This study investigates the impact of the ChatGPT-integrated Decision Tree Interactive Learning Model on students' decision-making skills. By merging artificial intelligence with traditional decision tree methodologies, this model provides a personalized, interactive learning experience that guides learners in gradually constructing and optimizing decision paths, while dynamically adjusting their choices in complex scenarios. The study was conducted with 80 Chinese students at King Mongkut’s Institute of Technology Ladkrabang in Bangkok, Thailand, randomly assigned to one of two groups: 40 students used the ChatGPT-integrated model, while the other 40 followed traditional teaching methods. A pre-test and post-test design was employed, utilizing a decision-making skills self-assessment as the primary evaluation tool. Means (x̄) and standard deviations (SD) were calculated, and an independent samples t-test was performed to compare the groups. The findings revealed that students using the ChatGPT-integrated model achieved significantly higher decision-making skills scores than those in the traditional teaching group, with differences reaching statistical significance at the 0.05 level. This study introduces a novel approach to enhancing students' decision-making abilities, providing empirical evidence for the potential of AI to foster higher-order cognitive skills in educational technology, and establishing a critical foundation for further integrating AI into education practice.

Authors:
Yanli Miao, King Mongkut’s Institute of Technology Ladkrabang, Thailand
Kanyarat Sriwisathiyakun, King Mongkut’s Institute of Technology, LadKrabang, Thailand
Thanin Ratanaolarn, King Mongkut’s Institute of Technology, LadKrabang, Thailand

About the Presenter(s)
Ms. Yanli Miao is currently pursuing her PhD in Technology Enhanced Learning and Innovation at King Mongkut's Institute of Technology, Bangkok, Thailand. She is working at Shanxi Vocational University of Engineering Science and Technology, China.

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