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    ChatGPT 기반 공학계열 AIoT 비교과 프로그램의 개발 사례 연구 = A Case Study on the Development of a ChatGPT-Based AIoT Extracurricular Program for Engineering Students

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    https://www.riss.kr/link?id=A110190640

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    This study aims to develop and implement an AIoT extracurricular program that integrates ChatGPT into engineering education and to examine its effectiveness with a focus on students’ problem-solving competence. The program was designed with input from industry and education experts and incorporated ChatGPT-assisted coding practice, AIoT device operation, and an individual proj-ect involving the design, implementation, and demonstration of an AIoT-based system. Using a one-group pretest–posttest design, student satisfaction and problem-solving competence were measured through surveys. The results indicated high overall satisfaction and statistically significant improvements across all subdomains of problem-solving competence. Qualitative analysis of project outcomes further revealed that students enhanced their ability to define problems, generate solutions, and iteratively refine their designs using ChatGPT as a learning support tool. These findings suggest that a ChatGPT-integrated AIoT program can effectively enhance engineering students’ problem-solving and integrative competencies. The study provides foundational insights for applying ChatGPT-based learning support systems to engineering design courses and future AIoT-related curricula.
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    This study aims to develop and implement an AIoT extracurricular program that integrates ChatGPT into engineering education and to examine its effectiveness with a focus on students’ problem-solving competence. The program was designed with input fr...

    This study aims to develop and implement an AIoT extracurricular program that integrates ChatGPT into engineering education and to examine its effectiveness with a focus on students’ problem-solving competence. The program was designed with input from industry and education experts and incorporated ChatGPT-assisted coding practice, AIoT device operation, and an individual proj-ect involving the design, implementation, and demonstration of an AIoT-based system. Using a one-group pretest–posttest design, student satisfaction and problem-solving competence were measured through surveys. The results indicated high overall satisfaction and statistically significant improvements across all subdomains of problem-solving competence. Qualitative analysis of project outcomes further revealed that students enhanced their ability to define problems, generate solutions, and iteratively refine their designs using ChatGPT as a learning support tool. These findings suggest that a ChatGPT-integrated AIoT program can effectively enhance engineering students’ problem-solving and integrative competencies. The study provides foundational insights for applying ChatGPT-based learning support systems to engineering design courses and future AIoT-related curricula.

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