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    개발 중심 모델 기반 교육용 로봇 수업이 예비 교사의 컴퓨팅 사고력 향상에 미치는 효과 분석 = Analyzing the Effects of Development-Centered Model-Based Educational Robotics Classes on Pre-service Teachers’ Computational Thinking

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    https://www.riss.kr/link?id=A110007397

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    In the era of digital transformation, computational thinking (CT) has emerged as a critical competency for future generations. With the 2022 revised curriculum expanding instructional hours in information education to at least 34 hours in elementary schools and 68 hours in middle schools, fostering CT among pre-service teachers has become an urgent priority. This study examines the effects of educational robotics classes, designed using the Development-centered model (DDD model)―one of the five SW education teaching-learning models developed in 2015 and grounded in inquiry learning―on enhancing pre-service teachers’ CT skills.
    The participants were 20 pre-service teachers from OO National University of Education, who engaged in a 15-week (30-session) robotics course structured around the three stages of the DDD model: Discovery-Design-Development. Data were collected through pre- and post-tests, including written CT assessments, CT self-assessments, a robotics function survey, and a questionnaire on stage-specific CT outcomes within the DDD model.
    The paired-sample t-test results from the pre- and post-written assessments of computational thinking revealed statistically significant improvements across all domains, including problem decomposition, abstraction, algorithmic procedures, and automation. Similarly, the paired-sample t-test of the self-assessments indicated significant improvements in all areas, suggesting that the course was effective in enhancing pre-service teachers’ computational thinking. The robotics function survey also showed substantial improvements across all functions, with the greatest gains observed in sensor-related functions (e.g., force and gyroscope sensors), which require complex processing abilities. In the survey on the stage-specific effects of the DDD model in fostering CT, participants most frequently selected the design stage as the most influential, while their awareness of sequential connectivity and cyclical structures was reinforced. These findings indicate that educational robotics classes based on the DDD model are effective in cultivating computational thinking among pre-service teachers.
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    In the era of digital transformation, computational thinking (CT) has emerged as a critical competency for future generations. With the 2022 revised curriculum expanding instructional hours in information education to at least 34 hours in elementary s...

    In the era of digital transformation, computational thinking (CT) has emerged as a critical competency for future generations. With the 2022 revised curriculum expanding instructional hours in information education to at least 34 hours in elementary schools and 68 hours in middle schools, fostering CT among pre-service teachers has become an urgent priority. This study examines the effects of educational robotics classes, designed using the Development-centered model (DDD model)―one of the five SW education teaching-learning models developed in 2015 and grounded in inquiry learning―on enhancing pre-service teachers’ CT skills.
    The participants were 20 pre-service teachers from OO National University of Education, who engaged in a 15-week (30-session) robotics course structured around the three stages of the DDD model: Discovery-Design-Development. Data were collected through pre- and post-tests, including written CT assessments, CT self-assessments, a robotics function survey, and a questionnaire on stage-specific CT outcomes within the DDD model.
    The paired-sample t-test results from the pre- and post-written assessments of computational thinking revealed statistically significant improvements across all domains, including problem decomposition, abstraction, algorithmic procedures, and automation. Similarly, the paired-sample t-test of the self-assessments indicated significant improvements in all areas, suggesting that the course was effective in enhancing pre-service teachers’ computational thinking. The robotics function survey also showed substantial improvements across all functions, with the greatest gains observed in sensor-related functions (e.g., force and gyroscope sensors), which require complex processing abilities. In the survey on the stage-specific effects of the DDD model in fostering CT, participants most frequently selected the design stage as the most influential, while their awareness of sequential connectivity and cyclical structures was reinforced. These findings indicate that educational robotics classes based on the DDD model are effective in cultivating computational thinking among pre-service teachers.

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