Process-Oriented Analysis of Knowledge Construction in Problem-Based Learning: A Systematic Review of Health...

Problem-Based Learning (PBL) is widely implemented in health professions education (HPE). Small-group knowledge construction plays an essential role in trainees' learning from PBL tutorials. However, there is a dearth of systematic reviews to unpack the black box of the PBL knowledge construction process. The current review tackles this gap by identifying (1) the perspectives and methods adopted to directly assess the PBL knowledge construction process and (2) the factors in group interaction processes that impact PBL knowledge construction. We conducted a systematic search of multiple databases in November 2023 and identified original studies analyzing PBL interaction processes in HPE. Two reviewers conducted a thematic synthesis of the findings. Of 2,691 citations identified, 60 empirical studies (2.2%) from 16 countries and covering eight health professions met the inclusion criteria. Most investigations adopted a social constructivist perspective to analyze recordings, observations, and digital trace data of group interactions, often triangulating with other data for deeper insights. A wide range of qualitative, quantitative, and mixed methods was used to analyze interaction processes. Our synthesis identified a series of intertwined factors that influence knowledge construction: cultural influences and linguistic strategies; interprofessional dynamics, curriculum and assessment practices; learning task design, including technology affordance; tutor facilitation; learner prior knowledge and experience; and team learning behaviors and interaction patterns, such as learner directedness, social-cognitive exchange, group climate, and group interaction patterns. Our review highlighted the complexity of PBL knowledge construction by revealing the interrelated impact of various factors. Future studies should adopt a sociocultural perspective, employ the Design-Based Research approach, and integrate multiple methods and levels of analysis to unravel the dynamic interplay of these factors. Future research directions include exploring new analytics techniques, leveraging AI to develop data-driven interventions, and enhancing the inclusivity of collaborative learning environments.