전공 유형별 예비 체육교사의 대화형 AI 기반 체육 수업실연 능력 발달 양상에 관한 단일대상 연구* = A Single-Subject Study on the Developmental Patterns of Interactive AI-Based Physical Education Teaching Performance Among Pre-service Teachers by Major Type

다국어 초록 (Multilingual Abstract)

Purpose: The purpose of this study is to investigate the developmental patterns of teaching performance among pre-service physical education (PE) teachers based on their major types within a Generative AI-powered teaching simulation environment. Specifically, the research aims to empirically analyze the differential developmental trajectories of teaching competencies as influenced by interactive AI-driven real-time feedback and simulations, considering the participants' academic backgrounds (e.g., PE majors vs. double majors).
Methods: To achieve this, pre-service PE teachers (e.g., 2 PE majors and 2 double majors) were selected as participants for a single-subject research design. The experimental intervention consisted of an 'Interactive AI-based Teaching Simulation Program' conducted over five sessions (20 minutes per session). Changes in teaching competencies were repeatedly measured across the baseline, intervention, and maintenance phases. The collected data were analyzed using descriptive statistics and visual analysis.
Results: The key findings are as follows: First, the Generative AI-based intervention led to a significant improvement in PE teaching performance across all pre-service teachers, regardless of their major type. Second, an analysis of developmental trajectories by major type revealed that the PE major group demonstrated rapid acquisition and high stability across overall domains. In contrast, the double major group exhibited a gradual and steady developmental curve. Third, all participants successfully maintained their improved teaching performance levels even after the conclusion of the intervention.
Conclusion: The results of this study suggest that Generative AI serves as a highly effective, personalized instructional tool that accounts for the individual academic characteristics of pre-service PE teachers. Beyond the mere adoption of technology, these findings provide foundational data for establishing data-driven individualized intervention models aimed at enhancing the quality of teacher education through AI-powered teaching simulations amidst the digital transformation of physical education.