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.

Mobile learning applications have been growing in demand and popularity and have become a common phenomenon in modern educational systems, especially with the implementation of mobile learning projects. This study applies the Unified Theory of Acceptance and Use Technology (UTAUT) model to examine the effects of different factors that were identified from the literature on students' acceptance of mobile learning applications in higher education. The data was collected from a 697 university students responded to an online questionnaire. SEM method was used for data analysis. The results showed that perceived information quality, perceived compatibility, perceived trust, perceived awareness, and availability of resources, self-efficacy, and perceived security are the main motivators of students' acceptance of mobile learning system, and consequently success the implementation of mobile learning projects. Results from this study provide the necessary information as to how higher education institutions can enhance students' acceptance of mobile learning system in order to support the usage of mobile technologies in learning and teaching process. These results offer important implications for mobile learning acceptance and usage.

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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).

This study aimed to alleviate the gap between the literature regarding the Social Networking Applications (SNAs) use for active collaboration and engagement as sustainability in higher education and task-technology-fit (TTF) and compatibility on their consequence on students' satisfaction and their performance impact its sustainability used in higher education. Although researchers have examined (SNAs) usage within multiple situations, the roles of (TTF) and compatibility as mediating variables have not been investigated through TAM model and constructivism theory on measuring education sustainability. Overall 602 students and researchers took part in this study, which were selected from public university. Using the method of structural equation modeling (SEM), we surveyed to discover the perception of students toward the (SNAs). Based on the results, the (SNAs) use for collaboration and engagement as sustainability in higher education, and TTF and compatibility positively impacted the student's learning performance on measuring education sustainability, and they were found to be completely pleased with the perceived ease of use and perceived usefulness. In conclusion, the role of TTF and compatibility presents positive influences performances related to sustainability for education; and both factors mediates associations among collaboration and engagement as sustainability in higher education, students' satisfaction on (SNAs) usage and students' performance related to sustainability for education. Therefore, their impact should be encouraged in learning processes in higher education institutions.

The aim of this paper to develop a model to measure sustainability for education and incorporate the literature big data adoption and knowledge management sharing in the educational environment. This paper hypothesizes that perceived usefulness, perceived ease of use, perceived risk, and behavioral 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 influences behavior intention to use technologies and big data adoption would be positively associated with sustainability for education. This paper employed a 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's responses were sorted into the 11 study constructs and analyzed to explain their implication of sustainability on education. The data were then quantitatively analyzed using structural equation modeling (SEM). The results showed that perceived usefulness, perceived ease of use, perceived risk, and behavioral 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 paper are provided.INDEX TERMS Big data adoption, knowledge management sharing, motivators, technology acceptance model (TAM).

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.

This paper attempts to mitigate this gap within the literature concerning the use of social media for cyber engagement (CE) among students. Since students often become upset when network providers intervene, this paper aims to develop a model to measure ethics issues related to engagement with social media. The conducted survey examines social media use with regard to cyber engagement, cyberbullying behaviors, and being bullied, harassed, and stalked. To achieve the objective, this paper employed a questionnaire as the main data collection method and distributed it to 242 students, all of whom use social media. The findings were obtained via a quantitative research method, structural equation modeling, and partial least squares. The findings from our empirical study indicate that the assessment of discriminant validity has become an extensively acknowledged requirement for the analysis of latent variables' relationships. Goodness of fit indices demonstrates a good fit of the model. Roughly more than half of students indicated they had been bullied, harassed, and stalked online. The proposed model will help campus administration and decision makers to formulate strategies that can significantly reduce cyber harassment among students.INDEX TERMS Social media used, cyber harassment, cyberstalking, cyber bullying.