This paper aims to explore and investigate the potential factors influencing students' behavioral intentions to use the e-learning system. This paper proposes an extended technology acceptance model (TAM) that has been tested and examined through the use of both innovation diffusion theory (IDT) and integrating TAM. This paper was conducted on 1286 students utilizing systems of e-learning in Malaysia. The findings were obtained via a quantitative research method. The findings illustrate that six perceptions of innovation characteristics, in particular, have impacts on students' e-learning system behavioral intention. The influences of the relative advantages, observability, trialability, perceived compatibility, complexity, and perceived enjoyment on the perceived ease of use is noteworthy. Moreover, the effects of the relative advantages, complexity, trialability, observability, perceived compatibility, and perceived enjoyment on the perceived usefulness have a strong impact. Therefore, the empirical results provide strong backing to the integrative approach between TAM and IDT. The findings suggest an extended model of TAM with IDT for the acceptance of the e-learning system used to improve the students' learning performance, which can help decision makers in higher education, universities, as well as colleges to evaluate, plan and execute the use of e-learning systems.

This mixed-method study explores the acceptance of ChatGPT as a tool for Metacognitive Self-Regulated Learning (MSRL) among academics. Despite the growing attention towards ChatGPT as a metacognitive learning tool, there is a need for a comprehensive understanding of the factors influencing its acceptance in academic settings. Engaging 300 preservice teachers through a ChatGPT-based scenario learning activity and utilizing convenience sampling, this study administered a questionnaire based on the proposed Technology Acceptance Model at UTM University's School of Education. Structural equation modelling was applied to analyze participants' perspectives on ChatGPT, considering factors like MSRL's impact on usage intention. Post-reflection sessions, semi-structured interviews, and record analysis were conducted to gather results. Findings indicate a high acceptance of ChatGPT, significantly influenced by personal competency, social influence, perceived AI usefulness, enjoyment, trust, AI intelligence, positive attitude, and metacognitive self-regulated learning. Interviews and record analysis suggest that academics view ChatGPT positively as an educational tool, seeing it as a solution to challenges in teaching and learning processes. The study highlights ChatGPT's potential to enhance MSRL and holds implications for teacher education and AI integration in educational settings.

Technology in education can influence students to learn actively and can motivate them, leading to an effective process of learning. Previous research has identified the problem that technology will create a passive learning process if the technology used does not promote critical thinking, meaning-making or metacognition. Since its introduction, augmented reality (AR) has been shown to have good potential in making the learning process more active, effective and meaningful. This is because its advanced technology enables users to interact with virtual and real-time applications and brings the natural experiences to the user. In addition, the merging of AR with education has recently attracted research attention because of its ability to allow students to be immersed in realistic experiences. Therefore, this concept paper reviews the research that has been conducted on AR. The review describes the application of AR in a number of fields of learning including Medicine, Chemistry, Mathematics, Physics, Geography, Biology, Astronomy and History. This paper also discusses the advantages of AR compared to traditional technology (such as e-learning and courseware) and traditional teaching methods (chalk and talk and traditional books). The review of the results of the research shows that, overall, AR technologies have a positive potential and advantages that can be adapted in education. The review also indicates the limitations of AR which could be addressed in future research.

This research intends to investigate factors affecting students’ behavioural intentions to use a massive open online courses (MOOCs) system. Integrating the technology acceptance model (TAM) with the innovation diffusion theory (IDT), the present research proposes an extended technology acceptance model. Testing of data collected from 1148 students using (MOOCs) system in Malaysia achieved the research objective. The findings obtained via a quantitative research method, based on analysing the results using a Structure Equation Modeling (SEM). The outcomes reveal that six views of novelty features swayed students’ a (MOOCs) scheme behavioural objective. The properties of the relative advantages, intricacy, trialability, observability, compatibility, and perceived enjoyment on the perceived ease of use are significant. Also, the effects of the relative advantages, complexity, trialability, observability, compatibility, and perceived enjoyment on the usefulness have a substantial impact. Therefore, the practical outcomes offer robust backing for the integrative method between TAM and IDT. The results recommend a prolonged model of TAM with IDT for the taking of MOOCs) system used to improve students learning performance, which can help decision makers in higher education, universities and colleges to planning, evaluating and executing the use of (MOOCs) systems.

Today, developments in information and communication technology (ICT) have a significant influence on education sustainability. In this study, the factors influencing students’ intentions towards using ICT in education sustainability, as well as their satisfaction from its use, were examined. This study aims to investigate student intentions to use information and communication technology, as well as their satisfaction with such use. Therefore, this study employed an extended model of the Technology Acceptance Model (TAM) as the research framework, and adopted quantitative data collection and analysis methods by surveying 502 university students who were chosen through stratified random sampling. Using structural equation modeling (SEM), student responses were sorted into eight study constructs and analyzed to explain their intentions towards technology use and satisfaction. A significant relationship was found between computer self-efficacy (CSE), subjective norms (SN), and perceived enjoyment (PE), which were significant determinants of perceived ease of use (PEU) and perceived usefulness (PU). PEU, PU, and attitudes towards computer use (ACU) influenced students’ intentions to use (SIU) ICT and students’ satisfaction (SS). The constructs succeeded in explaining usage intentions towards ICT among students and their satisfaction from this usage.

The rapid advancement of artificial intelligence (AI) technologies has led to a transformation in higher education worldwide. AI tools provide academic support to students anywhere and anytime to enhance their knowledge and skills. Those facing difficulties have been relying on traditional support and guidance. However, this support has experienced difficulties, including availability and accessibility. This study examines the potential of AI-powered tools to address these challenges, aiming to make academic support more accessible, efficient, and effective. This study focuses on understanding the determinants of AI tools' acceptance and use for academic support among students, influencing student satisfaction and academic performance in Pakistan and Malaysia. The research on AI tool acceptance and use in the higher education Institutions (HEI) context is still new and less explored in Pakistani and Malaysian higher education institutions. A theoretical model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and other factors was employed to identify factors that affect AI tool adoption in higher education. The survey research design was employed, and the total sample size was 305 respondents, with 203 students from Quaid-e-Awam University of Science and Technology (QUEST), Pakistan, and 102 students from Universiti Teknologi Malaysia (UTM). A “Partial least squares structural equation modeling (PLS-SEM) Analysis” was employed to assess the research model and hypotheses using SmartPls 4.0. In Pakistan and Malaysia, students are more concerned about using AI tools to improve their academic performance. The findings indicated that performance and effort expectancy, information accuracy of AI tools, pedagogical fit to meet the student’s expectations, and student interaction with tools were important factors in predicting the acceptance and use of AI tools among students of both countries in higher education, and the rising use of these AI tools has improved students’ satisfaction levels and significantly impacted students learning outcomes in both countries. Additionally, student engagement and personal innovativeness have not significantly affected the use of AI tools among students in both countries. This study provides a comprehensive analysis of AI tool adoption in the unique contexts of Pakistan and Malaysia, contributing to the broader discourse on technology integration in higher education.