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The purpose of this paper is to examine the effect of gamification on students’ e-learning adoption. In addition, this paper examines the effect of two mediations, that is, flow and engagement between gamification and e-learning adoption by using sequential mediation analysis.

The authors used the online survey method to collect the 570 responses through convenience sampling procedure. Sequential mediation analysis technique was used to test the mediation hypothesis.

The findings of this paper revealed that gamification elements are an important feature of flow, engagement in e-learning adoption process. Also, the paper found that engagement in the learning process is a key element for students to adopt e-learning.

This paper makes its contribution to the literature related to gamification and e-learning adoption. The paper signifies the importance of gamification as an educational application in e-learning environment and its contribution in designing an interactive learning environment.

Empirically, to the best of the authors’ knowledge, it is the first paper to examine the sequential mediation model of gamification in the education sector in a developing nation like India. Furthermore, this paper also extends engagement and flow theory related to e-learning process by showing how students’ engagement and flow impact the e-learning adoption in the gamified environment.

Due to the growing complexity involved in leveraging the endless possibilities of ICT on all levels, the technical competence of faculties of higher education institutions (HEI) and effective methods for fostering e-readiness has become questionable.

This research has developed and validated an empirically supported e-readiness scale, which can be used by HEIs to assess faculty members’ preparedness toward online teaching. The measurement model and the structural model were developed as the results of exploratory factor analysis and confirmatory factor analysis (n = 245). The previously identified components and their indicators were validated using the structural models and the final scale was developed with five dimensions (“online technological readiness, pedagogical readiness, institutional readiness, learning and delivery readiness and content readiness”).

The faculties’ e-readiness assessment tool, as a useful tool, could aid institutions in identifying problems that affect the implementation of e-learning or digitalization in the institutions and developing strategies in response.

Like any research this research also has some limitations and can be considered as future research probability like the responses for this research were collected from HEI in India; however, a cross-cultural study can be conducted to understand the parameters across the globe. Although the psychometric qualities of the e-readiness scale are acceptable, additional research in various higher educational environments, both nationally and internationally, is required to further establish the scale’s relevance, validation and generalizability.

Although many scales have been developed to assess the readiness level in the education sector, a scale, that holistically measures, the readiness level of faculties from an overall perspective was required. This scale can be used to recognize the e-readiness level of teachers in HEIs. This scale can also help the institutions assess the readiness level of their faculty members and address any improvements required in their teaching and learning pedagogy, further acknowledging training needs.

The purpose of this study is to analyze the combined effect of eight factors – performance expectancy (PE), effort expectancy (EE), hedonic motivation (HM), system quality (SQ), information quality (IQ), service quality (SEQ), digital literacy (DL) and computer anxiety (CA) on learners’ behavioral intention (BI) toward the adoption of e-learning in higher education institutions (HEIs) in India.

The study used factors from two theoretical models, the extended Unified Theory of Acceptance and Use of Technology and the DeLone and McLean Information Systems Success model. The study also considered DL and CA as additional factors because they could affect a learner’s intention in a developing country like India. Data were collected from three HEIs in Southern India and analyzed using fuzzy qualitative and comparative analysis (fsQCA).

The results of the study emphasize the importance of considering both individual and technological factors in e-learning adoption and provide evidence for the significance of integrating multiple theories in understanding the complex relationship between factors and learners’ BI. Four different configurations of the eight factors: EE*HM*SQ*IQ*SEQ*DL*∼CA; PE*EE*HM*SQ*IQ*DL*CA; PE*EE*HM*IQ*SEQ*DL*CA; and PE*EE*SQ*IQ*SEQ*DL*CA found to be sufficient to cause learners’ BI to use e-learning.

This study explores the complex relationship between different factors and learners’ intention to adopt e-learning using the fsQCA method. These findings may need further validation in HEIs across different geographical locations.

This study provides practical insights for HEIs in India and other developing countries on how different factors combine and interact to determine e-learning adoption in multiple contexts.

Using fsQCA as a novel and rigorous method, this study uncovers the complex and nonlinear causal relationships among various factors that affect e-learning adoption. This study provides a holistic and contextualized understanding of e-learning adoption in a developing country’s scenario. This study can inform educators and policymakers on how to design and implement effective e-learning strategies that suit different learner profiles and contexts.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Performance expectancy is the strongest predictor of intention to use e-learning. Various combinations of UTAUT model-based antecedents of acceptance of workplace e-learning are supported.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The purpose of this paper is to explore future directions in E-learning research by analysing data from Scopus indexed publications in order to have a comprehensive overview of the trends and thematic focus post COVID-19 in Asian context.

The paper uses Vos viewer and Biblioshiny software packages to analyse the bibliometric data. This software helped in identifying the anatomy of E-learning and their themes which were instrumental in forecasting future trends.

The paper depicts the trends in post COVID-19 E-learning research in Asian context. It identifies key publications, authors and journals in the field, with a focus on numerous networks of collaboration between writers and nations, identifying keyword clusters and co-citation analysis clusters. This study also explored that China and the USA are having maximum number of collaborations, whereas, countries like India, the United Kingdom, Singapore and New Zealand have comparatively weaker collaboration networks. So there is lot of potential for these countries for such collaborations. India is the most cited country globally and China is having maximum number of scientific productions per year.

The paper has been written by exclusively referring to Scopus database papers. Collecting data from different databases would significantly improve the study. Future researchers can also focus on papers from psychology, computer science and engineering fields as current work is based on open access articles on social business, business and arts and humanities.

This research will be useful to educational institutions that use these platforms to offer E-learning content and match future trends. This study will help researchers in understanding the new dimensions in the field of E-learning.

The current study uses bibliometric analysis to examine the association between E-learning, higher education and COVID-19. It aids in the identification of new difficulties within the complex and expanding study fields in the world of E-learning. Newly published studies on E-learning trends can improve understanding and bridge the knowledge gap. As a result, recommendations can be made to improve and implement newer strategies in field of education.

This study aims to focus on the Artificial Intelligence of Things (AIoT) course. As AIoT has many theoretical theories and students usually have little interest in learning the protocols, the experiments can help stimulate their curiosity. Due to the environmental factor, the teaching requires assistive videos and Problem-Based Learning (PBL) to understand students' learning conditions.

The experimental design generally follows the course theories going from easy to complex, and students can extend the acquired concepts to other project development, yet, without in-depth knowledge about the experiment, resulting in limited creativity.

The assessment analysis can reveal whether students have grown from the teaching. The final analysis at the end of the term can show learners' conditions; meanwhile, students can deliver their level of satisfaction. The click-and-mortar teaching environment provided in this research can improve learning setting and quality, solidifying learners' proficiency.

The research result has proved the feasibility of the proposed method. Apart from showing the experimental steps, the video also explains the corresponding theories, helping students reinforce experimental knowledge and boost learning willingness.

The objective of this study is to investigate the key determinants affecting the acceptance and utilization of Blackboard as a Computer-Assisted Language Learning (CALL) platform among Saudi university students pursuing English as a foreign language (EFL) courses.

Understanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.

The study's findings indicate that performance expectancy, social influence, effort expectancy and price value significantly affect the attitudes of EFL students toward using CALL. The habit factor was the most robust predictor of behavioral intention and technology use, indicating that CALL usage can become automatic for students and improve their engagement in EFL learning. The study highlights the importance of providing better technical and organizational support to EFL students who want to use CALL more effectively. The theoretical and practical implications of the study's findings are thoroughly discussed.

Understanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the UTAUT2 by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.

The Metaverse is an immersive virtual world where individuals interact with each other using an avatar. The Metaverse is promised to offer several potentials for different sectors. While the Metaverse promotes innovative interaction between individuals (e.g. learners), there is a scarcity of knowledge on what influences its acceptance and use in higher educational institutions (HEIs), particularly in developing countries. Thus, this paper aims to identify the factors that affect the users' intentions toward Metaverse technology for educational purposes in the HEIs in Jordan.

A study model was created by incorporating variables from the unified theory of acceptance and use of technology (UTAUT) (performance expectancy, PE; effort expectancy, EE; social influence, SI; and facilitating conditions, FC) and information system success (ISS) model (user satisfaction, SAT; system quality, SQ; service quality, SVQ and information quality, IQ) with perceived curiosity (PC) and hedonic gratification (HG) constructs. Both PC and HG were added as context-related factors that could contribute to improving the applicability of UTAUT and ISS to a wide range of technology use contexts. Data were gathered from 441 Jordanian university students using an online questionnaire.

The analysis of the structural model revealed that users' behavioural intentions toward using Metaverse were significantly affected by user satisfaction (SAT), performance expectancy (PE), facilitating conditions (FC) and hedonic gratification (HG). Also, information quality (IQ) and services quality (SVQ) were revealed to have a significant influence on user satisfaction. Likewise, the results illustrated a significant impact of systems quality (SQ), information quality (IQ) and service quality (SVQ) on PE. Lastly, a significant effect of PC on the EE factor was found.

This study will shed light on a number of practical implications for developers, designers, service providers and decision-makers supporting the acceptance and adoption of the Metaverse technology in the educational context. Also, it will contribute to developing the right strategies, and Metaverse content which will draw the attention of learners.

As per the surveyed literature and the researcher's prior knowledge, this is one of the first studies that integrate the UTAUT model, ISS model and two contextual factors (PC and HG) besides testing the proposed model in a developing country (Jordan). This paper is one of the few in which the individuals' acceptance behaviour of Metaverse technology was examined in the HEIs context.

The purpose of this study is to identify the factors that influence the willingness of Saudi Arabian students from four universities in Saudi Arabia, to adopt learning management systems (LMSs). This will be accomplished by using two popular technology acceptance models unified theory of acceptance and use of technology (UTAUT) and theory of planned behavior (TPB).

In total, 445 undergraduates from four Saudi educational institutions participate in filling out the study questionnaire. To investigate the correlations between the variables, the study used structural equation modeling for data analysis.

The results of the study show that effort expectancy (EE), subjective norm (SN), attitude toward behavior (ATB) and perceived behavioral control (PBC) are found to be substantially connected with their intentions to use (ITU) LMSs. The findings also show that there is a strong relationship between students’ intentions and their actual use of LMSs.

Like many studies, this research has some limitations. The primary limitation is that the findings of the study cannot be extrapolated to other settings since the report’s analysis and investigation were limited to four Saudi universities. Therefore, to generalize the study’s findings, similar research needs to be conducted in other Gulf and similar cultural universities.

The integrated model identifies key factors that influence the intent of Saudi Arabian students to use LMS, including EEs, social influence, ATB and PBC. This model can help develop solutions for the obstacles that prevent students from using LMS. The findings can be used to provide assistance to increase the likelihood of LMS acceptance as part of the educational experience. The model may also inspire further research on this topic in the Gulf nations, particularly in Saudi Arabia.

As none of the relevant studies conducted previously in Saudi Arabia has integrated the two models to study the students’ ITU LMSs, this study combines two major theories, TPB and UTAUT, in the context of Saudi Arabia, contributing to the field of technology use in education by expanding empirical research and providing a thorough understanding of the challenges associated with the use of LMS in Saudi universities. This study should be viewed as filling a crucial gap in the field. Moreover, this integrated model, using more than one theoretical perspective, brings a thorough comprehension of the barriers that hinder students’ adoption of LMSs in the academic context in Saudi Arabia and thus assists in making effective decisions and reaching viable solutions.

The study aims to investigate students' attitudes toward using technology for micro-credential programs (MCPs) and their behavioral intention toward using MCPs for learning and enhancing their skills. The study also intends to investigate the moderating influence of labor market conditions (LMC).

A closed-ended questionnaire is employed to collect data from 474 participants through a convenience sample, from the university students in Karachi. Two theoretical frameworks are used in the study: technology acceptance model (TAM) and self-determination theory (SDT). The partial least squares structural equation modeling (PLS-SEM) technique is used to analyze data.

Findings reveal significant and positive relationships between all variables, except controlled motivation (CM) and perceived challenges. Moreover, the moderation results ascertain that the labor market does not moderate the relationship between attitude toward using technology for MCPs and students' behavioral intention toward using MCPs for learning.

The study seeks to understand students' attitudes and behavioral intentions toward using technology for MCPs. Also, the moderating effect of LMC is highlighted in understanding the impact of the attitude to use technology (AT) for MCPs and behavioral intentions in higher educational institutions (HEIs) in Pakistan. The study highlights intuitive practical implications for students of HEIs, universities and digital credential program providers.