learning, and e-learning has been an emerging paradigm of modern education ( Sun et al. , 2008 ). E-learning relies on the use of multiple information systems, services and technologies. Information system encompasses information service and information technology (IT), where service is understood as the use of IT. Furthermore, the user experience (UX) and usability of information technology and services also affect e-learning process, not only the technical aspects, but also the social aspects ( Nakamura et al. , 2017 ). Given the relatively recent events in terms of COVID-19 and quarantine situation worldwide, e-learning has become increasingly important as one of the optimal solutions for education ( Radha et al. , 2020 ). We argue that in order to understand better factors influencing individual decision to participate in e-learning in a worldwide quarantine situation, comprehensive research with a holistic approach is needed. Hence, we aim to address this issue by assessing students' experience in their participation in e-learning. Based on this aim, the research question guides this study is What antecedent factors impact students ' intention to participate in e-learning during the COVID-19 quarantine? To answer the stated research question, we develop an integrated theoretical model that encompasses several antecedent factors (perceived challenges during COVID-19, school and teachers' perceived preparedness) and constructs from Technology Acceptance Model (TAM: Davis, 1989 ), perceived usefulness and perceived ease of use ( Yu, 2020 ). We conduct empirical research and collect data through an online survey questionnaire, focusing on university students as the target group. The data will be analysed through structural equation modelling (SEM) using SmartPLS v. 3.
The rest of this paper is structured as follows: Section 2 presents the literature review with the operationalisation of the required terminology and theoretical framework for the study. Section 3 provides the theoretical framework and hypotheses. Section 4 describes the methodology, research design, and data collection. Section 5 provides the results followed by Section 6 , providing discussions. Section 7 concludes the research and outlines the limitations and recommendations for future research.
2. Literature review
2.1 e-learning and participation in e-learning concepts.
To support e-learning, learning management systems (LMS) is increasingly being used, which are e-learning software that can be used to empower teachers to enrich students' learning ( Bansode and Kumbhar, 2012 , p. 415). LMS is a powerful software system enhancing learning and provides automated delivery of the course content and tracking of the learning progress of the students ( Dalsgaard, 2006 ). Sun et al. (2008 , p. 1183) defined e-learning as the use of telecommunication to deliver information for education and training. Garrison and Anderson (2003) defined e-learning participation as teaching and learning facilitated and supported by Internet technologies. In this research, e-learning is defined as the overall technological system to deliver teaching, whereas participation in e-learning is the act of use of telecommunication to deliver teaching and learning within such a system. Khan (2004) defined e-learning as an iterative process that goes from the planning stage through design, production and evaluation to delivery and maintenance stages. However, there are both advantages and disadvantages to e-learning. On a positive side, e-learning allows for a learner-centred, self-paced, cost-effective way of learning and on a negative side, there is a lack of social interactions, higher degrees of frustration and confusion, with higher preparation time for instructors ( Zhang et al. , 2012 ).
Sun et al. (2008) stated that personal perceptions about e-learning could influence attitudes and impact whether a user would intend to use to e-learning in the future. Uppal et al. (2018) and Kim and Frick (2011) mentioned that the supportiveness of the service, information quality and system quality are different aspects of e-learning quality, which could also impact the decision of the users. Moreover, Benigno and Trentin (2000) stated that e-learning is potentially affected by factors such as student characteristics, student-student interaction, learning materials, learning environment, and information technology (IT). Also, Selim (2007) mentioned that there are eight critical success factors of participation in e-learning (e.g. instructor’s attitude towards and control of the technology and student motivation and technical competency). Furthermore, Sun et al. (2008) suggested that perceived e-learning satisfaction is depended on the six dimensions: learner, instructor, course, technology, design and environmental. Sun et al. (2008) concluded that learner computer anxiety, instructor attitude toward e-learning, e-learning course flexibility, e-learning course quality, perceived usefulness, perceived ease of use, and diversity in assessments were the critical factors affecting learner's perceived satisfaction.
Garavan et al. (2010) conceptualised participation in e-learning and quantitatively validated the research model. In their model, the participation in e-learning is formed by the general-person characteristics (e.g. age and social class), motivation to learn and instructional design characteristics of e-learning (content quality and learner support, feedback and recognition). Additionally, the perceived barriers and enablers to e-learning are potentially affected by the proper instructional design of e-learning. Fleming et al. (2017) identified that predictors of future use and overall satisfaction from using e-learning are low perceived complexity of the e-learning system, the knowledge of e-learning, and available technical support for e-learning. Zhang et al. (2012) presented a research model that evaluates the impact of multiple factors on the intention to continue participation in the e-learning systems. Zhang et al. (2012) concluded that the intention to participate depends directly and indirectly on the psychological safety communication climate, on the perceived responsiveness of e-learning system and self-efficacy, as well as satisfaction from the previous use of the system. Furthermore, satisfaction and membership of the community were found to affect the intention to continue participation in e-learning.
2.2 Blended learning: boundaries between physical and virtual
Hrastinski (2008) stated that e-learning participation does not only occur online but also takes place offline. This is mainly due to the fact that e-learning requires time and energy to learn, communication, thinking and assessing what learners have obtained from e-learning communities in more traditional learning settings. Literature on e-learning is primarily on the so-called blended learning of physical and digital learning and Anthony et al. (2020) stated that blended learning (BL) has been increasing in popularity and demand. However, recent literature on the issue seems to be dominated with the factors of educator presence in online settings, interactions between students, teachers and content, and designed connections between online and offline activities as well as between campus-related and practice-related activities.
Wilson (2009 , p. 20) stated that “learning space continuum has two types of conditions at its extremities, wholly independent self-directed unstructured learning at one end and structured teacher-led didactic learning environments at the other”. Furthermore, Wilson (2009) identified different places for learning spectrums, ranging from unstructured that corresponds to home, bar, cafe or gym to lecture theatre and seminar places for holding workshops. The notion of learning space continuum may become necessary when we take into consideration e-learning. As Ellis and Goodyear (2016 , p. 150) identified, the “boundaries” between the physical and the virtual are become less transparent and more permeable, in addition to the greater need of students of being capable of using digital technologies to discover and construct knowledge that is meaningful to them.
Hence, we argue that e-learning participation cannot be defined narrowly as a specific activity in a specific context, but rather a range of activities, some of which may be even blended with the physical (more traditional) learning and interaction with teachers or other students in a more structured or unstructured manner. This could have a significant impact on the way not only e-learning, but the overall learning process is structured, including how the different technologies are used, how the instructional learning programs are structured, what are the social interrelationships between the students, instructors, organisations, and how the success of learning is measured.
2.3 COVID-19, quarantine and e-learning
Kaplan et al. (2020) stated that a third of the global population worldwide was on a quarantine lockdown in order to limit the spread of the COVID-19. This action led to the social distancing and thus fewer social connections, which also included closures of commercial enterprises and higher educations, resulting in limited physical presence and social interactions between the people. The impact of COVID-19 is also seen in the educational environments, with a potential to experience unparalleled transformations, just as many other human spheres of behaviour, which are facilitated by the advents in the development of IT, such as 5G ( Kaplan et al. , 2020 , p. 4). Paraschi (2020 , p. 19) stated that e-learning might even be an alternative activity that is to help communities previously relying on other activities, such as competitive educational and training e-learning programs blended with on-site summer schools in a Greek island as a replacement for tourism, which suffered greatly during the COVID-19 pandemic.
However, there are multiple challenges related to e-learning that come as a result of COVID-19. For instance, Almaiah et al. (2020) identified the critical challenges and factors of e-learning system usage during COVID-19 pandemic. In the research, the authors covered the topics of e-learning system quality, trust, culture, self-efficacy, and issues of financial support, change management and technical maintenance, all of which were mentioned as potentially influential factors of e-learning adoption. Moreover, we argue that COVID-19 pandemic is a challenge impacting the approach to e-learning, thus requiring adaptation and innovation in higher education to cope with the posed challenge. Alea et al. (2020) have evaluated the perceptions among the teachers about the impact of COVID-19 and the community quarantine on the distance learning and found multiple challenges related to it, as well as individual issues with preparedness for delivering distance learning. Also, Abbasi et al. (2020) stated that students did not prefer e-teaching over face-to-face teaching during the lockdown situation, and that administration and faculty members must take necessary measures to improve e-learning during the lockdown. Favale et al. (2020) stated that in the context of 80–90% of people in Italy staying at home during the quarantine, remote working and online collaboration exploded in an Italian university. Thus, the research on participation in e-learning in the context of COVID-19 is very relevant and timely.
2.4 Information service, information systems and information technology
In literature, information service is defined as “a component of an information system representing a well-defined business unit that offers capabilities to realise business activities and owns resources (data, rules, roles) to realise these capabilities” ( Ralyté et al. , 2015 , p. 39). Furthermore, Wijnhoven and Kraaijenbrink (2008 , p. 93) suggested that information services are “services that facilitate the exchange of information goods with or without transforming these goods”. The authors (2008, p. 114) stated that “information services have a lot in common with other types of information systems”, hence implying that the information services are distinct from the information systems. Importantly, it is necessary to outline that information system (IS) is defined as any combination of information technology (IT) and people's activities using that technology ( Gupta, 2000 ).
Accordingly, IT consists of telecommunications, computing, and content, whereby different types of IT are represented at the intersections (e.g. Internet being partly computing, and partly telecommunications). Hence, one may wonder about the exact definitions of an information service, an information system, an information technology and what is the interrelation between them. It is essential to underline that the terms are potentially having blurry boundaries and are hard to define. For the purposes of this particular study, information service is defined as the use of information technology by people. However, the information system of e-learning at large is not considered to be limited only to LMS such as Moodle as there are many other physical and virtual information services that could facilitate e-learning. This study will try to focus on the information services of e-learning that facilitate participation over IT.
3. Theoretical framework and hypothesis development
Ke and Hoadley (2009) suggested that there is no “one size fits all frameworks” when evaluating online learning communities. From the literature on e-learning, there are a number of identified antecedent factors that could potentially influence participation in e-learning. Besides, factors related to the current situation of pandemic (COVID-19) may also impact the participation in e-learning. The research model for this study is developed based on the literature review outlined above. Firstly, several antecedent factors that may affect participation in e-learning are identified. Secondly, these factors are used to build a theoretical framework which will be evaluated and examined empirically.
3.1 COVID-19 related factors
At the time of writing the paper, the research on the COVID-19 is new, as it is a relatively recent event. Hence, the exploratory purpose of the paper is to identify potential factors that may impact e-learning participation in quarantine time. Therefore, we aim to review the most recently published studies on this topic. For example, Alea et al. (2020) have recently performed a research on the opinions of teachers concerning the preparedness and challenges that the university might face when adopting e-learning in the times of the quarantine. They empirically evaluated the (1) awareness of the COVID-related situation, (2) the teacher's readiness and school's preparedness to conduct distance learning, and (3) perceived challenges in distance learning education ( Musingafi et al. , 2015 ). In this study, nevertheless, as we plan to survey students instead of teachers, we adapt the same survey questions and modify them slightly to fit the context of our study. As such, we use (1) awareness of COVID-19, (2) perceived challenges to participate in e-learning during the quarantine, (3) perceived educational institutions preparedness [perceived teachers' preparedness and perceived school's preparedness] to conduct distance learning, as the COVID-19 related factors to examine the students' intention to e-learning participation.
Awareness of COVID-19 has a positive effect on the intention to e-learning participation.
Awareness of COVID-19 has a positive effect on perceived usefulness.
Awareness of COVID-19 has a positive effect on perceived ease of use.
Perceived challenges during COVID-19 has a negative effect on the intention to e-learning participation.
Perceived challenges during COVID-19 has a negative effect on perceived usefulness.
Perceived challenges during COVID-19 has a negative effect on perceived ease of use.
Perceived educational institutions preparedness during COVID-19 has a positive effect on the intention to e-learning participation.
Perceived educational institutions preparedness during COVID-19 has a positive effect on perceived usefulness.
Perceived educational institutions preparedness during COVID-19 has a positive effect on perceived ease of use.
3.2 Perceived usefulness of e-learning
Perceived usefulness has a significant effect on the intention to e-learning participation.
3.3 Perceived ease of use of e-learning
Perceived ease of use has a significant effect on the intention to e-learning participation.
Perceived ease of use has a significant effect on perceived usefulness.
3.4 Intention to participate in e-learning
In the current study, our dependent variable is e-learning participation, which is measured by the student's intention to participate. There may be multiple different factors that could affect the intention of students to participate in e-learning during the quarantine situation. Prior studies in e-learning research use intention to participate in e-learning ( Masrom, 2007 ; Tselios et al. , 2011 ; Zhang et al. , 2012 ; Park, 2009 ) as the outcome variable.
Moreover, we intend to examine several potential individual characteristics as control variables when assessing the model. We argue that the younger students are more accepting the use of IT for learning. Evidence is paradoxical in this aspect, as Fleming et al. (2017) stated that age does not impact the intention of using e-learning. Ong and Lai (2006) stated that gender might indirectly affect the acceptance of e-learning, as men and women had different perceptions of PU and PEOU of e-learning systems. The theoretical framework model is provided in Figure 1 .
4. Methodology
The data collection was done between 15 August to 15 October 2020 through an online survey when closure of all educational institution, specifically higher education was announced by the Finnish government started from March 2020. Prior to the primary data collection, survey items (instruments) to measure five factors predicting the use of e-learning during COVID-19 among higher education students were adopted from previously validated studies and based on the adaptation process, the items for the current study were slightly modified suit the contexts of the study, COVID-19 and e-learning.
The items for measuring COVID-19 awareness (three items), perceived teachers and school preparedness (six items) and perceived COVID-19 challenges (four items) all were derived from Alea et al. (2020 , pp. 134–136). Survey items for measure perceived usefulness (four items) and perceived ease of use (four items) were derived from Masrom (2007) and Davis (1989) . Finally, items for measuring intention to participate in e-learning during the COVID-19 were derived from Lee et al. (2009) and Davis (1989) . The model measurement and assessment of the constructs were done through the use of SmartPLS 3.2 that was guided by the procedures of Partial Least Squares Structural Equation Modelling (PLS-SEM).
4.1 Data collection
During the school closures, the survey instrument was distributed through an online survey application. The data were obtained only from those respondents who indicated they are currently university students. As mentioned, the data collection was formed in the course of two months, and over 350 invitations were sent. After the closure of the survey, 153 responses were received. Upon further examination of the completeness of the data and removing unengaged responses or those who indicated that they are not currently students, in total, 131 responses were included in the dataset for further analysis.
5.1 Descriptive statistics
Of the respondents, 73 (55.7%) were female, while 56 (42.7%) respondents were males, and two did not want to reveal their gender. The average age of respondents was 25 years old with (standard dev. = 6.1). Moreover, the highest degree of the respondents was as follow: high school diploma ( N = 63), bachelor's degree ( N = 40), master's degree ( N = 19), and PhD or other ( N = 9). We also asked respondents to indicate how long in total have they been using e-learning systems. The following information was retrieved; less than a year ( N = 61), between one to three years ( N = 37), more than three years ( N = 32) and only one respondent indicated has never used such learning systems. We also asked the respondent to indicate to what extent the instructor's teaching style would impact their decision to participate in e-learning. We asked, “the instructor encourages and motivates me to use e-learning”, or “the instructor's style of presentation holds my interest”. The results showed that 36 students thought the teaching style of the instructor would motivate and encourage them to use e-learning systems and interestingly 23 students mentioned it does not affect their intention or the effect is not considerable. Regarding the second question, we found 28 students who believed that the instructor's presentation style would have a substantial impact on their intention to use e-learning systems to participate in e-learning. The same number of ( N = 28) students believed that the instructor's presentation style does not at all play a role in their decision to use such systems for e-learning participation, or the effect is somewhat limited.
5.2 Measurement results
In the following, we report on the data analysis at the measurement model, which refers to the assessment of the measures' reliability and their validity. In doing so, we computed: (1) item (indicator) loadings and internal consistency reliability, (2) convergent validity, and (3) discriminant validity ( Hair et al. , 2019 ).
5.2.1 Item loadings and internal consistency reliability
PLS-SEM results were utilised for the item loadings in this study. Table 1 shows the detail of item loadings. As shown in Table 1 , all item loadings (except one item PCHA_2 with the slightly lower value) satisfied the recommended loading values of >0.70 ( Hair et al. , 2019 ). However, from the algorithm process in PLS-SEM, one item (indicator) from the COVID-19 awareness (CAWA_3) was dropped. Therefore, 24 items remained for the next step of the PLS-SEM analysis. Internal consistency reliability refers to the evaluation findings for the statistical consistency across survey items (indicators). According to Hair et al. (2019) , internal consistency reliability should be reported through Cronbach's alpha ( α ) and Composite Reliability (CR). Therefore, we computed these two tests and the values achieved were all above to the recommended threshold of 0.70 ( Hair et al. , 2019 ) providing good internal consistencies.
5.2.2 Convergent validity and discriminant validity
Convergent validity is a statistical measure that assesses the construct validity, and it suggests that assessments having similar or same constructs should be positively related. Regarding the convergent validity, the value s of average variance extracted (AVE) must be reported. As shown in Table 1 , all the AVE values were above the recommended threshold of 0.50.
Discriminant validity test examines the extent to which a construct is different from other constructs ( Hair et al. , 2019 ). In order to report the values, the Fornell Larcker criterion will be used, and the AVE scores of a construct should be lower than the shared variance for all model constructs. As shown in Table 2 , all the AVE scores satisfied this condition, and therefore, the discriminant validity was established based on the evaluation of the Fornell Larcker criterion ( Fornell and Larcker, 1981 ).
However, as we used the PLS-SEM approach to perform the data analysis, we also assessed the discriminant validity through the Heterotrait-Monotrait Ratio of Correlations (HTMT). Discriminant validity problems also appear when HTMT values are higher than 0.90. The construct can be similar if HTMT shows a value of >0.90, which in this case, it indicates the lack of discriminant validity. Table 3 shows the HTMT values, and as it is indicated, all values were lower than 0.90.
We also examined the collinearity by reporting Variance Inflation Factor (VIF) values. The collinearity will be an issue if the VIF value is above 3.00 ( Hair et al. , 2019 ). Perceived usefulness (VIF = 1.663) and perceived ease of use (VIF = 1.559) are the predictor of intention to participate in e-learning during the COVID-19. Moreover, COVID-19 awareness is the predictor of perceived usefulness (VIF = 1.064) and perceived ease of use (VIF = 1.064). Perceived educational institutions preparedness predict perceived usefulness (VIF = 1.087) and perceived ease of use (VIF = 1.087). Perceived COVID-19 challenges predict perceived usefulness (VIF = 1.088) and perceived ease of use (VIF = 1.088). Therefore, the collinearity test results show that collinearity does not emerge as an issue in this study ( Hair et al. , 2019 ).
5.3 Structural results
The structural model assessment was performed following Hair et al. (2019) recommendation. In order to assess the path coefficient between endogenous and exogenous constructs, the sample was bootstrapped through 5.000 sub-sampling. The results of the SRMR indicator estimating the goodness of fit of the structural model was 0.065. The structural results showed that most of the hypotheses were supported ( Table 4 and Figure 2 ). The outcome variable, i.e. intention to participate in e-learning was explained by variance of 69%. Moreover, the perceived usefulness and perceived ease of use were explained by variance of 21% and 15%, respectively. The SEM results showed that the path between COVID-19 awareness to intention to participate in e-learning was significant ( β = 0.192; t = 3.220; p = 0.001); therefore, H1 was supported by the model. The SEM results also showed that the path between COVID-19 awareness to perceived usefulness ( β = 0.243; t = 2.748; p = 0.005) was significant; thus H1a was supported by the model. However, the COVID-19 awareness to perceived ease of use was not significant; thus H1b was rejected by the model.
The SEM results showed that the path between perceived challenges, as expected, negatively impact intention to participate in e-learning ( β = −0.186; t = 2.789; p = 0.005); therefore, H2 was supported by the model. The SEM results also showed that the path between perceived challenges during the COVID-19, as expected, negatively impact both perceived usefulness ( β = −0.36; t = 4.599; p = 0.001) and ( β = −0.246; t = 3.167; p = 0.002), thus H2a and H2b were both supported by the model. In addition, the SEM results showed that the path between perceived educational institutions preparedness to intention to participate in e-learning was not significant; therefore, H3 was rejected by the model. This finding is similar to Zia (2020) who also found that the curriculum and technology have a negative impact on the online classes during the COVID-19 pandemic. Furthermore, the SEM results showed that the path between perceived educational institutions preparedness to PU was also not significant; thus H3a was rejected by the model. However, perceived educational institutions preparedness to PEOU was significant ( β = 0.235; t = 2.365; p = 0.02), thus H3b was supported by the model. Finally, the strongest relationship emerged between the path from perceived usefulness to participate in e-learning ( β = 0.623; t = 9.225; p = 0.001); therefore, H4 was supported by the model. However, the results showed that the path between perceived ease of use to participate in e-learning was significant was not significant; thus, H5 was rejected by the model. As per path between PEOU to PU, the SEM results showed a significant effect of PEOU to PU ( β = 0.484; t = 6.220; p = 0.001); thus H5a was supported by the model.
We also examined the mediating effect of perceived usefulness and ease of use between the COVID-19 related factors and intention to participate in e-learning. To do so, we first accounted for the results of total indirect effects and then examined the specific indirect effects values, as PLS-SEM procedures required. The mediation test results showed the total indirect effects for the paths between COVID-19 awareness ( β = 0.161; t = 2.618; p = 0.01), and perceived challenges ( β = −0.251; t = 4.630; p = 0.001) to intention to participate in e-learning were significant, indicating that there might be mediation effects in these path relationships. Therefore, we checked the specific indirect effects values and found that theses paths are mediated only through perceived usefulness. The result showed that the paths between COVID-19 awareness ( β = 0.152; t = 2.553; p = 0.01) and perceived challenges ( β = −0.224; t = 4.187; p = 0.001) to intention to participate in e-learning were partially mediated through perceived usefulness. Finally, the effect of perceived educational institutions preparedness to intention to participate in e-learning was only realised through the mediating effect of PEOU-PU ( β = 0.07; t = 2.218; p = 0.03).
5.4 Multigroup analysis (MGA)
The research model was further investigated to see if the demographic characteristics of the respondents impact the path relationships in the model. To do so, we used the gender, and the average time the participant used the e-learning system in their e-learning activities. These two variables were used as control variables, and then we ran multigroup analysis (MGA) with PLS-SEM. The MGA results showed that respondents are different in some paths (see Table 5 ). For example, the path between perceived teachers and school's preparedness to perceived usefulness was only significant for males ( β = 0.261; t = 1.995; p = 0.05). The MGA results also showed that the path relationships between perceived challenges to (1) intention to participate in e-learning, (2) PU and (3) PEOU, were significant only for females. Therefore, the perceived challenges of COVID-19 could be considered as an important and influential factor influencing directly the decision-making of the students in e-learning participation. Finally, the path between the COVID-19 awareness to PEOU was only significant for females ( β = 0.332; t = 3.406; p = 0.001).
We also divided respondents into two groups based on their use of e-learning systems; group 1 included those who indicated they have experienced and used such systems for less than a year ( N = 61), group two for those who indicated they have experienced and used such systems for more than one year ( N = 69). The MGA results showed that the path between perceived educational institutions preparedness and PEOU was only significant for Group 1, those who mentioned that they had used the e-learning system for less than one year. However, more differences were observed in paths between COVID-19 awareness and perceived challenges to intention to participate in e-learning, as well as the path between perceived challenges to PEOU, such that the effects of these two path relationships were only significant for respondents in Group 2 (see Table 5 ).
6. Discussion
The SEM analysis revealed that the students' intention to participate in e-learning is significantly affected by the COVID-19 awareness and perceived challenges of the pandemic. It may be because of the subjective nature of the studied phenomena, which relies on the factors that relate to the individual (i.e. awareness and perceived challenges of the pandemic). These finding are similar to Raza et al. (2020) who also stated that there is need for improving the e-learning experience among students and escalating their intention to use such learning systems. Moreover, the perceived educational institution's preparedness (i.e. teachers and schools) seems to affect the intention to participate in e-learning only through the mediating effect of PEOU-PU. It may suggest that students do not see educational institutions' preparedness by itself as a motivating factor to use the e-learning system. It may also suggest that educational institutions have not been appropriately prepared to fully utilise the functionalities of e-learning systems (e.g. usefulness) facilitating the students' learning.
Moreover, the structure results showed that the awareness of COVID-19 situation might affect the usefulness of e-learning systems, but not the extent to which the use of such systems is easy. Given the pandemic requirements for safety via the social distancing and distance learning, students might consider e-learning systems as a better and safer alternative towards conventional in campus education. In other words, students have no other alternative left other than adapting to the dynamic situation and accepting to use e-learning systems to cope with the changes in their learning modes. Interestingly and as expected, the perceived challenges of COVID-19 situation seem to be a very influential factor determining the perceived value of e-learning systems and the intention to use them, however, it should be noted that the effect is negative. It may suggest that emotional and stress management of students is highly crucial for e-learning in the quarantine times.
Ong and Lai (2006) found that gender might impact the participation in e-learning through the perceived usefulness and perceived ease of use of e-learning systems. In the current paper, it was found the gender of the students impact their decision in e-learning participation. We would suggest that the perceived challenges of COVID-19 situation are having a more pronounced negative effect on female students than on their male counterpart. Plausibly, this might be due to the females' perceptions of their computer self-efficacy, which is crucial for e-learning ( Zhang et al. , 2012 ). In a similar vein, we would argue that the personality variations across genders may affect the results of why COVID-19 awareness has a significant impact on PEOU and the effect is only for females and why perceived preparedness has a significant impact on PU and that the effect is realised only for males. However, the latter may also be explained by the fact that males are more things-oriented, whereas females are people-oriented ( Su et al. , 2009 ). Hence, suggesting that males could potentially see more connections between e-learning systems' functionality (usefulness) and how these were improved by the preparedness of educational institutions.
The fact that the path between perceived educational institutions preparedness and PEOU was significant for those who used e-learning systems for a year or less may indicate that the educational institution's preparedness is only able to help an inexperienced user of e-learning systems by providing sufficient support and relevant information in the times of the pandemic. More experienced users of e-learning systems may have learned how to use them; hence the preparedness did not affect their perception of ease-of-use of e-learning systems. Contrarily, for experienced users who have used e-learning systems longer than a year, it may be that they are able to put the perceived challenges in perspective to the times when e-learning was not the main and the only mode of learning. The experience of use of e-learning systems is logically expected to be highly correlated with the age and the education level; hence, it could be hard to pinpoint whether differences come from the experience or other demographic variables.
7. Conclusions
The education of university students has been interrupted due to COVID-19 pandemic. The current situation has imposed unique challenges of smoothly maintaining the process of teaching and learning, as such e-learning has become an immediate solution to cope with the disruption in higher education. The results of this research revealed several theoretical implications. The first being the extension of the Technology Acceptance Model (TAM: Davis, 1989 ) for making it relevant to the current COVID-19 situation, and its application in the context of higher education to assess students' intention to use e-learning systems. The core theoretical focus of this study was to develop a conceptual model to identify factors impacting the students' intention to e-learning participation during the COVID-19 pandemic. This paper theoretically contributes to the literature by showing that the awareness of and the perceived challenges of the COVID-19 pandemic situation were the most significant factors influencing e-learning participation during the COVID-19 pandemic. As students' awareness of COVID-19 pandemic is increased, they would be more willing to achieve their education goals through the use of e-learning systems, especially when they are socially isolated, campus education is restricted and have to perform their studies mostly online. Moreover, the findings showed that no matter how well prepared the educational institutions (teachers and schools) are, the usefulness of e-learning systems still plays the leading role in enhancing the students' intention to participate in e-learning. Surprisingly, we did not find any direct impact of ease of use of e-learning systems to the intention of e-learning participation. Perhaps, blended learning (offline and online education) could be still the most proffered modes of learning for the students. In other words, a blended approach, where traditional teaching is combined with online teaching, should have ushered the students to participate in e-learning.
Alea et al. (2020) have found that there are multiple challenges in terms of educational preparedness during the COVID-19. However, in this study, it was found that educational institutions preparedness has little to no effect on the intention to participate in e-learning. Thus, the educational institutions are advised to consider the findings of this study to review their approaches to address their politics regarding e-learning in the times of the quarantine. We also found that the effects of the perceived pandemic challenges and educational institutions preparedness are different for experienced and inexperienced users of e-learning systems as well as among female and male students. As such, gender should be considered as a crucial factor in e-learning initiative taken by the educational institutions. Perceived challenges seem to have the most negative impact on women in the pandemic situation and their participation in e-learning. Sun et al. (2008) suggested that personal perceptions about e-learning affect the intention to participate in e-learning. In our study, it seems that the intention to participate in e-learning is affected by the perceptions about the contextual situation, such as about the current pandemic situation, perceived challenges it creates, and how does the educational institution prepare itself to tackle the situation.
7.1 Limitations
One of the drawbacks of the current research is the sample size used that can be expanded to achieve more generalisable findings. The conceptual model was developed for the purpose of this research, and therefore, the structural results and findings should be interpreted carefully. The size of the dataset and the sampling strategy might be other sources of potential errors. Since the data were collected through an online survey and during the COVID-19 pandemic situation, it is very hard to evaluate and assess whether the respondents answered questions as accurate as possible. Finally, this study took place in Finland, and might not apply to other countries due to different COVID-19 situation, regulations and imposed restriction during the current situation.
7.2 Future research
This research has uncovered interesting manifold insights about the different COVID-19 related factors on e-learning at educational institutions. As such, future research may utilise the conceptual model developed in this research and aim to explore further findings in other contexts. For instance, by investigating what encourages students to participate in e-learning more and why education institutions preparedness (both teachers and schools) does not account for higher intention to participate in e-learning. Students' perceptions could also be explored qualitatively. For example, why and how exactly awareness about COVID-19 encourages more intention to use e-learning systems. Future research is also advised on exploring further how educational institutions should become better prepared for future events, if they may occur, such as one we are witnessing in the current pandemic situation.
Theoretical model
Structural model
Reflective indicator loadings and internal consistency reliability
| Construct | Items | Loading | Mean | Std | | CR | AVE |
|---|
| Perceived usefulness of e-learning | PU1 | 0.94 | 3.85 | 2.05 | 0.94 | 0.95 | 0.85 |
| PU2 | 0.91 | 3.85 | 2.03 |
| PU3 | 0.93 | 3.59 | 2.09 |
| PU4 | 0.90 | 4.59 | 1.93 |
| Perceived ease of use of e-learning | PEOU1 | 0.90 | 5.28 | 1.54 | 0.91 | 0.94 | 0.79 |
| PEOU2 | 0.89 | 5.45 | 1.56 |
| PEOU3 | 0.91 | 5.16 | 1.62 |
| PEOU4 | 0.86 | 5.24 | 1.52 |
| COVID-19 awareness | COVA1 | 0.87 | 6.81 | 0.74 | 0.80 | 0.91 | 0.83 |
| COVA2 | 0.94 | 6.70 | 0.95 |
| Perceived educational institutions preparedness | PEIP1 | 0.75 | 3.73 | 1.88 | 0.91 | 0.93 | 0.69 |
| PEIP2 | 0.76 | 4.29 | 1.84 |
| PEIP3 | 0.83 | 4.85 | 1.80 |
| PEIP4 | 0.85 | 4.82 | 1.82 |
| PEIP5 | 0.90 | 4.86 | 1.86 |
| PEIP6 | 0.87 | 4.61 | 1.89 |
| Perceived challenges | PC1 | 0.82 | 5.66 | 1.83 | 0.85 | 0.89 | 0.68 |
| PC2 | 0.68 | 5.05 | 1.84 |
| PC3 | 0.91 | 5.53 | 1.91 |
| PC4 | 0.87 | 5.74 | 1.82 |
| Intention to participate in e-learning | INT1 | 0.85 | 2.87 | 2.12 | 0.91 | 0.94 | 0.80 |
| INT2 | 0.85 | 4.50 | 1.83 |
| INT3 | 0.93 | 3.79 | 2.04 |
| INT4 | 0.93 | 3.62 | 2.06 |
: = Cronbach's alpha; CR = Composite reliability; AVE = Average explained variance| | COAV | INT | PC | PEOU | PU | PEIP |
|---|
| COVID-19_awareness | | | | | | |
| Intention to participate in e-learning | 0.303 | | | | | |
| Perceived challenges | 0.154 | −0.408 | | | | |
| Perceived ease of use | 0.079 | 0.538 | −0.283 | | | |
| Perceived usefulness | 0.205 | 0.794 | −0.346 | 0.567 | | |
| Perceived educational institutions preparedness | 0.153 | 0.265 | −0.212 | 0.299 | 0.226 | |
Discriminant validity (HTMT)
| | COAV | INT | PC | PEOU | PU | PEIP |
|---|
| | | | | | | |
| Intention to participate in e-learning | 0.346 | | | | | |
| Perceived challenge | 0.222 | 0.431 | | | | |
| Perceived ease of use | 0.090 | 0.587 | 0.303 | | | |
| Perceived usefulness | 0.225 | 0.857 | 0.362 | 0.610 | | |
| Perceived educational institutions preparedness | 0.173 | 0.280 | 0.217 | 0.326 | 0.234 | |
Structural results
| Hypothesis | | -statistics | Sig |
|---|
| : COVID-19_awareness → Intention to participate in e-learning | 0.192 | 3.220 | |
| : COVID-19_awareness → Perceived usefulness | 0.243 | 2.748 | |
| : COVID-19 awareness → Perceived ease of use | 0.081 | 0.890 | NS |
| : Perceived challenges → Intention to participate in e-learning | −0.186 | 2.789 | |
| : Perceived challenges → Perceived usefulness | −0.360 | 4.599 | |
| : Perceived challenges → Perceived ease of use | −0.246 | 3.167 | |
| : Perceived educational institutions preparedness → Intention to participate in e-learning | 0.022 | 0.389 | NS |
| : Perceived educational institutions preparedness → Perceived usefulness | 0.112 | 1.267 | NS |
| : Perceived educational institutions preparedness → Perceived ease of use | 0.235 | 2.365 | |
| : Perceived ease of use → Intention to participate in e-learning | 0.110 | 1.780 | NS |
| : Perceived usefulness → Intention to participate in e-learning | 0.623 | 9.225 | |
| : Perceived ease of use → Perceived usefulness | 0.484 | 6.220 | |
Multigroup analysis results
| Path relationships | | -statistics | | Sig |
|---|
| |
| Perceived educational institutions preparedness → PU | 0.261 | 1.995 | 0.05 | Male |
| Perceived challenge → Intention to participate in e-learning | −0.310 | 3.828 | 0.001 | Female |
| Perceived challenge → PU | −0.572 | 6.487 | 0.001 | Female |
| Perceived challenge → PEOU | −0.335 | 3.981 | 0.001 | Female |
| COVID-19 awareness → PEOU | 0.332 | 3.406 | 0.001 | Female |
| |
| Perceived educational institutions preparedness → PEOU | 0.331 | 2.161 | 0.031 | Group 1 |
| COVID-19 awareness → Intention to participate in e-learning | 0.248 | 2.906 | 0.004 | Group 1 |
| Perceived Challenge → Intention to participate in e-learning | −0.289 | 3.114 | 0.002 | Group 2 |
| Perceived Challenge → PU | −0.279 | 2.518 | 0.01 | Group 2 |
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PhD in E-Research and Technology Enhanced Learning
Join our part-time Doctoral Programme in E-Research and Technology Enhanced Learning to carry out your own research and achieve a PhD. (Undertaken over a minimum of four years).
We have designed this programme for anyone in the world who wants to develop their research practice in this area. Although you will mainly learn online, you will also benefit from two short face-to-face residential meetings (one in the first year and one in the second year) where you will get to know your tutors and fellow students, and take part in a range of interactive sessions. These are valuable core elements of the programme.
Download the TEL Enquiry Handbook (2025)
Key information
The programme is purpose-built for professionals responsible for educating or training others in any sector. You will want to study to an advanced level and carry out a piece of research of the highest possible standard in an aspect of your professional practice. We have been running this pioneering programme for 15 years and have had students from a whole spectrum of backgrounds - from computing to law, nursing to higher education. We have found it is very relevant for people wanting to develop distance or blended learning in programmes they manage.
Whatever your background, you will be eager to work towards a PhD and focus on researching educational uses and practices of technology enhanced learning in educational settings and sectors. You’ll finish the programme with new insights, new opportunities, and new career possibilities.
Meet some of our Alumni on the Centre for Technology Enhanced Learning People webpages.
This is not an online version of an existing programme. Our programme was developed as an online programme for part-time professionals who will be studying mainly at a distance. You will be part of a cohort which means you’ll join our online learning community, receiving ongoing feedback from tutors and other students.
We have designed a two-year structured set of modules which introduce research themes in educational uses and practices of technology enhanced learning.
You will decide the focus of your research, but we will be here to advise you every step of the way. For example, past students have researched the use of a virtual learning environment for legal training, technology to assist the elderly at home, and the use of Twitter for early career researchers.
‘Technology enhanced learning' (TEL) encompasses all uses of information and communications technologies in learning and teaching. It is also sometimes referred to as 'e-learning', 'online learning' and 'advanced learning technology'. Many other terms are used around the world to describe this quickly growing and highly impactful phenomenon.
Our programme focuses on 'networked learning' – connections within an online learning community on the Internet. Joining us, you will explore human aspects of technology in learning, the values underpinning the use of technology, and how technology and learning shape each other.
E-Research is an emerging field which involves applying advanced technologies to existing research methods and approaches. Our programme examines trends in this field and explores how to use technologies for research into technology enhanced learning.
E-Research aims to advance and augment rather than replace traditional research methodologies. Improving knowledge in this area helps researchers perform research more creatively, efficiently and collaboratively across long distances, and share their research outcomes.
Although you will join us predominantly online, the residentials are compulsory, and they are an important part of your study. There are two four-day residential meetings in Part One of the programme, one in the first year and another in the second.
You will join us on campus in Lancaster to get to know your tutors and meet other students. At the same time, we will introduce you to wider thinking about e-Research and TEL research, as well as discussing modules, the virtual learning platform and associated technologies.
The first year residential dates for our 2025 intake are 31st March - 3rd April, 2025 The second year residential dates for our 2025 intake are still to be confirmed
The first year residential dates for our 2024 intake are 8th - 11th April 2024 The second year residential dates for our 2024 intake are 1st - 4th April 2025
Further information about timetables, accommodation, travel and visas is available on our Residentials web page.
How to Apply
The next start date is January 2024 (CH17).
Entry requirements
Apply online.
For admission to this programme applicants should normally have:
- a good honours degree from a British university or CNAA, and a good taught Master's degree; or
- qualifications of a comparable standard from a university or recognised degree awarding body in another country.
Preference will be given to applicants who have degrees in cognate areas (normally social science).
Language proficiency
Applicants will need to have an acceptable fluency in written and spoken English.
For students whose first language is not English, an English Language Test Certificate will be required, that is, IELTS Academic with an overall score of 6.5 with at least 6.0 for reading and writing.
Further information can be found at: English Language Requirements .
Please apply using the online system .
The next start date is 1st January, 2025.
Typical Cohort Number: 30
As this is a PhD by coursework and thesis we do not require a research proposal at this stage, but you should explain why you wish to join the programme and how you hope to benefit from it.
Please contact the admissions team if you have any questions about applying to study at Lancaster University.
Fees and funding
The fee for each cohort is set annually by the University and represents the part-time fee for that academic year. Once a student is on the programme the fee will be increased in line with inflation for each subsequent year of the course.
The course fee for:
- 24/25 is £5,410 per academic year, for four years minimum, for UK students and £9,670 per academic year, for four years minimum, for international students.
Fees are subject to a small increase each academic year.
To help finance your postgraduate study at Lancaster, you can apply for funding from charities and other funders: further details are available on the Fees and Funding webpage.
Applicants from the European Union can read more information about Research Fees (from Lancaster University) following the 2016 Referendum.
When you apply you will need to indicate your likely source of funding for your fees. If you are not self-funding you should investigate possible sources of finance as soon as you can for the full period of your study. Many students have been supported by their employing institutions.
Find out what our graduates say about studying on our PhD programmes
Several students have published journal articles arising from their module assignments and theses.
Structure and modules
The programme is divided into two parts and has a modular structure in Part 1. All modules are compulsory and they are assessed along with the thesis proposal and the final thesis.
- Part One (years 1 and 2) consists of four modules that offer participants guided study in key areas of technology enhanced learning research.
- Part Two (year 3 Onwards) - participants carry out an original piece of research under the supervision of a member of staff and produce a thesis with a maximum limit of 50,000 words.
View a list of some of the PhD theses from the TEL programme.
Online and Distance learning
The Educational Research Department has considerable experience of supporting online and distance learners and we aim to make all our students feel that they are full members of the Department and part of the postgraduate community. Wherever possible we facilitate online participation at events and seminars organised by the Department.
All students have access to Moodle which is our Virtual Learning Environment. Many resources, for example, journal articles; required for postgraduate study, will be available online through the OneSearch facility offered by the Library . Additionally, the Library provides extra services for Distance Learners.
Visit our Computer requirements for studying online page for further information.
Rebecca Marsden is the Online Learning Support Officer for the Department of Educational Research and she can be contacted with queries about online learning.
The Academic skills webpages provide a wide range of online study opportunities across a range of topics. These include digital skills, referencing, research training and critical thinking.
Current Programme staff
The staff who teach and supervise programmes and modules can vary due to staff changes including research and other types of leave.
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Dr Brett Bligh
Centre for Higher Education Research and Evaluation, Centre for Technology Enhanced Learning
Dr Kathy Chandler
Centre for Technology Enhanced Learning
Dr Bethan Garrett
Centre for Social Justice and Wellbeing in Education
Dr Katy Jordan
Dr Philip Moffitt
Professor Don Passey
Centre for Social Justice and Wellbeing in Education, Centre for Technology Enhanced Learning
Dr Julie-Ann Sime
If you have any questions, or would like further information about this programme, please contact the Programme Co-ordinator, Alice Jesmont. Tel: +44 (0) 1524 592893 Email: a.jesmont@lancaster.ac.uk
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PhD Educational Research - Higher Education
PhD Higher Ed: Research, Evaluation & Enhancement
ORIGINAL RESEARCH article
E-learning research trends in higher education in light of covid-19: a bibliometric analysis.
- 1 University of Bisha, Bisha, Saudi Arabia
- 2 University of Oum El Bouaghi, Oum El Bouaghi, Algeria
- 3 Binghamton University, Binghamton, NY, United States
- 4 University of Rochester, Rochester, NY, United States
This paper provides a broad bibliometric overview of the important conceptual advances that have been published during COVID-19 within “e-learning in higher education.” E-learning as a concept has been widely used in the academic and professional communities and has been approved as an educational approach during COVID-19. This article starts with a literature review of e-learning. Diverse subjects have appeared on the topic of e-learning, which is indicative of the dynamic and multidisciplinary nature of the field. These include analyses of the most influential authors, of models and networks for bibliometric analysis, and progress towards the current research within the most critical areas. A bibliometric review analyzes data of 602 studies published (2020–2021) in the Web of Science (WoS) database to fully understand this field. The data were examined using VOSviewer, CiteSpace, and KnowledgeMatrix Plus to extract networks and bibliometric indicators about keywords, authors, organizations, and countries. The study concluded with several results within higher education. Many converging words or sub-fields of e-learning in higher education included distance learning, distance learning, interactive learning, online learning, virtual learning, computer-based learning, digital learning, and blended learning (hybrid learning). This research is mainly focused on pedagogical techniques, particularly e-learning and collaborative learning, but these are not the only trends developing in this area. The sub-fields of artificial intelligence, machine learning, and deep learning constitute new research directions for e-learning in light of COVID-19 and are suggestive of new approaches for further analysis.
Introduction
The idea of e-learning was originated in the 1990s to explain learning thoroughly through technical advances. When instructional architecture and technologies have advanced, more attention has been paid to studying with the pedagogy. University education, further education, and e-learning have also recently adopted prominent roles in e-learning, too. It is now possible to provide e-learning for off-the-formal training through the internet. It also increased the need for personalization and advanced social people’s tools ( Siemens, 2005 ). In addition, it is often referred to as being able to read. It will help mix much learning more conveniently, but it has to be done, given the success of “traditional” e-learning pages. When the educational and technological assets join, this will be something more than a personal matter.
The COVID-19 pandemic has forced the closure of many activities, especially educational activities. To limit the spread of the pandemic, universities, institutes, and academic schools had to switch to e-learning using the available educational platforms. Social distancing is critical, and the COVID-19 pandemic has brought an end to face-to-face education, negatively impacting educational activities ( Maatuk et al., 2021 ). This closure has stimulated the growth of distance education activities as an alternative to face-to-face education in their various forms. Accordingly, many universities have shared the best ways to deliver course materials remotely, engage students, and conduct assessments.
The concept of e-learning, although widely known has not yet been fully explored ( Nicholson, 2007 ). Many countries designed and deployed distance education systems during the COVID-19 pandemic to ensure that higher education could continue without interruption ( Tesar, 2020 ). Several opportunities and challenges related to e-learning, higher education, and COVID-19 arose as a result of this, prompting a flurry of research into the area. When looking at the scientific studies published during the COVID-19 pandemic, it shows clearly that many international journals have published a large number of academic articles about e-learning in higher education during COVID-19 ( Karakose and Demirkol, 2021 ). Furthermore, a vast amount of bibliometric research has been carried out in this field. However, there is very little research focused entirely on the relationship between e-learning, higher education, and COVID-19, using scientometric or bibliometric analysis ( Furstenau et al., 2021 ).
This paper will discuss bibliometric indicators for e-learning in higher education during COVID-19 studies and proceed with a network analysis to define the most important sub-areas in this topic. To define the trends of e-learning in higher education during COVID-19, the following questions are proposed:
Q1: What are the most important sub-fields of e-learning in higher education in light of COVID-19?
Q2: Who are the most influential authors on the subject of e-learning in higher education in light of COVID-19?
Q3: What countries and research institutions are the most referenced for research on the subject of e-learning in higher education in light of COVID-19?
Q4: What are the research gaps and recent trends in the subject of e-learning in higher education in light of COVID-19?
An analysis was conducted to provide a broad and long-term perspective on the vocabulary of learning publications. It helps to recognize emerging problems within the multifaceted and increasing study fields of the world of e-learning. Newly published studies can improve knowledge and bridge the knowledge gap through findings regarding e-learning trends; this applies particularly to higher education due to the importance of knowing the latest information about distance learning and its methods. For this reason, the research is valuable for analyzing the volume of publications that have been made on the subject matter and to solidify the knowledge base on what has been studied by different expert researchers in education. So this will create new progress and new proposals to improve education in the event of a future pandemic.
In recent years, there has been an increasing interest in research within areas related to e-learning: online learning, blended learning, technology acceptance model, smart learning, interactive learning environments, intelligent tutoring systems, digital learning were reported ( Oprea, 2014 ; Castro-Schez et al., 2020 ; de Moura et al., 2020 ; Kao, 2020 ; Nylund and Lanz, 2020 ; Pal and Vanijja, 2020 ; Patricia, 2020 ; Şerban and Ioan, 2020 ).
A substantial quantity of literature has been written and published on the bibliometric analysis of e-learning. These studies mainly aim to identify the most critical areas (keywords) of e-learning. Networks such as that conducted by Chiang et al. (2010) showed that the significant research areas in e-learning are as follows: Education and Educational Research, Information Science and Library Science, and Computer.
Science/Multidisciplinary Applications
Cheng et al. (2014) analyzed data from 324 articles published between 2000 and 2012 in academic journals and conference proceedings from 2000 to 2012 to determine the vital research areas (the results identify six research themes in the field e-learning). Tibaná-Herrera et al. (2018a) used VOSViewer to conduct a bibliometric analysis of SCOPUS and SCImago Journal & Country Rank to establish the “e-learning” thematic category of scientific publications, thereby contributing to the discipline’s consolidation, accessibility, and development by researchers.
Bai et al. (2020) have also pursued similar work in analyzing 7,214 articles published in 10 journals on the subject of e-learning from 1999 to 2018; this study offers valuable hints on the future direction of how e-learning may evolve. Fatima and Abu (2019) examined 9,826 records from the Web of Science (WoS) database between 1989 to 2018 to identify significant contributions to the area of e-learning. The findings of this study show that the United States and the United Kingdom have contributed more than half of the research in e-Learning. According to a recent survey by Mashroofa et al. (2020) , the University of London is the most prolific institution globally. According to the WoS database, the institution has published 131 studies on e-learning; the bibliometric analysis of 6,934 results revealed that the publications received 59,784 citations.
Hung (2012) employed text mining and bibliometrics to examine 689 refereed journal articles and proceedings, comparing them to these research results. These works are divided into two domains, each of which has four groups. The study’s findings now offer evidence that e-learning methods vary across top countries and early adopter countries.
There have been multiple previous attempts to do a systematic review of e-learning publications ( Lahti et al., 2014 ; Zare et al., 2016 ; Garcia et al., 2018 ; Rodrigues et al., 2019 ; Araka et al., 2020 ; Valverde-Berrocoso et al., 2020 ), these studies mainly aimed to identify research areas, the most used and most important methods, and tools in e-learning.
Many studies have examined the results of e-learning publications through meta-analysis ( ŠUmak et al., 2011 ; Lahti et al., 2014 ; Mothibi, 2015 ; Cabero-Almenara et al., 2016 ; Yuwono and Sujono, 2018 ).
The study’s contribution is that no controlled studies have compared differences in networks, models, and software outputs to define the most critical research areas in e-learning and the most influenced authors, organizations, and countries.
The study makes an important contribution to the analysis of current models and networks of e-learning in higher education during the COVID-19 pandemic, aiming to define the most critical research areas in e-learning and the most influenced authors, organizations, and countries. In addition, it looks at the framework of e-learning and its future research trends in light of COVID-19. This has been done through numerous investigations ( Tibaná-Herrera et al., 2018a , c ; Hilmi and Mustapha, 2020 ; López-Belmonte et al., 2021 ).
Materials and Methods
Bibliometric data.
We retrieved published research via a topic search of the Science e-learning in higher education during the COVID-19 pandemic using the WoS database on August 12, 2021. The following search terms were used: topic = (“e-learning” “COVID-19” “higher education”), in title-abs-key from 2020 to 2021, and were 602 studies (475 articles, 80 articles; early access, 25 proceedings paper, 22 reviews) distributed over 2 years, as shown in Figure 1 .
Figure 1. Publications per year (KnowledgeMatrix Plus outputs).
The following selection criteria were used to choose the studies. First, for the title, we looked at the following: the studies that looked at the topic of e-learning in higher education during COVID-19. Second, for the abstract, we looked at the following: the studies that addressed the problem of e-learning in COVID-19. Third, for the keyword, we looked at the following: the studies that included e-learning, higher education, universities, and COVID-19. Fourth, the subject areas were limited to a selection of works that dealt with this subject in the following disciplines: business management and accounting, educational sciences, social sciences, and psychology.
The bibliometric study data represents the overall research on “E-learning in higher education in light of the COVID-19” in the WoS database. These data covered the last 2 years (2020 and 2021) in which the use of e-learning was expected due to the closure and quarantine procedures.
The reasons for choosing this database over others, particularly Scopus and ScienceDirect, are due to several considerations; due to WoS data, the field of scientometrics has advanced significantly. WoS is more than simply a database of academic papers. Many information objectives are supported by this selected, organized, and balanced database, including full citation links and improved metadata ( Birkle et al., 2020 ). WoS databases include high-quality research covering Science Citation Index Expanded (SCI-Expanded), Social Sciences Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI), Emerging Sources Citation Index (ESCI) ( Falagas et al., 2008 ).
Figure 1 illustrates how interest in e-learning research has increased in recent years, particularly between 2020 and 2021. Among the 602 studies with 4,280 citations, 230 in 2020 (1,400 citations), and 372 in 2021 (2,880 citations), the importance of higher education institutions, including universities, in this modern teaching and learning approach and their significance in the educational process during COVID-19 is evident. They are different from the periods approved in the previous studies ( Chiang et al., 2010 ; Cheng et al., 2014 ; Bai et al., 2020 ; Fatimah et al., 2021 ). Therefore, this field of research (e-learning) has been renewed, and researchers should pay more attention to it to provide effective methods and approaches in light of the continuing epidemic.
Methods and Tools
According to the methods and approaches of bibliometric analysis (see: Zupic and Čater, 2015 , p. 04). the study relied on the co-occurrence indicator (co-word) to find out the main keywords on which previous studies focused as well as the co-authorship, publications, and citations indicators to find prominent authors, organizations, and countries in the topic of e-learning in higher education in COVID-19.
Following the methodology of preparing the bibliometric study in management and organization, which was explained by Zupic and Čater (2015) , the bibliometric analysis was carried out by completing the following steps: research design, study questions, and analysis approach selection (co-occurrence, publication, citation, and co-authorship); bibliometric data compilation, selection, and filtration, analysis (choosing the appropriate bibliometric software, clean the data, and generate networks); visualization, and interpretation.
The bibliometric analysis was performed to design networks of e-learning and define the most frequent keywords and the most cited authors, organizations, and countries to explain new and current trends within this topic. This is achieved depending on different software: CiteSpace converts research domain concepts into mapping functions between research frontiers and intellectual bases and is effective for information visualization ( Chen, 2016 ); VOSviewer is used to design the networks and is a powerful function for co-occurrence analysis and citation analysis ( Van Eck and Waltman, 2013 ). KnowledgeMatrix Plus is a powerful tool for analyzing frequency and statistics ( Chen and Song, 2017 ). This software was not used in previous studies ( Chiang et al., 2010 ; Cheng et al., 2014 ; Bai et al., 2020 ; Fatimah et al., 2021 ).
Results and Discussion
Keywords frequency.
Figures 2A,B and Supplementary Table 1 present the most frequent keywords that have been repeated more than five, which amounted to 131.
Figure 2. (A) Network of keywords (VOSviewer outputs). (B) Network of keywords (CiteSpace outputs).
Figure 2A shows nine sub-areas (clusters) for research in e-learning within higher education during the era of COVID-19. First, the red cluster shows searches related to the following: higher education, students, motivation, attitudes, systems, technology acceptance model, and user acceptance. Second, the green cluster shows searches related to the pandemic, blended learning, online learning, hybrid learning, flipped classrooms, virtual learning, and distance education. Third, the navy-blue cluster shows searches related to higher education online, online teaching, online assessment, formative assessment. Fourth, the yellow cluster relates to stress, health, care, quarantine, mental health, anxiety, college students, adults, children. Fifth, the violet cluster shows searches related to surgery, surgical education, skills, strategies, student satisfaction, and simulation. Sixth, the light blue cluster shows searches related to e-learning, performance, quality, remote learning, digital learning, assessment, evaluation. Seventh, the orange cluster shows searches related to education, Covid-19, coronavirus, sars-cov-2, distance learning, medical education. Eighth, the brown cluster included: computer-based learning, self-instruction/distance learning, internet/web-based education, curriculum, knowledge, science, and technology. Finally, the pink clusters showed searches related to artificial intelligence, machine learning, and deep learning. The researcher can also take these subfields as topics for research in e-learning, especially the last cluster, which formed a recent research trend for many scholars ( Bhardwaj et al., 2021 ; Kashive et al., 2021 ; Rasheed and Wahid, 2021 ).
Figure 2B shows that the research on this topic requires focusing on several issues. These are the most frequently mentioned keywords in Supplementary Table 1 , including COVID-19 crisis, technology acceptance model (TAM), distance education, stress, ICT, special education needs, mental health, student satisfaction, surgical teaching, self-efficacy, technology adoption, using the machine, and e-learning. At the same time, many studies used different terms to express the same meaning, such as interactive learning, online learning, and Distance learning. This is similar to what was found in previous studies on e-learning ( Chiang et al., 2010 ; Cheng et al., 2014 ; Bai et al., 2020 ; Fatimah et al., 2021 ).
Reference Authors
Figures 3A–C show the network of the most referenced authors on the topic of “E-learning in higher education in COVID-19” based on co-authorship:
Figure 3. (A) Network of authors (VOSviewer outputs). (B) Publications and citations per author (KnowledgeMatrix Plus outputs). (C) Network of cited authors in COVID-19 (CiteSpace outputs).
Figure 3A shows that there is a research partnership between eight authors. The co-authorship is the affiliation and the country: Fernando Augusto Bozza, Rosana Souza Rodrigues, Walter Araujo Zin, Alan Guimaraes and Gabriel Madeira Werberich, Federal University of Rio de Janeiro, Brazil. Joana Sofia F. Pinto, Willian Reboucas Schmitt and Manuela Franca, Complexo Hosp Univ Porto, Radiol Dept, Porto, Portugal. As for the rest, they have separate and individual publications. Figures 3A–C present the top authors based on publications and citations.
Figure 3B shows that the first author on this topic on “E-learning in higher education in COVID-19” is Antonio José Moreno-Guerrero, Univ Granada, Dept Didact & Sch Org, Spain. Among this research, we find “Impact of Educational Stage in the Application of Flipped Learning: A Contrasting Analysis with Traditional Teaching” ( Pozo Sánchez et al., 2019 ). We also find research on e-learning in mathematics teaching: an educational experience in adult high school ( Moreno-Guerrero et al., 2020 ) as well as research on the following: the effectiveness of innovating educational practices with flipped learning and remote sensing in earth and environmental sciences ( López Núñez et al., 2020 ); machine learning and big data and their impact on literature; a bibliometric review with scientific mapping in WoS; and a flipped learning approach as an educational innovation in water literacy ( López Belmonte et al., 2020 ; López Núñez et al., 2020 ). Moreno-Guerrero talked about e-learning and did not discuss the COVID-19 ( Moreno-Guerrero et al., 2020 ); otherwise, Lüftenegger discussed e-learning and COVID-19 ( Holzer et al., 2021 ; Korlat et al., 2021 ; Pelikan et al., 2021 ).
Figure 3C shows that the most important authors searched in COVID-19 and touched on e-learning are Maram Meccawy, Isabel Chiyon, and Anand Nayyar among others.
Reference Organizations
Figures 4A–C displays the most referenced organizations on the topic of “E-learning in higher education in COVID-19” based on publications, citations, and co-authorship.
Figure 4. (A) Network of organizations (VOSviewer outputs). (B) Network of organizations (CiteSpace outputs). (C) Citations per publications by the organization (KnowledgeMatrix Plus outputs).
Figures 4A–C demonstrate that the leading research organization for publications, citations, and co-authorship on this topic is the University of Toronto with 16 publications and 207 citations, followed by the University of King Abdulaziz with 15 publications and 57 citations the Jordan University of Science and Technology with 11 publications and 115 citations, then the University of Vienna with 10 publications and 30 citations, then the University of Sharjah with 10 publications and 20 citations, then the University of Granada with 9 publications and 79 citations, then the University of Porto with 9 publications and 14 citations, then Monterrey Institute of Technology and Graduate Studies with 9 publications and 2 citations, then the University of Jordan with 8 publications and 46 citations, and finally, the University of Colorado with 8 publications and 16 citations. That is due to several reasons, including the interest of these organizations in publishing in the WoS database. Then their interest in publishing in the subject of the study. We thus find it among the top 500 universities. 1
Reference Countries
Figures 5A–C display the most referenced countries on the topic of “E-learning in higher education in COVID-19” based on publications, citations, and co-authorship.
Figure 5. (A) Network of countries (VOSviewer outputs). (B) Network of countries (CiteSpace outputs). (C) Citations per publications by country (KnowledgeMatrix Plus outputs).
Figures 5A–C illustrate that the top countries for publications, citations, and co-authorship in this topic are as follows: the United States with 344 publications and 1,167 citations, the United Kingdom with 132 publications and 530 citations, China with 117 publications and 592 citations, Spain with 104 publications and 321 citations, Italy with 98 publications and 175 citations, Brazil with 74 publications and 224 citations, Canada with 67 publications and 368 citations, India with 64 publications and 139 citations, Saudi Arabia with 60 publications and 216 citations, and Germany with 59 publications and 133 citations. These show extensive collaboration, especially between the United States and the United Kingdom with 11 collaborations, between the United States and Canada with 10 collaborations, and between the United States and China with 9 collaborations; other countries show an average of 3–5 collaborations.
The results of the bibliometric analysis showed that there are nine sub-fields of research within a topic: motivation and students’ attitudes to e-learning systems in higher education (technology acceptance model), comparison between blended learning and virtual learning, online assessment versus formative assessment of students in higher education, stress, anxiety, and mental health of college students in COVID-19, surgical education strategies to develop students’ skills, quality and performance of higher education strategies of e-learning in COVID-19, challenges of medical education and distance learning during COVID-19, and changing higher education curricula using technology.
Finally, using artificial intelligence, machine learning, and deep learning to transform the e-learning Industry, this final sub-field formed a recent research trend for many scholars ( Bhardwaj et al., 2021 ; Kashive et al., 2021 ; Rasheed and Wahid, 2021 ).
The bibliometric study shows that the first author in e-learning is Antonio José Moreno-Guerrero, Univ Granada, Dept Didact & Sch Org, and Spain. His writings ( Pozo Sánchez et al., 2019 ; López Núñez et al., 2020 ; Moreno-Guerrero et al., 2020 ) are considered a useful reference in e-learning and blended learning. Therefore, Marko Lüftenegger is one of the most influential author in the topic of “E-learning in higher education in COVID-19” ( Holzer et al., 2021 ; Korlat et al., 2021 ; Pelikan et al., 2021 )
The results of the bibliometric analysis showed that the top research organizations in this domain are as follows: the University of Toronto, the University of King Abdulaziz, Jordan University of Science and Technology, the University of Vienna, the University of Sharjah, the University of Granada, the University of Porto, Monterrey Institute of Technology and Graduate Studies, the University of Jordan, and the University of Colorado. The results also illustrate that the top countries are: United States, United Kingdom, China, Spain, Italy, Brazil, Canada, India, Saudi Arabia, Germany, due to several reasons, including the interest of these organizations and countries in publishing in the Web of Science database and their interest in publishing in the subject of the study.
Our research overlaps with that of López-Belmonte et al. (2021) , who tried to investigate the development of e-learning in higher education in the academic literature listed on the WoS. The same analysis, as well as bibliometric analysis, was carried out. The findings revealed no set path for research because of the research on e-learning in higher education, recent creation, and a scarcity of relevant research. According to the results of the bibliometric analysis, the study was aimed at determining acceptance and implementation of the educational curriculum in the teaching and learning processes.
This paper discusses the use of a bibliometric approach to track e-learning trends in higher education during the COVID-19 pandemic through the WoS database. From a methodological perspective, our proposed approach can visually represent the temporal links of the most cited articles internally in various streams and provide a comprehensive overview of the evolution of topics in the WoS database. Also, direct citation network analysis enables researchers to test articles important in e-learning and get a comprehensive overview of the issues published.
The study provided an insight into the world’s e-learning research in terms of mapping research publications. A scientific study was conducted using 602 e-learning documents from 2020 to 2021, and these were obtained through the WoS database. Over the years, the analysis identified trends in contributions in this area and headline sources for most researchers and leading institutions. The study is convergent with many previous studies in this area, including Chiang et al. (2010) , Hung (2012) , Cheng et al. (2014) , Tibaná-Herrera et al. (2018b) , Fatima and Abu (2019) , Bai et al. (2020) , and Mashroofa et al. (2020) . However, our study relies on many software to compare various theoretical models and networks of e-learning.
Based on the analysis data’s inference, growth trends in research publishing in e-learning of different forms have increased in recent years, especially so for the last 2 years (230 in 2020 and 386 in 2021). The significant findings of the bibliometric analysis are as follows: there are nine sub-fields of study in the subject of “E-learning in higher education in COVID-19,” and the prominent authors in this area are as follows: Antonio José Moreno-Guerrero and Marko Lüftenegger; the University of Toronto Canada is the most frequently cited organization in this domain; the United States is the leading country in terms of publications and citations; and the sub-field of artificial intelligence, machine learning, and deep learning to transform the eLearning Industry has emerged as a recent research trend for many scholars.
The study examined a very important topic, which is one of the current topics, “e-learning in higher education during COVID-19,” using bibliometric analysis of 602 studies published in Web of Science databases from 2020 to 2021. We found that the study sample should be larger; it needs further studies and a longer time, especially when we analyze citation, and research on this topic will thus continue in future years. Also, there are many tools and methods used in the bibliometric analysis that were not used in our study, including what has been mentioned ( Tibaná-Herrera et al., 2018b ; Gul et al., 2020 ; López-Belmonte et al., 2021 ; Rashid et al., 2021 ).
The findings of this study will assist interested academics and educational policymakers ( Brika et al., 2021 ) in the field of e-learning in understanding the current state of e-learning and identifying the different research trends in light of COVID-19. Additionally, it will serve as the beginning point for new research during the COVID-19 crisis, which will examine various problems and trends.
The findings of this research may help evaluate e-learning institutions’ quality and promote future educational trends. The findings may be utilized by e-learning institutions to evaluate quality as strategic dimensions and policy makers’ vision.
Data Availability Statement
The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author.
Author Contributions
All authors contributed to the design and implementation of the research, performed the revision, verified the analytical methods, supervised the findings of this work, discussed the results, and contributed to the final manuscript.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Acknowledgments
The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia, to fund this research work through the project number (UB-56-1442).
Supplementary Material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2021.762819/full#supplementary-material
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Keywords : e-learning, higher education, COVID-19, bibliometric analysis, Web of Science (WoS) database
Citation: Brika SKM, Chergui K, Algamdi A, Musa AA and Zouaghi R (2022) E-Learning Research Trends in Higher Education in Light of COVID-19: A Bibliometric Analysis. Front. Psychol. 12:762819. doi: 10.3389/fpsyg.2021.762819
Received: 22 August 2021; Accepted: 31 December 2021; Published: 03 March 2022.
Reviewed by:
Copyright © 2022 Brika, Chergui, Algamdi, Musa and Zouaghi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Said Khalfa Mokhtar Brika, [email protected]
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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Teaching and Learning Theses and Dissertations
Theses/dissertations from 2024 2024.
Beliefs of Male Elementary School Special Education and General Education Teachers Regarding Full Inclusion for Students with Autism Spectrum Disorder in Saudi Arabia , Sultan Alanazi
The Integration of Assistive Technology by Female In-Service Teachers of Students with Learning Disabilities in Saudi Arabia: A Qualitative Interview Study , Badriah Alotaiby
Theses/Dissertations from 2023 2023
Saudi Parents as Advocates for Their Young Children with Disabilities: Reflections on The Journey , Sadeem A. Alolayan
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Graduate Teaching Assistants’ Knowledge and Attitudes Toward Students with Disabilities in Higher Education , Yanlys De La Caridad Palacios
High School Teachers’ Perceptions of Promoting Student Motivation and Creativity through Career Education , Kyeonghyeon Park
The Specifics of Specific Learning Disability: An Analysis of State-Level Eligibility Criteria and Response to Intervention Practices , Lora M. Williams
Theses/Dissertations from 2021 2021
Saudi Early Childhood Educators' Perceptions of Gender Roles in Children's Dramatic Play , Dalal Alanazi
Barriers to Reducing the Assistive Technology use for Students with Autism as Perceived by Special Education Teachers in Saudi Arabia , Othman Ahmed Alasmari
Saudi Teachers’ Perspectives on Implementing Evidence-Based Practices Specifically Designed for Students with Autism Spectrum Disorder , Ahmad Saad Alghamdi
Perceptions of Preservice Teachers of Students with Intellectual Disabilities About their Preparation for Inclusive Education , Abdullah Aljudaya
Experiences of Saudi Arabian Mothers of Young Children with Disabilities: An Exploratory Study , Samirah Bahkali
Persistence Like a Mother: Nursing the Narrative toward Doctoral Completion in English Education—A Poetic Autoethnography , Krista S. Mallo
Warming Up and Cooling Down: Perceptions and Behaviors Associated with Aerobic Exercise , Balea J. Schumacher
A Multimodal Literacy Exploration: Lived Experiences of Haitian Immigrant Adolescent Girls in The Bahamas , Natasha Swann
Theses/Dissertations from 2020 2020
Perceptions of Preservice Teachers of Students with Autism and Intellectual Disabilities in their Teacher Preparation Programs in Saudi Arabia , Salman Almughyiri
Mapping Narrative Transactions: A Method/Framework for Exploring Multimodal Documents as Social Semiotic Sites for Ethnographic Study , Anne W. Anderson
The Effects of Augmented Reality (AR)-infused Idiom Material on Iranian Students’ Idiom Achievements, Motivation, and Perceptions , Babak Khoshnevisan
An Examination of Changes in Muscle Thickness, Isometric Strength, and Body Water Throughout the Menstrual Cycle , Tayla E. Kuehne
How the Use of Learner-Generated Images and Authentic Materials Affects the Comprehension and Production of Vivid Phrasal Idioms in L2 English Learners , Melissa Larsen-Walker
Explore L2 Chinese Learners' Motivation through L2MSS: Selves, Mental Imagery, and Pedagogical Implications , Yao Liu
Exploring Adult Indigenous Latinxs’ English Language Identity Expressions and Agency: A MALP®-informed Photovoice Study , Andrea Enikő Lypka
Theses/Dissertations from 2019 2019
The Use of Assistive Technology with Students with Severe Intellectual and Developmental Disabilities in Saudi Arabia: Teachers’ Perspectives , Khalid Mohammed Abu Alghayth
Saudi Special Education Preservice Teachers’ Perspective towards Inclusion , Sarah Binmahfooz
The Teacher Evaluation Conundrum: Examining the Perceptions of Special Education Teachers , Gordon Brobbey
Illuminating Changes in Preservice Teachers’ Perceptions about Teaching Elementary Mathematicsin an Introductory Methods Course , Elaine Cerrato
International Teaching Assistants’ Perceptions of English and Spanish Language Use at the University of Puerto Rico-Mayagüez , Edward G. Contreras Santiago
Psychological Responses to High-Intensity Interval Training Exercise: A Comparison of Ungraded Running and Graded Walking , Abby Fleming
The Effects and Students’ Views of Teachers' Coded Written Corrective Feedback: A Multiple-Case Study of Online Multiple-draft Chinese Writing , Jining Han
Autism and Inclusion in England’s Multi Academy Trust: A Case Study of a Senior Leadership Team , Danielle Lane
Promoting L2 Idiomatic Competence among Chinese College Students via WeChat , Zhengjie Li
EFL Student Collaborative Writing in Google Docs: A Multiple Case Study , Quang Nam Pham
Threats to Teaching: An Investigation Into the Constructs of Compassion Fatigue in the Classroom , April M. Steen
A New Literacy Coach and Two English Language Arts Teachers Learn Together: A Narrative Inquiry , Christiana C. Succar
Theses/Dissertations from 2018 2018
General Education Teachers’ Perceptions of Response to Intervention Implementation: A Qualitative Interview Study , Adhwaa Alahmari
A Study of Ghanaian Kindergarten Teachers' Use of Bilingual and Translanguaging Practices , Joyce Esi Bronteng
Deaf Lesbian Identity , Noël E. Cherasaro
Beyond Replicative Technology: The Digital Practices of Students with Literacy-Related Learning Difficulties Engaged in Productive Technologies , Aimee Frier
Once Upon a Genre: Distant Reading, the Newbery Medal, and the Affordances of Interdisciplinary Paradigms for Understanding Children’s Literature , Melanie Griffin
Learning in the Margins: The Educational Experiences of an African American Male with Disabilities , Aisha Holmes
Including children with learning differences: Experiences of independent school teachers , Lisa M. Lockhart
The Effects of Music Choice on Perceptual and Physiological Responses to Treadmill Exercise , Taylor A. Shimshock
Theses/Dissertations from 2017 2017
Perceptions of Arab American Mothers of Children with Autism Spectrum Disorder: An Exploratory Study , Haifa Alsayyari
It’s Not All Sunflowers and Roses at Home: A Narrative Inquiry of At-Risk Girls and Their Perceptions of Their Educational Experiences , Jessica Aggeles Curtis
Exploring Mathematics Teacher Education Fieldwork Experiences through Storytelling , Melody Jeane Elrod
Improving Reading Comprehension of Children with ASD: Implication of Anaphoric Reference Support with Computer Programming , Seda Karayazi Ozsayin
A Qualitative Content Analysis of Early Algebra Education iOS Apps for Primary Children , Lissa S. Ledbetter
Cultivating Peace via Language Teaching: Pre-Service Teachers' Beliefs and Emotions in an EFL Argentine Practicum , María Matilde Olivero
Collaboration with Families: Perceptions of Special Education Preservice Teachers and Teacher Preparation , Mehmet Emin Ozturk
Perspectives of AP U.S. History Teachers in Title I Schools , Mark Lance Rowland
What Does It Mean to Be a Service-Learning Teacher? - An Autoethnography , Kristy Causey Verdi
Early Childhood Mathematics Through a Social Justice Lens: An Autoethnography , Jennifer Ward
Theses/Dissertations from 2016 2016
Urban English Language Arts Teachers’ Stories of Technology Use: A Narrative Inquiry , Bridget Abbas
Teachers’ Third Eye: Using Video Elicitation Interviews To Facilitate Kuwaiti Early Childhood Preservice Teachers’ Reflections , Hessa Alsuhail
Foreign Language College Achievement and the Infusion of Three Selected Web 2.0 Technologies: A Mixed Method Case Study , Eulises Avellaneda
Emotional Self-Regulation: Voices and Perspectives of Teachers within Diverse Socio-Cultural Contexts , Anna Paula Peixoto Da Silva
The Effect of Exercise Order on Body Fat Loss During Concurrent Training , Tonya Lee Davis-Miller
Subtext of Decisions: Literacy Practices in the Context of Coding , Julia Hagge
The Role of Prep Schools in the Middle to High School Transition of Students in Southeastern Turkey , Mucahit Kocak
“It’s Not Pixie Dust”: An Exploratory Qualitative Case Study of a School-Based Multimodal Tablet Initiative , Erin Elizabeth Margarella
Influence of Language Arts Instructional Practices on Early Adolescents’ Motivation to Read: Measuring Student and Teacher Perceptions , Sarah E. Pennington
Educators' Oral Histories of Tampa Bay Area Writing Project Involvement , Margaret Hoffman Saturley
Anti-Fat Attitudes and Weight Bias Internalization: An Investigation of How BMI Impacts Perceptions, Opinions and Attitudes , Laurie Schrider
Use of a Game-Based App as a Learning Tool for Students with Mathematics Learning Disabilities to Increase Fraction Knowledge/Skill , Orhan Simsek
Theses/Dissertations from 2015 2015
Examining Experiences of Early Intervention Providers Serving Culturally Diverse Families: A Multiple Case Study Analysis , Wendy Lea Bradshaw
"I want to be the Sun": Tableau as an Embodied Representation of Main Ideas in Science Information Texts , Margaret Branscombe
A Case Study of Teachers' in Professional Learning Communities in a Campus Preschool , Victoria Jacqueline Damjanovic
Student-teacher Interaction Through Online Reflective Journals in a High School Science Classroom: What Have We Learned? , Megan Elizabeth Ehlers
Novice Teachers' Stories of Solving Problems of Practice , Yvonne Franco
Facilitating Motivation in a Virtual World Within a Second Language Acquisition Classroom , Andrew Warren Gump
IWitness and Student Empathy: Perspectives from USC Shoah Foundation Master Teachers , Brandon Jerome Haas
Precalculus Students' Achievement When Learning Functions: Influences of Opportunity to Learn and Technology from a University of Chicago School Mathematics Project Study , Laura A. Hauser
The Role of the Interruption in Young Adult Epistolary Novels , Betty J. Herzhauser
A Conceptual Analysis of Perspective Taking in Support of Socioscientific Reasoning , Sami Kahn
Restricted and Repetitive Behaviors as Strengths, not Weaknesses: Evaluating the Use of Social Stories that Embed Restricted Interests on the Social Skills of Children with Autism Spectrum Disorder , Maya Nasr
Job Satisfaction of Adjunct Faculty Who Teach Standardized Online Courses , Claudia A. Ruiz
Relationships between the Algebraic Performance of Students in Subject-Specific and Integrated Course Pathways , Derrick Saddler
The Common Core State Standards: Its Reported Effects on the Instructional Decision Making of Middle School Social Studies Teachers , Tracy Tilotta
The Influence of Types of Homework on Opportunity to Learn and Students' Mathematics Achievement: Examples from the University of Chicago School Mathematics Project , Yiting Yu
Theses/Dissertations from 2014 2014
Picturing the Reader: English Education Pre-service Teachers' Beliefs About Reading Using Photovoice , Michael Dicicco
The Effect of Music Cadence on Step Frequency in the Recreational Runner , Micaela A. Galosky
Balanced Artistry: Describing and Explaining Expert Teacher Practice as Adaptive Expertise , Nina Graham
The Fight Within: Experiences of School District Employees Who Advocate for the Rights of Their Own Children with Disabilities Inside the Districts Where They Work, a Heuristic Case Study , Keri Haley
A Phenomenological Study of the Experiences of Higher Education Students with Disabilities , Allen J. Heindel
Constructing an "Appropriate" Education in Florida Special Education Due Process Final Orders , Michelle Henry
The Effect of Teachers' Epistemological Beliefs on Practice , Milton David Huling
Perceptions, Beliefs and Practices about Technology among Teachers in a Jamaican Infant School , Suzette Anissia Kelly
"Choosing My Words Carefully": Observing, Debriefing, and Coaching Four Literacy Teachers' Through Their Lessons , Iveta Maska
Presentation of Civic Identity in Online High School Social Studies Discussion Forums , Holly Mcbride
In Our Image: The Attempted Reshaping of the Cuban Education System by the United States Government, 1898-1912 , Mario John Minichino
The Hypertrophic Effects of Practical Vascular Blood Flow Restriction Training , John Francis O'halloran
Science Teachers' Understandings of Science Practices before and after the Participation in an Environmental Engineering Research Experiences for Teachers (RET) Program , Dilek Özalp
The Effects of Emotive Reasoning on Secondary School Students' Decision-Making in the Context of Socioscientific Issues , Wardell Anthony Powell
Interagency Collaboration for the Provision of Services to Migrant Children with Disabilities: An Exploratory Study , Georgina Rivera-Singletary
Reflections in the Classroom: Perspectives on Teaching for Social Justice from Secondary Social Studies Educators , Gregory Lee Samuels
A Case Study of the Roles and Perceptions of Writing Coaches , Amy June Schechter
Genres of Children's Websites: A Comprehensive Methodology for Analyzing Digital Texts , James L. Welsh
Theses/Dissertations from 2013 2013
Attitude Toward Digital and Print-Based Reading: A Survey for Elementary Students , Diedre D. Allen
Playing in Trelis Weyr: Investigating Collaborative Practices in a Dragons of Pern Role-Play-Game Forum , Kathleen Marie Alley
Curriculum Gatekeeping in Global Education: Global Educators' Perspectives , Robert Wayne Bailey
Reading Assessment Practices of Elementary General Education Teachers: A Descriptive Study , Sarah Mirlenbrink Bombly
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- In order to be eligible, noncitizens must – as of June 17, 2024 – have resided in the United States for 10 or more years and be legally married to a U.S. citizen, while satisfying all applicable legal requirements. On average, those who are eligible for this process have resided in the U.S. for 23 years.
- Those who are approved after DHS’s case-by-case assessment of their application will be afforded a three-year period to apply for permanent residency. They will be allowed to remain with their families in the United States and be eligible for work authorization for up to three years. This will apply to all married couples who are eligible.
- This action will protect approximately half a million spouses of U.S. citizens, and approximately 50,000 noncitizen children under the age of 21 whose parent is married to a U.S. citizen.
Easing the Visa Process for U.S. College Graduates, Including Dreamers
- President Obama and then-Vice President Biden established the DACA policy to allow young people who were brought here as children to come out of the shadows and contribute to our country in significant ways. Twelve years later, DACA recipients who started as high school and college students are now building successful careers and establishing families of their own.
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DISSERTATION GLOBAL E-LEARNING: A PHENOMENOLOGICAL STUDY Submitted by Sudendra R. Rao School of Education In partial fulfillment of the requirements For the Degree of Doctor of Philosophy Colorado State University Fort Collins, Colorado Fall 2011 Doctoral Committee: Advisor: Don Quick Jim Banning
PhD Summary E-learning has emerged as a necessity to meet the challenges posed by the development of information technology and its potential for greater access to ... This thesis gives an account of the research undertaken by Mubarak Al-Kharang. Some of the material contained herein has been accepted and presented in the form of
e-Learning experience, in terms of, providing a quality educational experience, as well as, the means to obtain a degree? This chapter provides a discussion of the problem statement, which demonstrates the significance of the problem by referencing earlier works of e-Learning practice and evaluation,
This is a broad definition, but in the abstracts of papers examining higher education, the definition is often clarified in terms of measurements; for example: 'Student learning measurements included: pre-test, final examination (post-test) and final letter grade' (Boghikian-Whitby and Mortagy, 2008).
A. (2021). The impact and effectiveness of e-learning on teaching and learning. International Journal. Sciences Research, 5(1), 383-397. doi: 10.25147/ijcsr.2017.001.1.47Abstract Purpose - This paper presents research findings on the effectiveness and impact of E-Learning to the teaching and learning process of the Undergraduate Program (UGP ...
which structures e-learning barriers, was developed; to consolidate literature from the past 26 years (1990-2016). 259 papers concerning e-learning barriers, was included in the framework, to better understand the barriers that hinder e-learning implementation. TIPEC framework comprises of 68
foster a learning environment where students have technology experiences that enhance and transform their learning. The integration of technology-enhanced learning (TEL) tools and applications has become ubiquitous throughout all levels of education. The phenomenon of this study is based on the integration of TEL tools and applications into ...
3.3 Perceived ease of use of e-learning. Perceived ease of use is defined as "the extent to which students believe that e-learning will be easy to use" (Lee et al., 2009, p. 1324).Cheng (2012) stated that the PEOU of e-learning impacts the intention to use e-learning, although it may be that PEOU has a weaker effect on the intention to use e-learning, than PU (Lee et al., 2009, p. 1327).
A thesis submitted for the degree of Doctor of Philosophy by Joharah Alzahrani College of Engineering Design and Physical Sciences ... E-learning is growing in stature as an alternative channel of teaching and learning (Croxton, 2014). There are several reasons why e-learning is becoming popular. For example, it allows
Request PDF | Tools and Evaluation Techniques for Collaborative Online Learning Communities Niki Lambropoulos' PhD Thesis | This study provides new multidisciplinary approaches for tools and ...
PhD 2013 UNIVERSITY OF BEDFORDSHIRE ... Intentions in Learning Management Systems by ABDULLAH AL-AULAMIE A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of Philosophy September 2013 . ABSTARCT E-learning has become the new paradigm for modern teaching moreover, the ...
The e-learning library is an electronic library embedded into an integrated virtual learning environment centred around a partly web-based digital repository. The e-learning library provides easily acessible and retrievable electronically and digitally stored learning resources and illustration materials required for teaching and learning.
A CRITICAL ANALYSIS OF THE IMPLEMENTATION OF E-LEARNING PLATFORMS AT SELECTED PUBLIC UNIVERSITIES IN ZIMBABWE Submitted in fulfilment of the requirements of the ... Richard Munyanyi hereby declare that this dissertation submitted for a Doctor of Philosophy in Public Administration, Faculty of Management Sciences at the Durban
Join our part-time Doctoral Programme in E-Research and Technology Enhanced Learning to carry out your own research and achieve a PhD. (Undertaken over a minimum of four years). We have designed this programme for anyone in the world who wants to develop their research practice in this area. Although you will mainly learn online, you will also ...
This thesis deals with e-learning in the context of a developing country. The aim of the study was to describe and understand teachers' beliefs about e-learning in higher education at UMSA. Qualitative semi-structured interviews and observations were used to identify 10 teachers' beliefs about e-learning.
This paper will discuss bibliometric indicators for e-learning in higher education during COVID-19 studies and proceed with a network analysis to define the most important sub-areas in this topic. To define the trends of e-learning in higher education during COVID-19, the following questions are proposed:
result that lies in front of you: my PhD about e-Learning strategies of higher education institutions. Writing my PhD was a combination of having the emergence of ideas, theories and results and a planned, practical and structured process. It is about ideas that were not present at all when I started as a researcher at CHEPS in 1996.
Phd Dissertation on E-learning - Free download as PDF File (.pdf), Text File (.txt) or read online for free. This document discusses the challenges of writing a Ph.D. dissertation on e-learning, including the extensive research, analysis, and understanding required. It notes that the dissertation process takes significant time and effort, involving original research, data collection and ...
The doctoral thesis Desplegar menu The doctoral thesis The doctoral thesis. Showcase of doctoral theses; Doctoral theses submitted; Researcher's Kit ; Resources for preparing your doctoral thesis ; How to PhD at UOC; Co-supervision and international degree; Log in to the Campus; ... Socio-technical lifelong e-learning for the 21st Century ...
R. P. obtained the results. R.P. and P.E.L. wrote the paper. 4. In which chapter(s) of your thesis can this material be found? Chapter 2 5. e-Signatures confirming that the information above is accurate (this form should be co-signed by the supervisor/ senior author unless this is not appropriate, e.g. if the paper was a single-author work):
Theses/Dissertations from 2019. PDF. The Use of Assistive Technology with Students with Severe Intellectual and Developmental Disabilities in Saudi Arabia: Teachers' Perspectives, Khalid Mohammed Abu Alghayth. PDF. Saudi Special Education Preservice Teachers' Perspective towards Inclusion, Sarah Binmahfooz. PDF.
Phd Thesis in E-learning PDF - Free download as PDF File (.pdf), Text File (.txt) or read online for free. The document discusses the challenges of completing a Ph.D. thesis in e-learning, including extensive research, synthesizing vast information, and meeting the field's unique requirements. It introduces HelpWriting.net, which offers expert assistance through all stages of writing ...
E- Learning Paper instructions: I need a research paper on an evaluation plan to be conducted on a model for assessing readiness of faculty members in crises countries such as Libya, Tunisia and Egypt. The model has been developed with its Assessment Measurement Instrument and the methods chosen for evaluation are case studies. However, in […]
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