Research on AI-Driven Teaching of Medical Data Mining Courses Under the BOPPPS Model

As interdisciplinary integration deepens, the demand for applying engineering principles to address biological and medical challenges is on the rise. While machine learning serves as a crucial tool for processing complex medical data, the effective application of its techniques remains a significant challenge. Therefore, the “Medical Data Mining” course is designed to cultivate students' theoretical and practical skills in biomedical engineering. Current pedagogical practices are hindered by excessive teacher dominance and insufficient student interaction. To address these issues, this study introduces generative artificial intelligence technologies and interactive teaching models, integrated with the BOPPPS instructional design framework. This approach is designed to stimulate deep thinking, enhance student engagement and knowledge retention, and foster the development of critical and creative thinking skills among learners.