Perspectives on Teaching and Learning in Higher Education in the Era of Generative AI

This paper presents a systematic literature review (SLR) exploring perspectives on teaching and learning in higher education within the context of Generative AI advancements. By focusing on key areas such as teaching methodologies, student engagement, and ethical challenges, this research offers a detailed analysis of the changes that AI technologies, like GPT-4 and DALL-E, bring to academic settings. The findings indicate that while Generative AI provides opportunities for personalized learning and adaptive teaching, it also introduces significant challenges related to academic integrity, algorithmic bias, and data privacy. The paper provides insights into how educators and institutions can embrace Generative AI while addressing its ethical complexities. The paper employed a qualitative approach where key themes were identified such as Transformation in teaching Methodologies, Student Engagement and Learning Outcome and Ethical Challenges. The researcher adopted a purposive sampling method where several papers were purposefully selected based on the research topic. The PRISMA framework also played a critical role in selecting the relevant papers.