Design of a ChatGPT-integrated PBL based Physical Computing Course for Pre-service Teacher : Exploring Learning Satisfaction and Self-directed Learning Competence

This paper proposes a ChatGPT-integrated Project-Based Learning (PBL) model as an instructional approach to enhance preservice teachers' self-directed problem-solving and practical competence, and analyzes learners' satisfaction and the effectiveness of its application.By analyzing how generative AI supports learning engagement and problem-solving in PBL-based instruction, this study explores the potential to foster practical competencies and self-directed learning attitudes in future teacher education programs.During the course, 31 third-year or higher preservice teachers majoring in computer education participated in a 12-week program in which they used Arduino to design physical computing environments and develop instructional lesson plans.Survey results revealed high levels of satisfaction with the project-based learning approach (M = 4.64, t > 14, p < .001)and statistically significant satisfaction with ChatGPT integration (M = 4.57, t > 14, p < .001).By presenting a concrete example of applying AI-based instruction in an actual classroom setting, this paper provides an empirical model of AI-integrated PBL for preservice teacher education, offering practical insights for curriculum design in the digital era.Furthermore, by demonstrating the instructional application of ChatGPT in hardware oriented physical computing classes, it contributes to identifying both the educational potential and limitations of AI in computer and information education contexts.