KUAN YU HENG
National Taipei University of Education Graduate School of Curriculum and Instructional Communication Technology Student
Email：g111244009@grad.ntue.edu.tw
CHANG HSUN LI
National Taipei University of Education Graduate School of Curriculum and Instructional Communication Technology Assistant Professor
Email：hsunli@tea.ntue.edu.tw
Abstract
With the rapid advancement of technology, the importance of programming education continues to grow worldwide. However, students often encounter challenges related to syntax, conceptual understanding, and a lack of effective skills in planning and debugging programs. These difficulties can lead to frustration during the learning process, ultimately impacting learning outcomes. Therefore, identifying effective support tools and instructional strategies to help students systematically learn programming languages has become a critical issue worthy of further investigation.
This study aims to explore the impact of using Generative Artificial Intelligence (GAI) as a teaching support tool, integrated with an inquiry-based learning strategy, on students’ programming learning outcomes. To achieve this goal, a teaching program was designed that incorporates Gemini as the AI assistant and adopts the POEE (Predict–Observe–Explain–Evaluate) model of inquiry-based learning. Through the four-step process of prediction, observation, explanation, and evaluation, middle school students were guided to learn the Python programming language, and their learning outcomes were analyzed.
A one-group pretest–posttest experimental design was employed. The participants were 8th-grade students from a public secondary school in New Taipei city. A Python learning achievement test was administered before and after the intervention, and the collected data were analyzed to examine changes in student performance. The results are expected to demonstrate improvements in students’ Python programming achievement.
Keywords: Generative AI、Inquiry-based learning、Programming