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This research examined the feasibility of utilizing ChatGPT within a Collaborative Action Research (CAR) framework as a strategy in environmental science classrooms in a State College in the Philippines. It focuses on how ChatGPT can be effectively integrated into the CAR cycles to enhance teaching practices and improve learning outcomes. The AI-assisted process, guided by the design framework IDEE (Identification, Determination, Ethical Consideration, Evaluation) and CAR framework, facilitated the teaching strategies to promote critical thinking, problem-solving, and applying theoretical knowledge. These ChatGPT-generated strategies were adapted, implemented, and refined through the iterative CAR cycles, driven by teacher observations, student outputs, and feedback. Results demonstrated that the framework contributed to student engagement, fostering active learning and improving problem-solving skills, while several challenges were accounted for. This study highlights the benefits of ChatGPT in aiding instructional design, data, and information analysis for improvement and overall classroom practices. However, it emphasizes the need for critical evaluation and adaptation to ensure effective use in the educational and CAR contexts.
Christian Santiago (Thu,) studied this question.