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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.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether media richness and social interaction as environmental feature antecedents to nurses’ learning engagement (LE) can affect their continuance intention of massive open online courses (MOOCs) and task performance.

Sample data for this study were collected from nurses at five university-/medical university-affiliated hospitals in Taiwan. A total of 500 questionnaires were distributed, and 303 (60.6%) usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that nurses’ perceived media richness and social interaction in MOOCs positively influenced their behavioral LE and psychological LE elicited by MOOCs, which jointly caused their continuance intention of MOOCs and, in turn, enhance their task performance. The results support all proposed hypotheses and the research model, respectively, explains 84.3% and 63.7% of the variance in nurses’ continuance intention of MOOCs and task performance.

This study uses the S-O-R model as a theoretical base to frame nurses’ continuance intention of MOOCs and task performance as a series of the internal process, which is affected by environmental stimuli (i.e. media richness and social interaction) and organismic states. Noteworthily, while the S-O-R model has been extensively used in prior literature, little research uses this paradigm to expound nurses’ continuance intention of MOOCs in the work settings. Besides, there is a dearth of evidence on the antecedents of nurses’ task performance in the context of MOOCs. Hence, this study’s empirical evidence contributes significantly to the existing literature on bridging the gap of limited evaluation for the research on the impact of nurses’ MOOCs learning on their task performance in the work settings, which is very scarce in the S-O-R view.

The purpose of this study is to propose a research model based on the stimulus–organism–response (S–O–R) model to examine whether network externality, personalization and sociability as environmental feature antecedents to learners’ learning engagement (LE) can influence their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from learners who had experience in taking MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 371 usable questionnaires were analyzed using structural equation modeling in this study.

This study proved that learners’ perceived network externality, personalization and sociability in MOOCs positively affected their cognitive LE, psychological LE and social LE elicited by MOOCs, which jointly led to their LP in MOOCs. The results support all proposed hypotheses, and the research model accounts for 76.2% of the variance in learners’ LP in MOOCs.

This study uses the S–O–R model as a theoretical base to construct learners’ LP in MOOCs as a series of the inner process, which is affected by network externality, personalization and sociability. It is worth noting that three psychological constructs including cognitive LE, psychological LE and social LE are used to represent learners’ organismic states of MOOCs usage. To date, hedonic/utilitarian concepts are more often adopted as organisms in previous studies using the S–O–R model, and psychological constructs have received lesser attention. Hence, this study’ contribution on the application of capturing psychological constructs for completely expounding three types of environmental features as antecedents to learners’ LP in MOOCs is well documented.

Since there is lack of studies in determine factors that affecting enjoyment sentiment when using online learning system, this study aims to explore the antecedents of perceived online learning enjoyment by using extended technology acceptance model (TAM) and its effect on behavioral intentions (BIN) among higher education institutions students.

The research framework was empirically evaluated using a cross-sectional research design and the data was collected from 715 undergraduate students from public higher education institutions in Malaysia using an online survey method. A structural equation modeling using partial least square method was used to examine the hypothesized model.

The results of partial least squares structural equation modeling indicated that the main predictive variables of TAM along with the extended variables were significantly influence the perceived online learning enjoyment. Meanwhile, the analysis also identified that perceived online learning enjoyment can significantly generate positive BIN for using online learning platforms as well as it also plays as a significant mediator role.

This study has significant implications for higher education institutions that wish to develop online learning environment for their students by providing answers to higher education institutions on how to successfully use the learning management system to assist students' learning performance from the aspect of online learning enjoyment sentiment.

This study is remarkable because it is the first attempt to explore the effect of these five predictors on students' learning enjoyment toward online learning platforms and subsequently on BIN to use this learning platforms, especially in the context of Malaysian higher education system. It is also unique in the way to extend the use of TAM predictive variables with others variables to produce more informative results about the study. Hence, this study also has a new contribution in the literature in the domain of digital learning.

This systematic review aims to assess the studies collected by identifying factors influencing the acceptance of e-learning systems before and during the current propagation of the COVID-19 pandemic.

This study undertook a literature review on the in-depth revision of studies published before 2021. The reviewed research papers meet the inclusion and exclusion criteria. A total of 97 out of 214 articles met the inclusion criteria and were subsequently used in this review.

The findings revealed that the survey questionnaire is the most common data collection instrument used regardless of the research objectives. 2019 was a remarkable year because of the emergence of the COVID-19 pandemic.

This systematic review relied on specific databases (ScienceDirect, Emerald, IEEE and Google Scholar) to search for the articles included in this paper. However, these databases may not comprehensively represent all papers published on e-learning using the technology acceptance model (TAM).

This paper suggests a guide for managers and scholars in educational institutions and acts as a roadmap for practitioners and academics in the educational field and policymakers. This research spotlights the significant factors influencing the acceptance and adoption of e-learning.

This research assessed articles that examined the TAM in e-learning and classified them according to their methodology, country of dissemination, context and distribution within the year of publication. This paper contributes to the body of knowledge in a way that will benefit stakeholders in an educational setting.

This study aims to investigate the factors that influence the continuance intention to use personal cloud storage services among Generation Y.

A quantitative online survey was carried out to collect data from 271 respondents. Structural equation modelling with SmartPLS 4.0 software was used to run the analysis and examine the hypothesized relationships in the research model.

The study revealed that both satisfaction and habit exert a significant influence on continuance intention, whereas self-efficacy does not demonstrate a significant effect. In addition, satisfaction was found to be influenced by confirmation, perceived usefulness and perceived security. Furthermore, confirmation and cloud storage service quality were found to impact perceived usefulness, while confirmation also had an effect on perceived security. However, the hypothesized moderating role of perceived privacy risk in the relationship between perceived usefulness, perceived security and satisfaction was not supported.

This study advances the field by adapting an expanded expectation-confirmation model that delineates the nuanced impacts of habit, user satisfaction and self-efficacy on Generation Y’s continuance intention to use personal cloud storage services. It challenges the conventional wisdom regarding self-efficacy’s influence on technology adoption, offering a more intricate portrayal of its role. This research contributes a distinctive theoretical perspective, emphasizing the complex interplay of factors that inform sustained user engagement with cloud technologies.

This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption process within educational institutions. Technology integration in education has rapidly gained prominence, with EdTech offering innovative solutions to enhance teaching and learning experiences. However, understanding the determinants that affect EdTech adoption remains critical for its successful implementation and impact. This paper aims (1) to identify the factors influencing the adoption of EdTech by college students (2) to create a conceptual model that shows the connections between the elements that lead to college students adopting EdTech.

The research employed a mixed-methods approach, combining qualitative data analysis and conceptual modeling to achieve the objectives. The underlying knowledge required to create a qualitative data gathering tool was obtained through a thorough literature analysis on innovation dissemination, educational psychology and technology adoption. College students, teachers and administrators participated in semi-structured interviews, focus groups and surveys to provide detailed perspectives on their attitudes about and experiences with EdTech. The Scopus and Web of Science databases are searched for relevant information in an organized manner in order to determine the factors influencing the adoption of EdTech. Second, an extended version of the technology adoption model is adopted to develop a qualitative data-based conceptual framework to analyze EdTech adoption in the Indian context.

Overall, by highlighting the critical components that emotionally influence college students' adoption of EdTech products in educational institutions, this course adds to the body of information already in existence. The conceptual framework model serves as a roadmap for educational stakeholders seeking to leverage EdTech effectively to enrich the learning environment and improve educational outcomes. By recognizing the significance of the identified factors, academic institutions can make informed decisions to foster a climate conducive to successful EdTech integration.

A comprehensive conceptual framework model was developed based on qualitative data analysis to illustrate the interrelationships between the identified factors influencing EdTech adoption. This model presents a valuable tool for educational institutions, policymakers and EdTech developers to comprehend the complex dynamics of implementing these technological solutions.

The findings of this study demonstrated a number of important variables that affect the uptake of EdTech products in educational settings. These factors encompassed technological infrastructure, ease of use, perceived usefulness, compatibility with existing academic practices, institutional support, financial constraints and individual attitudes towards technology. Additionally, the research explored the significance of institutional preparation for embracing technological advancements as well as the influence of socio-cultural elements.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

This study conducts a systematic literature review to examine the interrelationships between e-learning critical success factors, instructors' perceptions of these factors, and the corresponding institutional actions taken by higher education institutions to achieve success in e-learning implementation, by fostering instructors’ acceptance of e-learning as a viable mode of delivery in higher education.

The research design employed in this study involves a systematic literature review of 43 peer-reviewed articles from EBSCO host and Scopus databases. The selected methodology employed thematic analysis of the gathered data by utilizing a multistep qualitative coding method of analysis.

The systematic literature review delivers three key findings. First, there is a notable divergence between instructors' perceptions of critical success factors for e-learning in higher education and the perspectives of other stakeholders, such as students, e-learning experts, and institutional management. Second, it emphasizes the importance for higher education institutions to understand and address instructors' perceptions to facilitate effective e-learning implementation. Third, the literature suggests potential causal relationships between institutional actions addressing the success factors deemed important by instructors and instructors' sustained acceptance of e-learning as a viable delivery mode.

The present study enriches knowledge of instructor perceptions of critical success factors for effectiveness in higher education by extending research in institutional management actions to enable their achievement. This study has implications for research strands on how instructors’ motivation and propensity for e-learning acceptance can be influenced by institutional management and how to reduce the level of resistance to adopting e-learning courses by addressing e-learning’s critical success factors as perceived by instructors.

Based on the theoretical insights derived from the systematic literature review, a conceptual framework is constructed, integrating the three concepts under investigation: success factors, institutional actions, and instructors' acceptance of e-learning in higher education. This framework provides a basis for future research seeking to validate the potential causal relationships among these concepts. Moreover, the study contributes to existing literature by addressing and consolidating research strands related to critical success factors and instructors' perceptions of e-learning effectiveness in higher education.

The purpose of this study is to examine the acceptance factors of e-learning among students in high schools. In this study, researchers used a combination of system acceptance models, namely UTAUT2 and TOE. The UTAUT2 framework is used to explore technology acceptance from the context of individual behavior, while TOE is used to understand technology acceptance from the organizational context based on the perspective of students, as it results in a better choice to anticipate the relationship between the acceptance of technological innovation in high schools.

This study used quantitative methods. The sample in this study amounted to 212 people who were high school students who had just tried using SIDEK-Edu. This study uses Partial Least Square-Structural Equation Modeling (PLS-SEM) to analyze the measurement model and structural model with WarpPLS version 6 software.

Based on the results of the tests carried out, out of a total of 16 hypotheses, 6 hypotheses were accepted and 10 hypotheses were rejected. Research findings from the individual context show that performance expectancy, social influence, and learning value have a positive and significant effect on behavioral intention to use SIDEK-Edu innovation technology. Furthermore, judging from students' perceptions in the organizational context, only relative advantage has a positive and significant effect on behavioral intention, while compatibility, ICT resources, and competitive pressure do not.

The limitations of this research are that this research uses a homogeneous sample of high school students, this research only focuses on the high school level, this research is limited to the dominant variables in measuring the acceptance of SIDEK-Edu innovation technology.

Input to the high school, both the organization, teachers, and also decision makers in the organization. This makes it easier for all parties to design and implement the system they have so that it is as expected, In addition, the existence of SIDEK-Edu also provides a new learning method experience in learning accounting which is very beneficial for high school students, especially vocational high school.

SIDEK-Edu is a new innovative technology to research and is an LMS that focuses on accounting learning (theory room and practice room in one learning media). In addition, the model used in the study is a combination of models (UTAUT2-TOE) to indentify e-learning acceptance.