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Christian Santiago, Aurora State College of Technology, PhilippinesAbstract
This study employed a Case Study to examine the feasibility and impact of integrating ChatGPT as a strategic partner in environmental science education at a state college in the Philippines through a Collaborative Action Research (CAR) framework. The participants included one instructor and 214 third-year Bachelor of Science in Agriculture students. Over nine sessions, the research followed an iterative CAR cycle guided by the IDEE framework (Identification, Determination, Ethical Consideration, Evaluation). Data were collected through multiple methods: pre- and post-intervention problem-solving tests to measure learning outcomes, structured teacher observations, and thematic analysis of qualitative student feedback. The intervention's contribution to student engagement and skills was measured by a significant increase in pass rates on situational problem-solving tests and by positive student reflections that indicated enhanced critical thinking and active participation. Results demonstrated that the ChatGPT-assisted CAR framework effectively supported the development of teaching strategies that fostered student engagement, active learning, and problem-solving skills. However, major challenges were identified, including the need for significant teacher mediation to contextualize AI-generated strategies, the risk of over-reliance that can stifle deep pedagogical reflection, and initial student difficulty in adapting to inquiry-based methods. This study concludes that while ChatGPT is a powerful tool for instructional co-design and data analysis within a CAR framework, its success depends critically on the teacher’s reflective practice and adaptive expertise to ensure strategies are contextually relevant and pedagogically sound.
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