Reconfiguring tutor–peer roles to foster critical thinking in medical PBL assisted by tutor‐managed chatGPT

Abstract

BACKGROUND: Critical thinking skills (CTS) are essential in medical education. Problem-based learning (PBL) effectively develops CTS, with generative AI (e.g., ChatGPT) offering enhancement potential. OBJECTIVES: This study investigates how a tutor-managed ChatGPT-PBL model: (1) reconfigures tutor/peer roles and CTS compared to traditional PBL; (2) establishes predictive relationships between tutor/peer roles and CTS and (3) confirms optimal operational parameters for tutor-managed ChatGPT to enhance CTS. METHODS: A quasi-experimental study assigned 170 medical students to either a ChatGPT-PBL or a traditional PBL group. Data from a 31-item survey assessing tutor and peer roles and CTS, along with learning logs and tutor observations for 36 participants, recorded AI engagement metrics (e.g., query frequency, multi-source validation, comparative questioning). The intervention used a pre-defined "3-2-60 Rule" (≥3 queries/session, ≥2 authoritative sources/claim, >60% comparative framing), derived from existing literature, to guide ChatGPT engagement. Interrelationships were examined. RESULTS: ChatGPT-PBL improved CTS outcomes, enhancing tutor-guided constructive/self-directed/contextual/collaborative learning and peer-driven information processing/communication/critical analysis. Regression identified collaborative learning and information processing as CTS predictors in both approaches, but ChatGPT shifted their influence: collaborative learning's role decreased while information processing's increased. High adherence to the "3-2-60 Rule" correlated with CTS gains, with high-engagement groups (>3 queries, ≥2 sources, comparative framing) outperforming peers. CONCLUSIONS: Tutor-managed ChatGPT reconfigures tutor/peer roles in PBL to enhance CTS development. Structured peer-ChatGPT-tutor interactions (following the 3-2-60 rule) contributed to enhancing CTS. Given ChatGPT's socioemotional limitations, future implementations should embed adversarial ChatGPT tasks and ethical transparency protocols.

Ähnliche Arbeiten