Artificial intelligence applications (AIA) increase innovative interaction, allowing for a more interactive environment in governmental institutions. Artificial intelligence is user-friendly and embraces an effective number of features among the different services it offers. This study aims to investigate users’ experiences with AIA for governmental purposes in the Gulf area. The conceptual model comprises the adoption properties (namely trialability, observability, compatibility, and complexity), relative advantage, ease of doing business, and technology export. The novelty of the paper lies in its conceptual model that correlates with both personal characteristics and technology-based features. The results show that the variables of diffusion theory have a positive impact on the two variables of ease of doing business and technology export. The practical implications of the current study are significant. We urge the concerned authorities in the governmental sector to understand the significance of each factor and encourage them to make plans, according to the order of significance of the factors. The managerial implications provide insights into the implementation of AIA in governmental systems to enhance the development of the services they offer and to facilitate their use by all users.

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Despite numerous studies offering some evidence about the significance of quality measurements in enhancing the success of m-learning applications, there are still limited studies about the role of quality measurements in promoting the usability of mobile learning systems. Therefore, our study explores the role of quality measurements in promoting the usability of m-learning systems during COVID-19. The results revealed that the service quality, information quality and system quality are the most important factors affecting mobile learning usability among learners during COVID-19. Moreover, these findings are valuable for classifying the significance of these quality elements, which provide guidance on assigning quality aspects to improve this mobile learning usage during COVID-19 in higher education institutions.

Due to the COVID-19 pandemic, most universities around the world started to employ distance-learning tools. To cope with these emergency conditions, some universities in Jordan have developed “mobile learning platforms” as a new tool for distance teaching and learning for students. This experience in Jordan is still new and needs to be evaluated in order to identify its advantages and challenges. Therefore, this study aims to investigate students’ perceptions about mobile learning platforms as well as to identify the crucial factors that influence students’ use of mobile learning platforms. An online quantitative survey technique using Twitter was employed to collect the data. A two-staged ANN-SEM modelling technique was adopted to analyze the causal relationships among constructs in the research model. The results of the study indicate that content quality and service quality significantly influenced perceived usefulness of mobile learning platforms. In addition, perceived ease of use and perceived usefulness significantly influenced behavioral intention to use mobile learning platforms. The study findings provide useful suggestions for decision makers, service providers, developers, and designers in the ministry of education as to how to assess and enhance mobile learning platform quality and understanding of multidimensional factors for effectively using mobile learning platforms.

The growing use of the Internet of Things (IoT) around the world has encouraged researchers to investigate how and why the IoT is implemented in colleges and universities. Previous studies have focused on individual attitudes rather than the integration of attitudes from two different perspectives. Furthermore, other studies have investigated the use of the IoT in non-educational settings, ignoring the effect of the IoT related to the technology acceptance model (TAM) and technological pedagogical content knowledge (TPACK) model. The present work aims to address this research gap by determining the main factors that influence acceptance of the IoT, leading to increased awareness in collaborative learning, where technology forms the core tool in enhancing the use of the IoT. A questionnaire was used to collect data from teachers and students from colleges and universities in Oman and the United Arab Emirates (UAE). The data were analyzed through the structural equation modeling (SEM) method. The findings indicated that there are two levels of positive effects on the intention to use IoT. The first level is technology features, which are represented by technology optimism and technology innovation; these factors are crucial to using the IoT. The second level is learning motivation, which has a close relationship with teachers’ knowledge, and content pedagogy, which has a significant effect on the familiarity with IoT tools and applications. TAM constructs have a positive and direct impact on the intention to use IoT. The practical and managerial implications show that teachers, educators, and students can obtain benefits from these results to help IoT features to suit users’ needs.