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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.

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).

This paper aims to present part of the work of an ongoing research project that is looking at socio‐ cultural and technological developments from a mobile technology convergence view; in order to show how culturally aware convergence developments in mobile technology can be adopted and employed for the betterment of society.

The paper presents a scenario for a mobile technology enabled learning environment in support of the conventional learning approach with a focus on enabling parental involvement and contribution to the daily learning objectives of their children and hence enhancing a quality learning experience. It further critically discusses issues of interface design – at both the device and application levels – that will have an impact on the quality of e‐learning, with a focus on mobile technology.

The paper shows how interface design can positively enhance the quality defining characteristics of learning in an e‐learning environment. Ways of achieving these characteristics of learning through effective e‐learning are reported. This is done by addressing requirements for quality‐learning through effective interface‐design considerations, towards meeting the overall quality requirements of learning that should be intrinsic to a holistic e‐learning environment. The value of human computer interaction and the critical factors of promoting productive interaction are addressed.

There are several factors affecting quality of e‐learning as a tool and approach to flexible and independent learning. The advent and use of mobile technology has been investigated in this work from a socio‐cultural and technological perspectives in two continents. The limitations lie in the depth of investigations and how far the findings can be applied to the diversity of learners.

As the effects of cultures and the rapid technological advancements take toll on teaching and learning the findings reported in this paper have far reaching implications for learners from different cultures and also for attempts at bridging existing digital divide.

The approach adopted in the research is unique by virtue of new findings and ideas presented. The paper highlights the opportunities for mobile devices and technology to play a role in the development of communities through technology aided learning (e‐learning), with a focus on e‐learning systems and technology requirements for delivering a quality learning experience.

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 study was based on situated learning, by combining mobile learning and augmented reality, so that students could not only access information content in a real environment but also obtain such information via augmented reality, to support mobile learning.

The research included development of an augmented reality system combined with situational learning, used by students to learn about campus plants as part of the college life technology curriculum. Students took part in mobile learning, and an investigation was conducted into the computer learning behaviour of notebook users. College students were used as the experimental subjects. Data were collected using questionnaire surveys and were evaluated in order to identify the behavioural intentions of learners in outdoor learning activities.

The questionnaire survey covered environmental interactivity, system quality and textbook content. It was found that learners who used mobile learning augmented reality (MLAR) generally managed to browse all the contents of the textbook at each learning location, without spending too much time looking for information, and learners could quickly integrate this into the learning situation. Learners who used MLAR had a strong motivation to study plants at the learning site because they wanted to use the augmented reality technology to observe virtual plant models. Learners who used MLAR in their field learning liked using augmented reality for further learning, for example, using a magic wand to interact with the technology.

This study adopted a new approach to deliver elements of the life technology curriculum, integrating augmented reality into mobile learning. All participating students gave positive reviews of six aspects of the proposed system: their behavioural intentions, cognitive usefulness, cognitive ease of use, environmental interactivity, system quality and textbook content.

The purpose of this paper is to propose a hybrid model based on the expectation-confirmation model (ECM), flow theory, and updated DeLone and McLean information system (IS) success model to examine whether quality factors as the antecedents to nurse beliefs affected nurses’ intention to continue using the blended electronic learning (e-learning) system.

Sample data for this study were collected from nurses at five hospitals in Taiwan. A total of 500 questionnaires were distributed, 396 (79.2 percent) questionnaires were returned. Consequently, 378 usable questionnaires were analyzed in this study, with a usable response rate of 75.6 percent. Collected data were analyzed using structural equation modeling.

Information quality, system quality, support service quality, and instructor quality contribute significantly to perceived usefulness (PU), confirmation, and flow, which together explain nurses’ satisfaction with the usage of the blended e-learning system, and this in turn leads to their continued system usage intention.

First, the application of the ECM with the view of updated DeLone and McLean IS success model reveals deep insights into quality evaluation (including information quality, system quality, and support service quality) in the field of nurses’ e-learning continuance intention. Especially, this study additionally contributes to the identification of instructor quality that may lead to nurses’ continued blended e-learning usage intention. Next, the empirical evidence on capturing both extrinsic motivator (i.e. PU) and intrinsic motivator (i.e. flow) for completely explaining quality antecedents of nurses’ blended e-learning continuance intention is well documented.

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.

Describes the holistic approach to learning and teaching interaction which has been taught on undergraduate and postgraduate degrees and doctoral programmes. The holistic approach develops students to be critical, confident and independent; aims to make learning a process of self‐improvement that explicitly recognizes the self and the social context of learning and teaching, and recognizing the needs of the individual learner in the interaction. Its premise is that the social context of the interaction is significant. It recognizes that the exchanges that take place within this social action are the foundation for developing critical learners, thus including experiential knowledge of learners and teachers to improve the quality of the teaching situation and levels of achievement of learners. Kelly’s Personal Construct Theory is invoked to explain how the holistic approach leads to the development of learners as critical thinkers. The result of practising the holistic approach has been sustained high levels of student attendance at lectures and seminars, improved progression, and appreciative and satisfied cohorts.

The majority of e‐learning empirical research studies have focused on the two research streams: outcome comparison studies with classroom‐based learning and studies examining potential predictors of e‐learning success. The determinants of e‐learning success include interactions, instructor support and mentoring, information delivery technology, course content, self‐motivation, learning styles, and course structure. Most of these empirical studies failed to include the technological dimension as an antecedent of effectiveness of e‐learning systems. The purpose of this paper is to empirically test the effects of e‐learning management systems (LMS), self‐efficacy and self‐regulated learning on learner satisfaction and system effectiveness.

This research model is an extension of the information systems success model of DeLone and McLean and the virtual learning environment effectiveness model of Piccoli et al. The research model was tested using the structural equation modelling‐based Partial Least Squares (PLS) methodology.

First, use of e‐LMS is not positively related to systems quality, information quality, self‐managed learning, and user satisfaction. Second, the findings strongly support the previous works of Rai, et al., Livari, and Freeze, et al. These three studies found strong positive relationships between information quality and user‐satisfaction and between systems quality and user‐satisfaction in a voluntary or mandatory use context. Third, perceived user satisfaction with e‐LMS is a very strong predictor of system effectiveness. This is in accordance with the findings and conclusions discussed in the literature on student satisfaction (Freeze et al., Eom et al., Rai et al., Livari). Of the four factors hypothesized to affect user satisfaction with e‐LMS, only two (systems quality and information quality) are supported at p<0.01.

This paper provides empirical evidence to support that e‐learner satisfaction is an important predictor of e‐LMS effectiveness and that systems quality and information quality have significant direct impacts on the perceived satisfaction of e‐learners with e‐LMS.

This study provides new empirical evidence that e‐learners' self‐regulated learning behavior may not lead to a higher level of e‐learners' satisfaction with e‐LMS, but it may lead to a higher level of satisfaction with web‐based courses.