Community-engaged problem-based learning (CE-PBL) integrates problem-based learning with community engagement to foster experiential, student-centred education. This study evaluates the CE-PBL in a sustainable energy master programme using qualitative feedback from 122 students across 10 cohorts (2002–2020), using hybrid thematic analysis with generative AI. The analysis identifies themes aligning closely with programme objectives and graduate attributes, such as teamwork, technical expertise, and adaptability. Human-machine collaboration using ChatGPT-4 effectively supported data analysis, though the study underscores the essential role of human verification for contextual accuracy. The study shows that the CE-PBL module significantly contributes to developing critical skills in sustainable energy engineering students. However, further research is needed to assess its broader impact.
COMMUNITY-ENGAGED PROBLEM-BASED LEARNING (CE-PBL): PREPARING SUSTAINABLE ENERGY EXPERTS FOR APPLIED CONTEXTS
Reference Text
Proceedings of the 21st International CDIO Conference, hosted by Monash University, Melbourne, Australia, June 2-5, 2025 Year
2025 Authors
Affiliations
Pages
490-500 Abstract
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