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 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.

Teaching and learning are significantly influenced by information and communications technology (ICT). The goal of this study was to develop a new model and conduct confirmatory factor analysis to learn more about how students use ICT for digital learning as sustainability. The purpose of this research project was to investigate computer self-efficacy, computer anxiety, perceived enjoyment and acceptance of digital learning as sustainability at Saudi universities, based on students’ satisfaction with actual ICT usage for digital learning as sustainability. This research project made use of structural equation modelling with SEM-AMOS and an expanded variant of the technology acceptance model as the research model. A questionnaire based on the technology acceptance model and social cognitive theory was employed as the main data collection method and was distributed to 684 students from students at two universities. Students’ answers were categorized into seven categories and evaluated to determine how satisfied students were with ICT and how likely they were to continue using it for digital learning as sustainability. The findings revealed a connection between computer self-efficacy, computer anxiety and perceived enjoyment, factors which all played a significant role in perceived usefulness and ease of use. Perceived usefulness and ease of use also had an impact on students’ continued intention to use and satisfaction. This research-built model was effective in explaining students’ continued desire to use ICT and their satisfaction with it.

Nowadays, social media applications (SMAs) which are quite popular among students have a significant influence on education sustainability. However, there is a lack of research that explores elements of the constructivist learning approach with the technology acceptance model (TAM) in higher education. Therefore, this research aimed to minimize the literature gap by examining the SMA factors used for active collaborative learning (ACL) and engagement (EN) to affect the students’ academic performance in measuring education sustainability, as well as examining their satisfaction from its use. This study employed constructivism theory and TAM as the investigation model, and applied a quantitative method and analysis through surveying 192 university students at King Faisal University. Using structural equation modeling (SEM), the responses were sorted into nine factors and analyzed to explain students’ academic performance in measuring education sustainability, as well as their satisfaction. The results were analyzed with structural equation modelling; it was shown that all the hypotheses were supported and positively related to sustainability for education, confirming significant relationships between the use of SMAs and the rest of the variables considered in our model (interactivity with peers (IN-P), interactivity with lecturers (IN-L), ACL, EN, perceived ease of use (PEOU), perceived usefulness (PU), SMA use, student satisfaction (SS), and students’ academic performance (SAP).

Education and learning have been significantly impacted by ICT. The purpose of this project is to create a new model and conduct confirmatory factor analysis in order to better understand how students utilize ICT in the classroom. An additional aim is to study, based on students’ attitudes and aspirations to utilize ICT for digital learning, their fundamental computer abilities, media-related skills, WBS, and adoption of digital learning technologies, by surveying students at Bisha University and King Faisal University. Structural equations modeling (SEM)-AMOS was used to survey 711 university students, and this study used an improved version of the Technology Acceptance Paradigm (TAM) approach as its research paradigm, as well as quantitative data collection and analytic methodologies. Students’ comments were divided into seven categories and analyzed to identify their attitudes toward and intentions for using ICT in learning environments. BCS, media-related abilities, and WBS all had a substantial influence on perceived usefulness and perceived ease of use, according to the research. This model, which was based on research, was successful in describing students’ attitudes and intentions about using ICT for digital learning.

The aim of this research to develop a model to measure sustainability for education, and incorporating the literature Big Data adoption and knowledge management sharing in the educational environment. This research hypothesize that perceived usefulness, perceived ease of use, perceived risk and behavioural intention to use big data should influence adoption of big data, while age diversity, cultural diversity and motivators should impact knowledge management sharing. Therefore, knowledge management sharing influence behavior intention to use technologies and big data adoption would be positively associated with sustainability for education. This study employed version of TAM and motivation theory as the research framework, and adopted quantitative data collection and analysis methods by surveying 214 university students who were chosen through stratified random sampling. Student responses were sorted into the eleven study constructs and analysed to explain their implication of sustainability on education. The data were then quantitatively analyzed using Structure Equation Modelling (SEM). The results showed that perceived usefulness, perceived ease of use, perceived risk and behavioural intention to use big data were significant determinants of big data adoption, while age diversity, cultural diversity and motivators were significant determinants of knowledge management sharing. The knowledge management sharing, behavior intention to use technologies and big data adoption succeeded in explaining 66.7% of sustainability on education. The findings and implications of this study are provided.