Implementing generative AI (GenAI) in higher education: A systematic review of case studies

The introduction of Generative Artificial Intelligence (GenAI) tools, like ChatGPT, into higher education heralds a transformative era, reshaping instructional methods, enhancing student support systems, and redefining the educational landscape. Recent literature reviews on GenAI highlight a lack of focus on how these tools are being practically implemented in educational settings. Addressing this gap, the present study systematically examines empirical case studies that demonstrate the integration of GenAI into teaching and learning in higher education, offering actionable insights and guidance for academic practice.

We conducted a search of relevant databases and identified 21 empirical studies that met our inclusion criteria. The selected studies cover a diverse range of disciplines, locations, types of participants (from first-year students to postgraduates and academics), and a variety of methodologies. We classified the selected publications based on the pedagogic theory of Laurillard's Conversational Framework (LCF) and the Substitution, Augmentation, Modification, and Redefinition (SAMR) framework. We also synthesized definitions from selected empirical studies and recent research exploring Technological Pedagogical Content Knowledge (TPACK) in the age of GenAI, providing a comprehensive understanding of GenAI-TPACK factors. Limitations and future research opportunities are also discussed. The paper concludes by providing a GenAI-TPACK diagram to guide educators in effectively incorporating GenAI tools into their teaching practices, ensuring responsible and impactful use in higher education.