Given the rapid advancements in artificial intelligence (AI) and its potential implications for higher education, this article seeks to critically evaluate the strategic adoption of AI in the framework of smart universities.In this article, innovative institutions are perceived to be an imminent transformation in higher education that utilizes AI and emerging technologies to transform academic leadership and administrative processes.The main assumption is that through such integration, universities can achieve personalized learning pathways, economic efficiency, and overall performance improvement.However, entering this new educational paradigm requires a thorough examination of potential challenges such as questions regarding educational quality, job loss, bias risk, privacy violations, and security concerns.The main goal of this article is to provide a balanced assessment to assist stakeholders in making informed strategic decisions regarding the endorsement and advancement of the smart university model.A pivotal factor in this discourse is the acceptance by employers of academic credentials that include AI, a variable that may significantly redefine the education sector.Within a comprehensive analysis of its broader social impact, this article also delves into the implications of AI-based innovations for universities.

Amid the growing need to keep learners abreast of rapid technological advancements brought about by the Fourth Industrial Revolution, this study explores perceived needs of students in virtual learning environments supported by emerging technologies. A survey was conducted across five leading open universities in Southeast Asia. The study aimed to identify student preferences regarding features of their virtual learning environments that could better prepare them as productive citizens and professionals. Findings indicate strong interest in interactive books and learning analytics, underscoring the importance of enhancing learner engagement and data-informed instruction. The results inform the development of a strategic roadmap to guide open universities in prioritizing technological and pedagogical innovations aligned with the evolving expectations of digital-age learners.

This study examines the attitudes of distance education students toward AI integration in teaching and learning and is grounded in a multidimensional theoretical framework.It explores cognitive, affective, behavioral, and ethical dimensions as well as the dimension of actual usage by surveying students from two distance-learning universities.Findings reveal enthusiasm for AI's potential despite moderate self-reported competence and limited prior use.Exploratory factor analysis supports the five-dimensional structure, while regression analyses show no significant effects of gender, age, or study year.The results suggest that AI literacy, ethical awareness, and structured training opportunities may be key to fostering engagement.Recommendations include inclusive training for both students and faculty.

Team-based learning (TBL) is one pedagogy used to promote active learning.While TBL was initially implemented in the face-to-face classroom, there is a growing need for collaborative pedagogies in online classrooms.Course delivery in an online classroom may include a variety of formats and be accompanied by challenges related to the transition from a face-to-face classroom to an online modality.Instructors may have to devote more energy to course design, learning new technology tools, promoting student engagement, and planning in general.Consequentially, students can benefit from active learning through generating engagement online.Teaching TBL online may afford the positive benefits known to be associated with TBL while still allowing for the flexibility and accommodations of distance learning.This original qualitative research examined instructors' perceptions of the challenges and successes of teaching TBL online across three distinct modes of course delivery and offers implications and considerations for instructors transitioning into an online setting.

This study provides a thorough bibliometric analysis of the research landscape concerning the application of soft computing in higher education.This study collects 5,140 pieces including books, book chapters, journal articles published in respected journals, and conference papers presented at notable international conferences that were published from 2010 to 2023.The research aims to map the intellectual contours of this dynamic field, identify seminal works, and elucidate the evolution of key themes and methodologies.Publication trends, key areas, influential articles, publication venues, and several noteworthy topics related to soft computing applications in higher education were explored and the extracted data was visualized with the help of VOSviewer. Keyword clustering and trend analysis provide insights into the predominant themes, revealing a transition from theoretical foundations to practical applications and integration into pedagogical practices. China has published the most papers and has the most productive authors in the field of Artificial Intelligence, PatternRecognition, and Neural Networks.The analysis reveals a significant growth in the volume of research, indicating an increased recognition of soft computing as an essential facet of educational technology.The study provides researchers with a better understanding of the application of soft computing research in the field of higher education and existing knowledge gaps for further research.Practitioners may benefit from the bibliometric review to keep abreast of the current discussions and applications of soft computing in higher education.The current review is one of the few attempts to investigate soft computing applications in higher education using a comprehensive set of articles published during the past decade.

The rapid expansion of online education in the United States, accelerated by the COVID-19 pandemic, has significantly increased student enrollment in distance learning, highlighting the flexibility and accessibility that online education offers.However, this growth raises concerns about maintaining student engagement in online environments, which is crucial for achieving positive learning outcomes and requires careful consideration of institutional policies and practices.This study aims to provide educators with a deeper understanding of the dynamics of fostering student engagement in online learning.The linkages between student empowerment, self-efficacy, self-regulation, and perceptions of technical support services are examined to understand better how these factors relate to student engagement.An analysis of the responses of 313 business students from a regional university in the United States supports the idea that to foster more engaged and productive students, educators and institutions play a crucial role in facilitating student empowerment and self-efficacy and developing self-regulation skills.

Although online teaching can be affected by a number of factors, ranging from the usage of broadband and digital equipment to the skills of users, teachers' digital literacy has been recognized as a key component that can impact the practices of online teaching considerably.This study takes Suzhou Singapore Industrial Park Foreign Language School (SF School), an international high school in China, as a case to investigate how teachers' digital literacy level may impact their teaching practices and experiences.The findings of this research, although the digital literacy level of teachers who participated in this research is generally high, are not balanced in different aspects.Moreover, teachers did not have very positive reflections on the experiences and practices of online teaching during the period of Covid-19.Although teachers tend to attribute this to several aspects from both the student and technological side, they do not have much awareness about the required design of online teaching, which is an approach different from onsite teaching, and echoes the status of the unbalanced digital literacy of the teachers.