Research on the Theory-Practice Integrated Training Mode of Medical Vocational Education from the Perspective of AI Dual-Track Evaluation

Abstract

Objective To address the long-standing problems in practical teaching of medical vocational education, such as “emphasis on operation over theory, disconnection between theory and practice, insufficient intelligent intervention, and low scene realism”, this study constructs an AI dual-track evaluation system and explores a new integrated training mode that can effectively improve students’ theoretical knowledge, operational skills and clinical thinking ability. Methods A total of 105 students majoring in nursing, medical imaging and medical laboratory technology were divided into experimental group (n=53) and control group (n=52) by stratified random sampling. The experimental group adopted the AI dual-track evaluation training system, while the control group used the traditional training mode. An 8-month teaching experiment was carried out using controlled experiment method, data mining method and expert consultation method. Through multimodal biological signal collection, medical knowledge graph, dynamic case database and intelligent intervention engine, synchronous evaluation, correlation diagnosis and personalized training of operation standardization and theoretical cognitive level were realized. All evaluation indicators were determined before the experiment. Results Compared with the control group, the theoretical knowledge retention rate of the experimental group increased by 39.6%, and the operational skill migration ability improved by 34.7%. The training preparation time was shortened by 50%, the development efficiency of personalized teaching resources increased by 3 times, and the procurement cost of training equipment decreased by about 40%. The accuracy of theory-practice correlation diagnosis reached 85.3%, the timely rate of intelligent intervention was 92.1%, the accuracy of resource recommendation was 86.5%, and student satisfaction was 90.7%. All key system indicators met the standards. The mode showed significant effects in remedying the shortcomings of two types of students: “skilled in operation but weak in theory” and “good at theory but lagging in operation”. Conclusion The integrated training mode of theory and practice driven by AI dual-track evaluation can fundamentally solve the core pain points of disconnection between theory and practice, single evaluation and insufficient intelligence in medical training. It significantly improves the quality of talent training and teaching efficiency, with both academic value and practical promotion value. It can provide a reproducible technical scheme and practical paradigm for the digital transformation of medical vocational education, the reform of integrated teaching of theory and practice, and the cultivation of high-quality clinical technical talents.