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The purpose of this study was to obtain valuable insights into students’ engagement and experiences within the virtual learning environment, especially in the context of crises. Among the innumerable challenges people throughout the world faced during the first year of the COVID-19 pandemic, those of students in institutions of higher education needing to engage in online academic studies are of special interest. Using an online survey, this study could predict students’ online engagement during the COVID-19 pandemic through three theoretical frameworks: the students’ academic motivation to study, the Big Five personality traits, and loneliness, and with a new tool measuring the participation in the Zoom platform.

To examine the psychological and technological factors predicting the students’ engagement, this study surveyed 547 students from different academic institutions of higher learning.

Findings show that the less lonely the students felt, the less neurotic they were, and the higher they scored in levels of extroversion, agreeableness, consciousnesses and openness to experience, the greater their engagement in their academic studies. In addition, students who were older, more educated, with higher intrinsic motivation and lower lack of motivation were more engaged in their online academic studies. Finally, participating in classes through the Zoom platform and experiencing it positively was a significant predictor of higher academic engagement.

Recognizing these factors can enable educators, institutions of higher learning, counselling services and students to obtain tools for higher engagement in online learning.

We aimed to identify factors that influence student engagement in distance learning.

The research involved a group of 671 students from economic and technical higher education institutions in Poland. We collected the data with the CAWI technique and an original survey. Next, we processed the data using principal component analysis and then used the extracted components as predictors in the induced smoothing LASSO regression model.

The components of the students’ attitude toward remote classes learning conditions are: satisfaction with teachers’ approach, attitude to distance learning, the system of students’ values and motivation, IT infrastructure of the university, building a network of contacts and communication skills. The final model consisted of seven statistically significant variables, encompassing the student’s sex, level of studies and the first five extracted PCs. Student’s system of values and motivation as well as attitude toward distance learning, were those variables that had the biggest influence on student engagement.

The research result suggests that in addition to students’ system of values and motivation and their attitude toward distance learning, the satisfaction level of teachers’ attitude is one of the three most important factors that influence student engagement during the distance learning process.

The main value of this article is the statistical model of student engagement during distance learning. The article fills the research gap in identifying and evaluating the impact of various factors determining student engagement in the distance learning process.

Feedback is crucial in a learning process, particularly in an online interaction where both learners and instructors are distantly located. Thus, this paper aims to investigate the association between feedback strategies, embedded course syllabus and learning improvement in the Sakai Learning Management System.

This paper uses a survey design to collect cross-sectional data from adult distance learning students. The data were analysed using descriptive statistics and a standard multiple regression model in Stata.

The results show that feedback strategies (timing, mode, quality and quantity) and embedded course syllabus have a significant relationship with learning improvement. However, the feedback strategy – target – is not significantly related to learning improvement though it is the highest feedback strategy.

This paper has contributed to the extant literature by providing empirical evidence to support the constructivism theory of learning from a distance learning perspective in a developing country. The study has shown that if the feedback strategies are well managed and applied, they would make a considerable impact on distance education students' academic pursuits. Hence, the paper provides a pedagogical foundation for short and long-term distance learning policy.

Amidst the COVID-19 pandemic, education has shifted to online teaching and learning. Interactivity is a crucial tool used to make online education effective. This study empirically examines the role of interactivity in higher education and its influence on students' behavioral outcomes, specifically focusing on soft skills and personality upgradation.

A quasi-experimental research design was carried out for post-graduate students undergoing a business communication course from four major institutions. For analysis, t-test, confirmatory factor analysis (CFA) and partial least squares structural equation modeling (PLS-SEM) have been employed. Experimental research has established the causal relationship between interactivity, personality and soft skill upgradation (SSU).

It was found that the theoretical structural model has a rational model-fit validity. Resultantly, practitioners may use prior knowledge of virtual community (VC) members to enhance web interactivity, thereby increasing social identity and social bonds in a group for more meaningful and effective delivery of online courses.

The major limitations lie in its context-dependent nature, predominantly influenced by the pandemic-induced mandatory online learning. The study's cross-sectional design also inhibits its ability to assess goal-directed behaviors over time, necessitating further longitudinal research.

The study is one of the pioneering pieces of research that examines the role of pre-defined grouping and enhanced web interactivity in VCs in the context of online learning, especially during the COVID-19 pandemic. Integrating theories of web interactivity, social bond theory (SBT) and social identity theory (SIT) provides a novel understanding of cognitive and social influences that drive meaningful online discussions and their impacts on knowledge enhancement and personality development. Its findings have implications for the design of effective online learning environments and e-learning pedagogy, contributing to the growing domain of information and communication technology (ICT)-enabled education.

The COVID-19 pandemic has compelled higher educational institutions to implement alternative educational strategies that rely heavily on internet accessibility and utilisation to monitor and evaluate students. This study aims to find certain indicators for planning and designing future courses of inclusive online education in the domain of disaster risk reduction (DRR).

The study reviews and analyses online teaching and learning experiences of DRR courses. It uses online surveys and interviews to derive the perspectives of selected students and educators in universities in Asia and the Pacific region.

Active engagement is considered to be achieved when students are active in chat boxes, through presentations, through assignments and when the video cameras of students are turned on. On the contrary, students perceive active engagement differently because they face emotional disturbances and health issues due to prolonged screen/digital device use, have inadequate information and communications technology infrastructure or have digital literacy deficiencies among others. The study finds that online courses have many sets of strengths, weaknesses, opportunities and threats, when they are balanced, they can improve DRR courses in the future.

The study is based on the outcome of interviews with 10 experienced educators in DRR courses as well as students from different schools taking courses in DRR education. However, the students are not necessarily taking the courses of the educators interviewed due to the inability of some educators to avail themselves and the challenge of contacting the students. This notwithstanding, the results of this study give a general overview of the situation to be considered in the planning and design of online and distance education.

The results do not reflect the reaction of students and tutors of the same course. Future studies of collecting and analyzing the responses from the students and the educators with the same course could provide tailored solutions.

This study attempts to find solutions to bridging two different perspectives on teaching and learning. The results would be important to strengthening and designing future online courses.

This study aims to reveal the impact of e-learning on accounting education amid COVID-19 in Jordanian universities from the viewpoint of faculty members.

The questionnaire is used as a study instrument distributed to faculty members at the Accounting Departments of the Jordanian public and private universities. Due to the COVID-19 pandemic, Google Forms has been used to distribute 117 questionnaires that have been analyzed via the partial least squares-smart program.

The results show a negative impact of learning difficulties on accounting education, a negative impact on the personal skills of faculty members on the digitization of accounting education, no impact on the personal skills of faculty members, a positive impact on training courses, the use of technology on accounting education and the digitization of accounting education, as well as a positive impact on the skills of faculty members on the digitization of accounting education.

These results are significant in determining the adequacy of online learning for accounting education at the Accounting Departments of Jordanian public and private universities from the viewpoint of faculty members amid COVID-19.

This study highlights the impact of the e-learning system imposed amid COVID-19 on accounting education, teaching efficiency and the future of accounting education.

This paper aims to explore the significance of videoconferencing in blended learning, using the technology acceptance model to investigate students’ perceptions and its impact on course engagement, student satisfaction and future technology use intention. In addition, it examines the role of teacher support in fostering interactive virtual learning experiences.

This study focuses on a cohort of international students regarding blended courses amid the COVID-19 pandemic when the conventional face-to-face components were substituted with virtual classrooms through videoconferencing. It aims to investigate how to facilitate connectivity between Southeast Asian students and their professors located in a Southern state in the USA.

This study reveals that the perceived usefulness of videoconferencing predicts future intention to use, emphasizing the vital role of teacher support in engaging students in virtual classrooms and contributing to student satisfaction.

The small sample of international students in blended courses with an American university during the COVID-19 pandemic may limit the generalization of the findings.

Videoconferencing can be a valuable tool to enhance connectedness in digital learning post pandemic.

Videoconferencing in blended learning can bridge geographical barriers and provide access to diverse learners who might otherwise have limited educational opportunities.

This study supports the integration of videoconferencing as a mechanism for providing high-quality digital learning experiences.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether media richness (MR), human-system interaction (HSI) and human-human interaction (HHI) as technological feature antecedents to medical professionals’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from medical professionals at six university-/medical university-affiliated hospitals in Taiwan. A total of 600 questionnaires were distributed, and 309 (51.5%) usable questionnaires were analyzed using structural equation modeling in this study.

This study certified that medical professionals’ perceived MR, HSI and HHI in MOOCs positively affected their emotional LE, cognitive LE and social LE elicited by MOOCs, which together explained their LP in MOOCs. The results support all proposed hypotheses and the research model accounts for 84.1% of the variance in medical professionals’ LP in MOOCs.

This study uses the S-O-R model as a theoretical base to construct medical professionals’ LP in MOOCs as a series of the psychological process, which is affected by MR and interaction (i.e. HSI and HHI). Noteworthily, three psychological constructs, emotional LE, cognitive LE and social LE, are adopted to represent medical professionals’ organisms of MOOCs adoption. To date, hedonic/utilitarian concepts are more commonly adopted as organisms in prior studies using the S-O-R model and psychological constructs have received lesser attention. Hence, this study enriches the S-O-R model into an invaluable context, and this study’s contribution on the application of capturing psychological constructs for completely explaining three types of technological features as external stimuli to medical professionals’ LP in MOOCs is well-documented.

This paper aims to consolidate empirical studies between 2013 and 2022 to investigate the impact of artificial intelligence (AI) in higher education. It aims to examine published research characteristics and provide insights into the promises and challenges of AI integration in academia.

A systematic literature review was conducted, encompassing 44 empirical studies published as peer-reviewed journal papers. The review focused on identifying trends, categorizing research types and analysing the evidence-based applications of AI in higher education.

The review indicates a recent surge in publications concerning AI in higher education. However, a significant proportion of these publications primarily propose theoretical and conceptual AI interventions. Areas with empirical evidence supporting AI applications in academia are delineated.

The prevalence of theoretical proposals may limit generalizability. Further research is encouraged to validate and expand upon the identified empirical applications of AI in higher education.

This review outlines imperative implications for future research and the implementation of evidence-based AI interventions in higher education, facilitating informed decision-making for academia and stakeholders.

This paper contributes a comprehensive synthesis of empirical studies, highlighting the evolving landscape of AI integration in higher education and emphasizing the need for evidence-based approaches.

Self-regulation is the level of learning where the learner becomes an active agent in their learning process in terms of activity and aspects of motivation and metacognition. The current paper mostly deals with the metacognitive aspect. The purpose of this study is to gain insight into self-regulation of learning in the context of modern technology in higher education. This study also aims to highlight the direction, tendencies and trends toward which self-regulation of learning is moving in relation to modern technologies.

The review study was compiled via searches in three databases: Scopus, Web of Science and ERIC. A filter was used to search for empirical studies solely in English, published over the past decade on the topics of self-regulation of learning and technology in higher education.

The findings clearly show a correlation between self-regulation of learning and modern technology, especially after a significant event such as the Covid-19 pandemic. However, in the wake of this change, the field of education has seen the emergence of methods and new platforms that can provide support for the development of self-regulated learning strategies.

The originality of the study lies in the fact that it focuses on the link between self-regulation of learning and modern technologies in higher education, including some predictions of the future direction of self-regulation of learning in this context.