Research on the Method of Value-added Evaluation of Vocational Education Based on Decision Tree Model

Value-added evaluation is an important exploration direction for education evaluation in the new era. Empowering value-added evaluation with artificial intelligence is a new trend in education reform in the information age. Introducing AI based value-added evaluation methods in vocational education is conducive to promote high-quality development of vocational education. This article first elaborates on the basic connotation of value-added evaluation in vocational education in relevant work. Secondly, it reviews the development process of decision tree models in the field of educational evaluation; In addition, the rationality of using machine learning algorithms to assist in implementing value-added evaluation is discussed. The following elaborates on the application principles of decision tree models in value-added evaluation. In the experimental section, a decision tree model was used to conduct value-added evaluation and analysis of student performance in computer network course at a vocational secondary school. Finally, the experimental results were analyzed and corresponding teaching suggestions were proposed.