Digital information has had a significant impact on higher education, transforming the way students learn and interact with course materials, professors, and their peers. Education systems that place a high priority on learning satisfaction and tutor quality frequently ignore the problem of limited access to digital information and technology. In this study, we provide an integrated model that examines how the TAM constructs of digital information in education (DIE) are affected by digital information flow, technological readiness, learning satisfaction, and tutor quality. We provide information on the results of a project evaluation that examined how digital information is used in higher education. We gathered information from a survey of 594 college students to validate our model and hypothesis. Our research suggests that external factors that improve users' technological readiness and learning satisfaction may have an impact on how valuable they perceive DIE to be. A user's traits, particularly their level of technological preparedness, have a significant impact on how simple technology is to use. The user's perceived usefulness of the technology may also be further enhanced in some cultures by the tutor’s perceived excellence. External elements like the flow of information may have a significant impact on the intention to use technology.

Artificial intelligence is user-friendly and possesses useful characteristics to share across the various services that are provided. By enhancing innovative contact, artificial intelligence applications (AIA) enable a more involved environment in governmental institutions. The goal of this study is to discover how users in the UAE feel about using AIA for educational reasons. Data collected from a survey of 387 university students were used to validate the model and hypotheses. The adoption features, such as perceived compatibility, trialability, relative advantage, ease of doing business, and technology export, are included in the conceptual model. The current study's practical implications are crucial in that they push the relevant educational authorities to comprehend the significance of each component and enable them to make plans and efforts in accordance with the order of the factors' relative importance. The managerial implications give educational sectors insight on how to apply AIA in their system to improve the growth of the provided service and to make the process easier for all users. The conceptual model of the paper, which links both traits of the individual and those of the technology, is what makes it new. The findings indicate that the diffusion theory variables outperform the other two variables of ease of doing business and technology export.

Recent studies on e-feedback have answered many questions concerning the effectiveness of e-feedback in educational and non-educational sectors. They stated clearly that e-feedback is efficient and practical. From both teachers’ and students’ perspectives, e-feedback has influenced their learning and teaching environment effectively. It is a good technique to personalize the learning strategies. Based on the previous assumption, this study aims at exploring the effectiveness of e-feedback in an educational environment taking into consideration the TAM model and the external factors of trustworthiness and enjoyment. The data is collected by an online questionnaire that was distributed among a group of students. Facilitating communication among teachers and students. It helps in replacing the traditional feedback and assess the learning environment during the pandemic periods. The two constructs of perceived ease of use and perceived usefulness affect positively the intention to use the e-feedback and initiates this type of feedback as a prominent procedure to be used frequently in the learning environment. In addition, the perceived enjoyment and perceived trustworthiness increase the chance of using e-feedback. Recently, e-feedback is highly dominant among online platform users.

This analysis integrates the “technology acceptance model (TAM)” with the “use of gratifications theory (U&G)” to develop an embedded model that predicts the use and satisfaction of emotional icons called stickers through WhatsApp. The explanation for combining these two theories is that U&G offers accurate information and a thorough knowledge of use, while TAM theory has been firmly established in several technical implementations. A newly developed hybrid analysis procedure has been applied within this research. Using an artificial neural network (ANN), and the structural equation model (SEM) have been combined. The research also uses the importance-performance map analysis (IPMA) to present each factor’s performance as well as importance. The ANN and IPMA research have both indicated that for sticker use intention, a highly essential predictor is Socialization. An online questionnaire survey was developed to assess the recommended model. The intention to use stickers was significantly affected by “Socialization, Self Presentation, Enjoyment, Novelty, Unique Function, Perceived Ease of Use, and Perceived Usefulness”. The research's main achievement is the convergence of two separate theories into a single conceptualization to accurately calculate the TAM components when it comes to the usage of stickers in WhatsApp. Theoretically, the recommended model provides enough insight for aspects which affect the intention to use stickers with relevance to the socialization’s factors considering interpersonal aspects. Practically, the higher education decision-makers along with professionals would extract variables that are important as compared to others and policies would be developed accordingly. The deep ANN model competence has been analyzed within the research to decide upon the non-linear associations between variables of the theoretical model, methodologically.

Recently audio and video material has been used significantly in various online platforms. The audio-video materials enhance the teaching and learning process by facilitating the transformation of the data and providing a richer interactive environment, hence gaining wide intention within the educational realm. However, empirical studies have not examined the acceptance of the audio and video material depending on a conceptual model where acceptance is the key factor. The present study attempts to overcome this gap in the literature review by investigating the effects of media richness, speed and vividness, perceived concentration, perceived ease of use, perceived usefulness on the acceptance of audio-video material. What distinguishes the current study is the fact that content richness is considered as a mediator that affects all other factors in the conceptual model. The data is collected by distributing the online survey to college students. The results provide mostly insight and support for students’ intention to use audio-visual resources in a conceptual model. The technology characteristics of speed and vividness as well as TAM constructs were significant predictors of technology acceptance. However, it is concluded that the external factor of the perceived concentration has no impact on the students’ perception and intention to use audio-visual resources. In the recommendation, some theoretical and practical implications are stated along with the focus on technology designers, change managers, and users.

YouTube and TikTok have gained increasing recognition as social network sites to support online knowledge acquisition, sharing, and application via social media platforms in the medical field. This study examines which aspect of TikTok and YouTube stimulates doctors, nurses, and any other YouTube and TikTok in the medical setting, to rely on them as sources of knowledge acquisition and sharing to keep their medical repertoire updated. A hybrid model is designed to investigate users’ acceptance of YouTube and TikTok as social media platforms. The model focuses on four main external factors: content richness, innovativeness, satisfaction, and enjoyment. These factors are connected with two TAM constructs which are perceived ease of use and perceived usefulness. The results have shown that both YouTube and TikTok are affected by PEOU, PU, personal innovativeness, flow theory, and content richness. Both social media networks provide up-to-date sources described as useful, enjoyable, and relevant. Nevertheless, the comparative results have shown that YouTube has deeply influenced users’ medical perception and knowledge compared to TikTok. It is created for the very mere purpose of socialization and self-expression. In contrast, YouTube is used for educational and non-educational purposes due to the type of uploaded content and time management. Therefore, TikTok developers and influencers should initiate highly specialized videos and create content that raises awareness of medical field issues.

This paper focuses on the impact of fear emotion upon technology adoption by educators and students during Covid-19 pandemic. Mobile learning (m-learning) has been applied as the educational social platform within higher education institutes, public as well as private. The research hypotheses were associated with the Covid-19 influence on m-learning adoption with the rise of the coronavirus increasing types of fear. Such fears include fear caused by the education failure, family lockdown, and loss of social relationships. Teachers and students are mostly fearful of these aspects of the situation. An integrated model was established within the research, using theoretical models; the Planned Behavior theory, the Technology Acceptance Model, and the Expectation-Confirmation Model. The proposed integrated model (using PLS-SEM software) was analyzed using an online survey data, with 420 respondents from Zayed University, UAE. The findings indicated that attitude was the best predictor for using the m-learning system, followed by continuous intention, expectation confirmation, perceived usefulness, ease-of-use, perceived fear, behavioral control, and satisfaction. According to the research, during the coronavirus pandemic, if the m-learning system is adopted for educational reasons, the learning and teaching outcome proves quite promising. Yet there is a fear of the family being stressed, or of loss of friends, and also a fear of the results of future schooling. It is therefore necessary to assess the students efficiently during this pandemic so that the situation can be managed emotionally.