AI 디지털교과서 활용 역량 강화를 위한 교사 연수 모델 개발
Development of a Teacher Training Model for Enhancing AI Digital Textbook Utilization Competency
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The advancement of artificial intelligence (AI) in education has led to the emergence of AI Digital Textbooks (AIDT), transforming teacher-student interactions by supporting personalized, self-directed, and collaborative learning. To effectively utilize AIDT, teachers require enhanced AI and digital literacy competencies. However, existing training programs lack a structured approach to integrating AI-based pedagogical strategies. This study develops a teacher training model that strengthens AIDT utilization by incorporating the TPACK framework, Cognitive Load Theory, and Learning Analytics. Additionally, the Forschendes Lernen (FL) approach is applied to foster inquiry-based learning, enabling teachers to explore and implement AI-driven teaching methods. The proposed model emphasizes hands-on AI teaching strategies, adaptive lesson design, and AI-assisted feedback mechanisms, overcoming the limitations of traditional training programs. This research provides a structured framework for AIDT-based teacher professional development and offers insights into AI integration in education. Future research should focus on empirical validation of the model’s effectiveness and continuous refinement to align with emerging AI technologies.
Abstract
The advancement of artificial intelligence (AI) in education has led to the emergence of AI Digital Textbooks (AIDT), transforming teacher-student interactions by supporting personalized, self-directed, and collaborative learning. To effectively utilize AIDT, teachers require enhanced AI and digital literacy competencies. However, existing training programs lack a structured approach to integrating AI-based pedagogical strategies. This study develops a teacher training model that strengthens AIDT utilization by incorporating the TPACK framework, Cognitive Load Theory, and Learning Analytics. Additionally, the Forschendes Lernen (FL) approach is applied to foster inquiry-based learning, enabling teachers to explore and implement AI-driven teaching methods. The proposed model emphasizes hands-on AI teaching strategies, adaptive lesson design, and AI-assisted feedback mechanisms, overcoming the limitations of traditional training programs. This research provides a structured framework for AIDT-based teacher professional development and offers insights into AI integration in education. Future research should focus on empirical validation of the model’s effectiveness and continuous refinement to align with emerging AI technologies.