The study’s main purpose was to discover the important factors that impact university students’ online learning and academic performance during the COVID-19 epidemic, as well as their usage of social media throughout the pandemic. Constructivism theory was used and developed with constructs mostly linked to leveraging social media for collaborative learning and student interaction during the COVID-19 pandemic, given the context-dependent nature of online learning during the epidemic. During the COVID-19 epidemic, additional components such as collaborative learning, student participation, and online learning were implemented. The enlarged model, which assesses students’ happiness and academic performance during the COVID-19 epidemic in connection to social media use, was validated using empirical data collected via an online survey questionnaire from 480 Saudi Arabian higher education students. AMOS-SEM was used to analyze the model’s various assumptions (Analysis of Moment Structures-Structural Equation Modeling). The findings revealed that (1) using social media for collaborative learning and students’ engagement has a direct positive impact on students’ interactivity with peers and teachers; (2) students’ interactivity with peers and teachers has a direct positive impact on online learning during the COVID-19 pandemic; (3) online learning during the COVID-19 pandemic mediates the relationship between students’ interactivity and satisfaction; (4) online learning during the COVID-19 pandemic mediates the relationship between students’ interactivity and satisfaction. Students, higher education institutions, and educational technology application suppliers would benefit greatly from the conclusions of this study, both theoretically and practically.

The study’s major goal was to figure out what factors impact university students’ behavior and intentions to use social media to boost their academic performance during the COVID-19 Pandemic. Given the context-dependent nature of online learning, the Technology Acceptance Model (TAM) was adopted and supplemented with components largely relevant to harnessing social media for collaborative learning and engagement. Collaborative learning, student participation, and a social media mindset are just a few of the new features. The enlarged model was validated using empirical data from an online survey questionnaire filled by a sample of 409 Saudi Arabia higher education students, which assesses students’ social media usage intentions and academic performance during the COVID-19 Pandemic. AMOS-SEM was used to analyze the model’s various assumptions (Analysis of Moment Structures- Structural Equation Modeling). The findings revealed that: (1) utilizing social media for collaborative learning and student engagement has a direct positive impact on perceived usefulness, ease of use, and enjoyment; (2) perceived usefulness, ease of use, and enjoyment has a direct positive impact on attitude to use social media; and (3) the link between TAM characteristics “usefulness, ease of use, and pleasure” and behavior intention to use social media is mediated by attitude to use social media. (4) Students’ attitudes and behavior intentions on social media have a direct positive influence on their academic performance during the COVID-19 Pandemic. Academics, higher education institutions, and educational technology application providers will benefit greatly from the conclusions of this study, both theoretically and practically.

The current study highlights the potential of multimodal large language models (MLLMs) to transform higher education by identifying key factors influencing their acceptance and effectiveness. Aligning technology features with educational needs can enhance student engagement and learning outcomes. The study examined the role of MLLMs in enhancing performance benefits among higher education students, using the task–technology fit (T-TF) theory and the artificial intelligence device use acceptance (AIDUA) model. A structured questionnaire was used to assess the perceptions of 550 Saudi university students from various academic disciplines. The data were analyzed via structural equation modeling (SEM) using SmartPLS 3.0. The findings revealed that social influence negatively affected effort expectancy regarding MLLMs and that hedonic motivation was also negatively related to effort expectancy. The findings revealed that social influence and hedonic motivation negatively affected effort expectancy for MLLMs. Effort expectancy was also negatively associated with T-TF in the learning context. In contrast, task and technology characteristics significantly influenced T-TF, which positively impacted both performance benefits and the willingness to accept the use of MLLMs. A strong relationship was found between adoption willingness and improved performance benefits. The findings empower educators to strategically enhance MLLMs adoption strategically, driving transformative learning outcomes.

Students, colleagues, and other members of society are increasingly using digital media. Students utilize digital media for a variety of reasons, including communication, gaming, making new friends, and simply being curious. However, there are some disadvantages to using digital media. Cyberbullying, cyberharassment, and cyberstalking are examples of useful digital media activities that can have a negative impact on digital media users and lead to societal issues. Surprisingly, limited studies have investigated cyberbullying in depth, utilizing a broad and varied sample of Middle Eastern institutions. As a result, the purpose of this study is to fill a research vacuum by questioning students’ use of digital media for cyber involvement. This research aims to create a model for assessing the ethical consequences of behaviors that directly impact students’ psychological health because of their use of digital media. The questionnaire looked at how people used digital media to engage in cyberbullying and cyber engagement, the ethical implications of bullying, and being harassed, stalked, and bullied. The study employed a quantitative questionnaire to collect data to achieve the research goal. It was given to 1012 students who are digital media users. Partial least squares (PLS) and structural equation modeling (SEM) were used to examine the data. Considering the empirical data, nearly half of the participants admitted to being harassed, stalked, or bullied on different digital platforms. The evaluation of discriminant validity is a prerequisite factor for examining possible variables’ relationships. The goodness-of-fit index indicates that the model is well-fit. Through the established model, decision-makers and school administration would be able to implement measures that would effectively reduce cyber harassment among students and improve the digital media usage experience.

The purpose of this study was to investigate the factors that influence the use of e-learning among students in higher education during the Corona Virus disease, during the 2019 season (COVID-19). A poll of 395 students from the student’s university was used to conduct the research. The study’s theoretical foundation was an expanded Technology Acceptance Model (TAM), which included task-technology fit and students’ engagement, as well as external elements such as experience (EXP), technology anxiety (TEA), and facilitating conditions (FC). The suggested model was tested and evaluated using SEM-PLS. The investigation demonstrated that the suggested TAM-based scale effectively describes factors impacting students’ use of E-learning during the pandemic. According to the findings, students’ engagement (SEN), EXP, TEA, and FC have a favorable impact on task–technology fit (TTF) and perceived ease of use (PEOU), resulting in a good impact on TTF and usage of an e-learning system for educational sustainability (EA). Finally, the TTF fit and convenience of use of eLearning in education have a positive impact on the behavioral intention to use an e-learning system for educational sustainability and the adoption process. As a result, higher education institutions should use eLearning as a sustainability learning strategy.

Teachers' professional development plays a significant role in the sustainability of quality education. However, providing sustainable professional development programs is difficult because of various challenges, such as insufficient government policies, a scarcity of qualified personnel and training opportunities, lack of access and resources, etc. The COVID-19 epidemic has further intensified the problem and adversely harmed schoolteachers’ interest, motivation, and involvement. In such situations, technology can play a positive role in carrying out sustainable educational activities. However, little focus has been paid to the use of technology for the sustainable professional development of teachers, particularly in the under developing countries. Due to its unique qualities, mobile learning is receiving much attention as an essential component to impart sustainable education to teaching professionals. It represents a paradigm shift in ongoing professional development, particularly for teachers who are constrained by time, resources, and travel requirements. Mobile learning is an alternate and complementary technique to enhance teachers' professional development, allowing them to work, learn, and attain their full potential. To meet the sustainable development goal of teachers’ education, in [1] we have provided a framework for teachers' continuous professional development (CPD). Based on that, we have also developed a mobile App to provide training and ongoing support to teachers’ professionals. This study evaluates the usability of our mobile App for the sustainable development of teachers. Usability characteristics of usefulness, efficiency, and satisfaction are measured using a usability testing approach. 107 elementary school instructors took part in the study. Participants in the study performed eight usability tasks in the same room using the researcher's internet bandwidth. The participants' time and completion rate were recorded. A post-test questionnaire followed usability tasks. After the usability activities, participants completed a System Usability Scale questionnaire to assess overall satisfaction with the training app and gain a broad picture of the program. The application achieved a 100% completion rate for all tasks, indicating an extremely effective, efficient, and sustainable system. Moreover, the satisfaction percentage was also found to be 84.1 percent, which is considered highly satisfactory.