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Technology acceptance research in the L&T contexts has a necessity for enabling the significant inclusion of technology in educational settings (Scherer et al., 2019). Despite the propensity for information communication and technology to enhance the teaching and learning process, the acceptance or rejection of learning technology is essential. Technological acceptance model (TAM) has evolved to become a key model to depict the predictors of human behaviour towards prospective rejection or acceptance of technology (Granic and Marangunic, 2019). In their recent systematic review of the extensive literature on TAM, Granic and Marangunic (2019) found that most of TAM research originate from Asia (Taiwan, Malaysia, South Korea and China), Europe, North America, Middle East and Africa. To the best of the authors’ knowledge, research on TAM has been very scarce in small island economies. This study aims to guide the empirical model of Al-Fraihat et al. (2020), which wants to uncover the quality of learning by understanding the intentions and satisfaction of tertiary education learners on the acceptance and use of information technology (IT) for e-learning, during the confinement period.

This study adopted a quantitative approach. The proposed framework was borrowed from Al-Fraihat et al. (2020) and amended based on the contextual aspect of the study. The model proposed by Al-Fraihat et al. (2020) takes into consideration the quality of e-learning through technical system quality, information quality, service quality, educational system quality, support system quality, learner quality and instructor quality. The framework has as the basis the TAM where the perceived satisfaction, perceived usefulness, use and benefits of E-learning have been evaluated. This current study evaluated the quality of the e-learning platform from the students’ perspective in the confinement period. The service quality construct has been broken into three different dimensions, namely, service quality from an IT perspective, service quality from an administration perspective and service quality from the faculty represented by the Head of Departments. Another dimension has been added so as to evaluate the learner’s point of view when studying during confinement, namely, confinement and learning quality.

The findings of this study did not support H25, that is the hypothesis that perceived usefulness has a positive relationship with perceived satisfaction, in contradiction to similar previous studies that confirmed the relationship (Al-Sabawy et al., 2011; Al-Fraihat et al., 2020). However, interestingly, the findings of this research supported the relationship between perceived satisfaction and benefits (H26). This means that the greater the satisfaction of the learner, the greater the benefits on students. The results of this study further supported that there is a positive relationship between perceived usefulness and benefits (H27); there is a positive relationship between perceived usefulness and use (H28); and finally, there is a positive relationship between use and benefits (H29). Such relationships were also found in the existing literature (Al-Sabawy et al., 2011; Cidral et al., 2018; Al-Fraihat et al., 2020). The perception of the usefulness of the e-learning system determines the benefits, usefulness and system use. When the learners feel that the system is enhancing their learning, learning activities and performance, hence learning more effectively, they tend to see the e-learning system as useful and they are more likely to use the e-learning system/tool. The use of the tool/system, thus positively impacts the benefits that the learners derived from the system.

The COVID-19 and overnight decision for a country-wide lockdown drastically changed the education sector. School and all teaching institutions were closed. However, most universities had to review their teaching and learning models to introduce e-learning to ensure the semester’s progress. Hence, the use of the various LMS tools became a necessity overnight. This study on e-learning in Mauritius uses the TAM as the theoretical foundation because the theory has long been extensively used to investigate the quality of learning eg. Davis (1989), Scherer et al. (2019), Al-Fraihat et al. (2020).

The purpose of this study is to propose a hybrid model integrating the expectation-confirmation model with the views of cognitive absorption (CA) theory and updated DeLone and McLean information system success model to examine whether quality factors as antecedents to medical professionals’ beliefs can affect their continuance intention of the cloud-based e-learning system.

This study’s sampling frame was taken from among medical professionals working in hospitals with over 300 beds in Taiwan which had implemented the cloud-based learning management system (LMS) with a blend of asynchronous and synchronous technologies. Sample data for this study were collected from medical professionals at six hospitals in Taiwan. The data for this study were gathered by means of a paper-and-pencil survey, and each sample hospital that participated in this study was asked to identify a contact person who could distribute the survey questionnaires to medical professionals who had experience in using the cloud-based LMS in their learning. A total of 600 questionnaires were distributed, and 378 (63.0%) usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that medical professionals’ perceived learner–content interaction quality, learner–system interaction quality, service quality, cloud storage service quality and learner–human interaction quality all positively caused their perceived usefulness, confirmation and CA elicited by the cloud-based e-learning system, which jointly explained their satisfaction with the system, and resulted in their continuance intention of the system.

Several limitations and suggestions may open avenues for future research. First, the limitation of self-reported measures should be considered; future research may combine with qualitative data (e.g. semi-structured, narrative, in-depth interviews, focus group interviews and open-ended questions) to get more complete interpretations of medical professionals’ cloud-based e-learning continuance intention. Next, this study’s data were collected from hospitals in Taiwan only; given this study’s limited scope, future research may generalize this study’s sample to the respondents of other national cultural backgrounds and make cross-country comparisons to enhance the completeness of this study. Finally, this study’ results were based on cross-sectional data; future research may use a longitudinal analysis by taking into account the evolution of medical professionals’ cloud-based e-learning continuance intention over time.

This study fully evaluates interaction-related and cloud-related quality determinants through an understanding of medical professionals’ state of CA in explaining their cloud-based e-learning system continuance intention that is difficult to expound with only their utilitarian perception of the system. Hence, the results contribute to deep insights into an all-round quality evaluation in the field of medical professionals’ cloud-based e-learning continuance intention, and extrinsic and intrinsic motivators are both taken into consideration in this study’s theoretical development of medical professionals’ cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

The purpose of this study is to propose the research model integrating the expectation-confirmation model with the views of learning engagement (LE) and extending DeLone and McLean information systems (IS) success model to examine whether quality determinants as antecedents to students' beliefs can influence students' continuance intention of massive open online courses (MOOCs).

Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed, and 363 (60.5%) useable questionnaires were analyzed using structural equation modeling in this study.

This study proved that students' perceived knowledge quality, system quality, interface design quality, learner–instructor interaction quality, and collaboration quality all positively caused students' perceived usefulness, confirmation and LE in MOOCs, which jointly explained students' satisfaction with MOOCs and subsequently resulted in students' continuance intention of MOOCs.

This study fully evaluates IS-related and interaction-related quality determinants via an understanding of students' state of LE in explaining students' continuance intention of MOOCs that is difficult to expound with only their utilitarian perception of MOOCs. Hence, this study contributes to deep insights into an all-round quality evaluation in the field of MOOCs continuance intention and takes extrinsic and intrinsic motivators into account in the theoretical development of MOOCs continuance intention to acquire a more comprehensive and robust analysis.

Explores the concept of quality from the perspective of the learner as part of the learning process. Focuses on the centrality of the learner in identifying and working towards building‐in quality to the education and training process. Proposes that, rather than the retrospective approaches to evaluating quality, approaches should be developed which follow the life cycle of the learner. Sees recent curriculum innovations, including the development of modular schemes and proposed funding arrangements in further education, as means of facilitating this approach.

The main purpose of this study is to examine whether quality factors as the antecedents to learner beliefs can affect learners' intention to use an e‐learning system.

This study gathered sample data from eight high‐tech companies in Taiwan. A total of 680 questionnaires were randomly distributed, 522 questionnaires were returned for a response rate of 76.76 percent, and 483 usable questionnaires were analyzed, with a usable response rate of 71.03 percent. Data were analyzed by using structural equation modeling.

Information quality, service quality, system quality, and instructor quality, as the antecedents of e‐learning acceptance can provide detailed accounts of the key forces underpinning employees' perception with regard to their beliefs (i.e. perceived usefulness, perceived ease of use, and perceived enjoyment), and this situation can further enhance employees' usage intention of the e‐learning system.

Based on the extended technology acceptance model and the updated DeLone and McLean information systems success model, this study integrates related e‐learning quality factors including information quality, service quality, and system quality into the research model and further contributes additionally to the identification of instructor quality that may lead to e‐learning acceptance. Also, it should be noted that the empirical evidence on capturing both extrinsic and intrinsic motivators for completely explaining quality antecedents of e‐learning acceptance is well documented in this study. Hence, this study contributes significantly to the body of research on evaluating the quality antecedents of e‐learning acceptance.

This chapter analyses the current situation and perceptions of quality assurance (QA) in adult education (AE) in Latvia. In the Latvian context, QA in AE is a challenge. According to recent studies, QA should have a formative character in order to facilitate targeted benefits for adult learners, whereas in practice AE in Latvia is more focussed on the institutional perspective rather than the individual’s needs and wishes. This is in contrast with the humanistic approach to adult learning and andragogy principles, which emphasise learner-centred education. The aim of the chapter is to research opportunities for improving the QA process in AE in Latvia in order to increase personal benefits for an individual. The systematic review of scholarly papers, monographs, scientific reports on QA in AE conducted in Latvia in the twenty-first century indicated a contradiction between the theoretical concepts applied to AE in Latvia and the implementation of the QA process in practice. This chapter contributes to the overall understanding of the terminology used in AE in the country, analyses the prevailing concepts and elaborates conclusions for QA improvements based on humanistic pedagogy principles.

The purpose of this paper is to investigate factors influencing English as foreign language (EFL) learners’ satisfaction using learning management systems (LMS) in blended learning.

This study conducted a survey method among 164 intermediate EFL learners of Safir Language Academy in Iran. Survey data were analyzed using the partial least squares (PLS) method, while Smart PLS was used to test the hypotheses and to validate the proposed model.

The results indicated that teaching presence, cognitive presence, information quality and system quality affect satisfaction of blended learning. However, there is not a significant relationship between social presence and learners’ satisfaction in blended learning using LMS.

This study proposes a comprehensive model which has been developed using the indicators of community of inquiry model, system quality and information quality to contribute to our understanding of key factors impacting EFL learners’ satisfaction.

The outcome will help academic institutions to provide effective English-medium instruction for the enhancement of EFL learners’ satisfaction and a basis for factors influencing EFL learners’ satisfaction in blended learning.

Our study aims to focus on the application of knowledge mapping to provide pedagogically-structured learners' competences.

We conducted an experiment examined the associations between the pedagogical quality of students’ pedagogically-informed knowledge (PIK) maps, class assignment scores and perceptions of PIK mapping’s uses.

The results showed that higher assignment scores were significantly predicted by higher quality PIK maps, ratings for PIK mapping were significantly higher than other mappings, and the learners’ experience of PIK mapping led to a significant change of attitude towards mapping as a learning activity and to a positive opinion of the value of PIK mapping in particular. Interestingly, there was no significant relation between learners’ opinion ratings of the uses of PIK mapping in learning and their assignment scores.

Questions remain on the generalizability of the findings, and on the features of a PIK map which are particularly useful to a learner. This study investigated the value of PIK mapping in the context of a practical class on the building of simple DIY (do-it-yourself) holographic projectors; it may be thought that the applied nature of the topic was more suited to the PIK mapping of learner competences and intended learning outcomes than a more theoretic classroom topic on holography. A future study is planned to address this issue.

This study aims to propose a conceptual structural equation model to investigate the relationships among e‐learning system quality, e‐learning readiness, e‐learners' competency as well as learning outcomes, and to demonstrate the direct and indirect effect of e‐learning system quality and e‐learning readiness on learning outcomes from the perspectives of e‐learners' competency.

A questionnaire was distributed to 379 full‐time employees from ten technological companies in Taiwan who have had e‐learning experience (n=379). Data were analyzed by employing structural equation modeling.

Results reveal that both e‐learning system quality and e‐learning readiness have a direct and significant impact on e‐learners' competency. However, e‐learning system quality and e‐learning readiness influence learning outcomes indirectly through e‐learners' competency. In addition, e‐learners' competency has direct and positive significant influence on learning outcomes.

Based on these findings, organizations in Taiwan that would like to implement e‐learning with their employees should focus on improving individuals' online learning skills such as self‐direction, meta‐cognitive, and collaborative skills.

The findings created an understanding of what attributes of external and internal factors influence the outcome of e‐learning in high tech companies. In terms of research contributions, the study extends previous researches by identifying the mediating effect of e‐learning competency on the relationship between e‐learning system quality, e‐learning readiness and learning outcome. Organizations that would like to adopt e‐learning to improve employees' knowledge and skills will be able to apply strategies based on the findings from the research.

The purpose of this study is to propose a sustainable quality assessment approach (model) for the e-learning systems keeping software perspective under consideration. E-learning is becoming mainstream due to its accessibility, state-of-the-art learning, training ease and cost effectiveness. However, the poor quality of e-learning systems is one of the major causes of several failures reported. Moreover, this arena lacks well-defined quality assessment measures. Hence, it is quite difficult to measure the overall quality of an e-learning system effectively.

A pragmatic mixed-model philosophy was adopted for this study. A systematic literature review was performed to identify existing e-learning quality models and frameworks. Semi-structured interviews were conducted with e-learning experts following empirical investigations to identify the crucial quality characteristics of e-learning systems. Various statistical tests like principal component analysis, logistic regression, chi-square and analysis of means were applied to analyze the empirical data. These led to an adequate set of quality indicators that can be used by higher education institutions to assure the quality of e-learning systems.

A sustainable quality assessment model for the information delivery in e-learning systems in software perspective has been proposed by exploring the state-of-the-art quality assessment/evaluation models and frameworks proposed for the e-learning systems. The proposed model can be used to assess and improve the process of information discovery and delivery of e-learning.

The results obtained led to conclude that very limited attention is given to the quality of e-learning tools despite the importance of quality and its effect on e-learning system adoption and promotion. Moreover, the identified models and frameworks do not adequately address quality of e-learning systems from a software perspective.