Research on Intelligent Development of Talent Cultivation Mode of Higher Vocational Innovation and Entrepreneurship Education Based on Data Mining under the Perspective of Industry-Teaching Integration

Abstract

Against the backdrop of the integration of industry and education, vocational college innovation and entrepreneurship education has entered a new phase characterized by diversification, emphasis on intrinsic development, and intelligent development. This article constructs a student learning behavior analysis model, collects student learning behavior data, and proposes the use of the k-means algorithm to analyze student behavior. Additionally, course access, video viewing, assignment performance, daily performance, and interaction are selected as online learning behavior characteristics. The results reveal that vocational college students exhibit a high proportion of passive learners, with relatively low proportions of passive and active learners. Passive learners account for the largest proportion at 87.5%, and learning quality is primarily influenced by factors such as teacher attention, chapter quizzes, assignments, and course credits. The construction of a vocational college innovation and entrepreneurship education talent cultivation model can be approached from three aspects: establishing a comprehensive innovation and entrepreneurship talent cultivation system, implementing an apprenticeship system for innovation and entrepreneurship talent cultivation, and developing an innovation and entrepreneurship course system.