Flipped learning has garnered substantial attention as a potential means to enhance student engagement, improve learning outcomes, and adapt to the evolving educational landscape. However, despite the growing interest and potential benefits of flipped learning, several challenges and areas of concern persist. This systematic literature review critically examines the implementation of the flipped classroom in higher education by focusing on the role of technologies and tools, pedagogical activities and courses, and existing challenges. Using a systematic approach, a total of 30 research articles published between 2014 and 2023 were chosen for the review. This study identified video creation tools, learning management systems (LMS), content repositories, collaborative platforms, podcasts, and online assessment tools as technologies that play a central role in the flipped classroom. Moreover, this study identifies specific pedagogical activities within different courses that contribute to the effectiveness of flipped learning in higher education. The implementation challenges that teachers and students may face in the flipped classroom were presented, and potential strategies to alleviate these challenges were provided. This study will contribute to a more comprehensive understanding of flipped learning's benefits, technologies and tools, challenges, and potential to improve higher education.

Generative Artificial Intelligence (GenAI) tools hold significant promises for enhancing teaching and learning outcomes in higher education. However, continues usage behavior and satisfaction of educators with GenAI systems are still less explored. Therefore, this study aims to identify factors influencing academic staff satisfaction and continuous GenAI usage in higher education, employing a survey method and analyzing data using Partial Least Squares Structural Equation Modeling (PLS-SEM). This research utilized the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Expectation Confirmation Model (ECM) as its theoretical foundations, while also integrating ethical concerns as a significant factor. Data was collected from a sample of 127 university academic staff through an online survey questionnaire. The study found a positive correlation between effort expectancy, ethical consideration, expectation confirmation, and academic staff satisfaction. However, performance expectancy did not show a positive correlation with satisfaction. Performance expectancy was positively related to the intention to use GenAI tools, while academic staff satisfaction positively influenced the intention to use GenAI. The social influence did not correlate positively with the use of GenAI. Security and privacy were positively associated with staff satisfaction. Facilitation conditions also positively influenced the intention to use GenAI. The findings of this study provide valuable insights for academia and policymakers, guiding the responsible integration of GenAI tools in education while emphasizing factors for policy considerations and developers of GenAI tools.

Mobile learning (m-learning) is increasingly becoming a popular global trend, especially among English language learners. However, despite the growing interest in mobile English language learning, there have been no reviews of research conducted on this subject. This paper represents the first attempt to provide a comprehensive analysis of the existing literature (2010–2015) to identify the taxonomy and distribution of research as well as to identify the advantages and challenges and provide some recommendations to facilitate the effective use of mobile English language learning and its applications. Following a review protocol, articles on mobile English language learning from six major databases (IEEE Xplore, ScienceDirect, Web of Science, ERIC, SpringerLink, and Wiley Online Library) were reviewed. Applying inclusion and exclusion criteria, 133 related articles were identified. The results show that the majority of studies were conducted on application m-learning technologies. Pure mobile applications were the most widely-used applications in the English m-learning context. Meanwhile, concerns regarding quality, usability, integration, financial costs, security and privacy, pedagogical practice, and safety were found to be the main challenges of mobile English language learning. Finally, some recommendations are provided for users, developers/providers, and researchers. The results of this paper can assist users, researchers, policymakers, and practitioners in the education sector to allocate the necessary resources and make plans to mitigate the challenges and facilitate the effective use of mobile English language learning in educational practices.

Big Data Adoption (BDA) has already gained tremendous attention from executives in various fields. However, it is still not well explored in the education sector, where a large amount of academic data is being produced. Therefore, integrating Technology Organization Environment (TOE) and Diffusion of Innovation (DOI), this study aims to develop a theoretical model to identify the factors that influence BDA in the higher education sector. To do so, significant technology-, organization-, and environment-related factors have been extracted from previous BDA studies. Meanwhile, the moderating effects of the university size and the university age are added into the developed model. A sample of 195 data was collected from the managerial side of virtual university (VU) campuses in Pakistan using an online survey questionnaire. Structural equation modeling (SEM) was used to test the research model and developed hypotheses. The results showed that relative advantage, complexity, compatibility, top management support, financial resources, human expertise and skills, competitive pressure, security and privacy, and government policies are significant determinants of BDA. However, the results did not support the influence of IT infrastructure on BDA. Based on the findings, this study provides guidelines for the successful adoption of big data in higher education sector. This study can serve as a piece of help to the ministry of education, administrators, and big data service providers for the smooth adoption of big data.