Problem-Based Learning in the Generative AI Era: A Literature Exploration of Pedagogical Model Adaptation

Abstract

This study aims to explore and synthesize the literature on the adaptation of the Problem-Based Learning (PBL) model in the era of Generative Artificial Intelligence (GenAI) in higher education. The background of this research is the rapid development of GenAI, such as ChatGPT, which has transformed the educational landscape; however, a knowledge gap remains regarding how the PBL model fundamentally adapts. This study employs a systematic literature review method with a scoping review approach following the PRISMA guidelines. The literature search was conducted across four major databases (Scopus, Web of Science, ERIC, and ScienceDirect) with publication limits from 2021 to 2026. The findings identified five main themes: Forms of GenAI integration in PBL; shifting roles of educators and students; challenges and ethical considerations; opportunities and benefits; and pedagogical strategies for effective implementation. The findings indicate that GenAI not only functions as an assistive tool but also transforms the essence of the PBL process through personalized learning, real-time feedback, and the redefinition of educator roles from knowledge providers to facilitators and learning designers. The conclusion of this study affirms that the adaptation of the PBL model in the GenAI era requires the redesign of problem scenarios, the development of critical AI literacy, the formulation of ethical guidelines, and faculty training to utilize AI responsibly.