Generative AI in education: Process-aware pedagogy, assessment integrity, and institutional governance

Background: Generative artificial intelligence (GenAI), particularly large language models such as ChatGPT, is rapidly transforming higher education by reshaping how knowledge is produced, assessed, and mediated through digital systems. While these tools offer new opportunities for learning support and instructional efficiency, they also raise significant concerns regarding academic integrity, institutional governance, and ethical sustainability. Methods: This study conducts a qualitative thematic literature review of research published between 2020 and 2025. Using thematic synthesis, the study analyzes scholarly articles, institutional reports, and policy discussions addressing the integration of generative AI in higher education. The analysis focuses on four thematic areas: the rise of GenAI in educational contexts, academic integrity challenges, institutional and policy responses, and ethical and environmental implications. Results: The review identifies four key tensions shaping current debates: rapid student adoption outpacing institutional readiness; growing ambiguity in authorship and assessment practices; fragmented policy responses ranging from prohibition to cautious integration; and limited attention to the ethical and environmental costs of large-scale AI deployment. The findings indicate that these issues are frequently discussed in isolation rather than as interconnected challenges. Conclusions: The study argues for a process-aware pedagogical framework, referred to as augmented pedagogy, that positions generative AI as a cognitive scaffold rather than a substitute for learning. Such an approach emphasizes transparency in AI use, process-oriented assessment, and responsible institutional governance to ensure that AI integration strengthens rather than undermines the educational mission of universities.