Evaluation shows significant improvements in teachers' social-emotional learning competencies using AI courseware, indicating its effective application.
Purpose: This study develops and verifies a teacher training program to enhance their competence in supporting elementary SEL using AI courseware. Methods: Focusing on teachers' AI courseware-based affective instructional design competence, four sub-domains (emotional state recognition, emotional feedback construction, affective information integration into lesson design, and instructional execution and regulation) were identified. Self-efficacy changes were then analyzed for 20 elementary school teachers before and after training. Results: Statistically significant improvements were observed across all sub-domains, indicating the effectiveness of the practice-oriented training program in enhancing teachers' AI courseware-based SEL support competencies. Teachers specifically improved in practical skills like recognizing student emotions, formulating empathetic language, and integrating these into lesson flows, suggesting enhanced ability to reinterpret and utilize AI analysis information. Conclusion: This study proposes a practical training model to enhance teachers' expertise in AI courseware-based emotional design and implementation. Further research on emotional feedback precision and diverse applicability is needed.
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Kwang‐Pyo Hong (2025) studied this question.
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