Exploration of Blended Teaching of Python Artificial Intelligence Programming Foundation in Medical and Engineering Integrated Universities

Abstract

In response to the training needs of compound talents in the integration of medicine and engineering and digital and intelligent transformation, aiming at the problem of the disconnection between theory and medical practice in the traditional teaching of information technology courses in medical and engineering integrated universities, this paper takes the Python artificial intelligence programming foundation course as an example and proposes a project-driven online and offline collaborative blended teaching model. Based on policy orientations such as the Implementation Plan for the Digital and Intelligent Transformation of the Pharmaceutical Industry (2025-2030), a teaching system of "medical case-driven + hierarchical practice" is constructed. Through the collaborative linkage of the Superstar Learning Platform and offline project training, a learning situation database is established and intelligent analysis is used to feed back teaching, forming a complete teaching closed-loop. Teaching practice shows that this model can significantly improve students’ programming application ability and the thinking of the integration of medicine and engineering, and effectively solve the pain points of traditional teaching. The research results provide a set of promotable blended teaching paradigms for the information technology curriculum reform in medical and engineering integrated universities, which are driven by real medical scenarios and supported by data intelligent analysis.