Integration of Generative Artificial Intelligence in Higher Education: Pedagogy Factors and Best Practices

The rapid advancement of artificial intelligence (AI), particularly generative artificial intelligence (GAI), is transforming numerous sectors, including higher education. GAI utilises advanced machine and deep learning technologies to create personalised, high-quality content across various media forms. This study aims to provide comprehensive insights into the integration of GAI in higher education, examining its technological aspects, pedagogical implications, and the broader ecosystem. It identifies both opportunities and challenges, advocating for the cautious adoption of GAI to enhance teaching and learning. The application of GAI could significantly support sustainable learning outcomes and the development of interdisciplinary skills that improve educational experiences. This analysis is framed by three theoretical perspectives: technological pedagogical content knowledge (TPACK), the technology acceptance model (TAM), and the twenty-first-century learning framework. The findings suggest that higher education institutions should strategically embrace GAI to meet the global educational goal of quality education. Future research should extend to empirical studies to pinpoint specific GAI techniques that can be effectively integrated into educational practices. This will provide valuable guidance for policymakers, academic leaders, and practitioners in developing strategies to overcome the challenges associated with GAI in education.