Project-Based Learning in the Era of Generative Artificial Intelligence: Toward a Hybrid Epistemic Governance Framework for Undergraduate Computer Science Education

Abstract

The integration of generative artificial intelligence technology (GenAI) within higher education contexts is changing the epistemology associated with educational settings. In undergraduate computer science programs, project-based learning (PBL) has traditionally been considered one of the core pedagogical approaches to teaching based on constructivist epistemologies that emphasize purposeful knowledge construction and artifact production. The introduction of AI systems that can generate programming codes, designs, documentation, and feedback undermines the traditional association of cognitive work with epistemological development. This study presents an integrative theoretical approach referred to as Hybrid Epistemic Governance (HEG) in which PBL is rethought in relation to AI learning environments. Based on the principles of sociocultural theory, activity theory, distributed cognition, sociomaterialism, cognitive load theory, and the existing literature on AI literacy, this paper argues that the epistemological axis of pedagogy in the age of AI must shift from being production-centric to governance-centric. Through the HEG framework, this research explores four interrelated dimensions—epistemic discernment, algorithmic reflexivity, governance agency, and authenticity reconstruction—which collectively examine the ways in which learners engage with AI technologies through project work. This study analyzes the structural conflicts that typify the project-oriented nature of work environments facilitated by AI and articulates a set of principles for governance pedagogies along with an approach to future validation through a methodology. By framing project-oriented education as governance of hybrid human-AI knowledge systems, this research contributes to theory development in relation to generative AI technologies in higher education and offers a pragmatic framework for undergraduate computer science education.