In the digital age, the intersection of artificial intelligence (AI) and higher education (HE) poses novel ethical considerations, necessitating a comprehensive exploration of this multifaceted relationship. This study aims to quantify and characterize the current research trends and critically assess the discourse on ethical AI applications within HE. Employing a mixed-methods design, we integrated quantitative data from the Web of Science, Scopus, and the Lens databases with qualitative insights from selected studies to perform scientometric and content analyses, yielding a nuanced landscape of AI utilization in HE. Our results identified vital research areas through citation bursts, keyword co-occurrence, and thematic clusters. We provided a conceptual model for ethical AI integration in HE, encapsulating dichotomous perspectives on AI’s role in education. Three thematic clusters were identified: ethical frameworks and policy development, academic integrity and content creation, and student interaction with AI. The study concludes that, while AI offers substantial benefits for educational advancement, it also brings challenges that necessitate vigilant governance to uphold academic integrity and ethical standards. The implications extend to policymakers, educators, and AI developers, highlighting the need for ethical guidelines, AI literacy, and human-centered AI tools.

This study investigated student teachers’ preferred active learning strategies, and those which they actually received during their teacher preparation programmes. An explanatory mixed methods research design was adopted, including a survey completed by 308 participants and group interviews involving 38 participants. Data were gathered from student teachers completing their university education in three countries: Qatar, Lebanon, and China. Results indicated the prevalence of and a preference for a passive mode of instruction among student teachers as a convenient approach that would guarantee good grades from assessment procedures favouring memorization. Further, several inconsistencies between the quantitative and qualitative data revealed challenges in reconciling the theory-practice gap, changing perceptions towards alternative teacher roles, and realigning assessment procedures with innovative teaching methods.