초․중등 교사의 AI 디지털교과서 활용 수업 초기 경험 분석: 근거이론을 기반으로

초록

This study examined the early instructional experiences of elementary and middle school teachers with artificial intelligence (AI) digital textbooks and explored the environments and contexts surrounding their use. Employing a grounded theory approach, interviews were conducted with 56 teachers actively implementing AI digital textbooks in K-12 settings. Data-including written interview responses and instructional materials-were analyzed through open, axial, and selective coding. The open coding yielded 128 concepts, 34 subcategories, and 14 categories. The central phenomenon identified was the challenge of implementing data-driven individualized instruction using AI digital textbooks. The identified causal conditions included the limitations of traditional learning environments and the need for an integrated platform. The identified context conditions comprised constrained digital teaching-learning environments and diverse digital instructional methods, while intervening conditions involved teacher- and student-related variables. Correspondingly, the suggested strategies included leveraging dashboards for learning data analysis, designing data-driven individualized instruction, implementing data-driven assessment and feedback, and providing socio-emotional support through various features. The enactment of these strategies enhanced learners’ agency, improved teachers’ abilities to implement individualized instruction, and revealed the need for improved system quality and usability. This paper provides policy and practical implications to promote the effective use of AI-based learning platforms.

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