An Association Rule Mining-Based Model for Evaluating the Role of Information Technology in Innovation and Entrepreneurship Education: Implications for Biotechnological Commercialization

Abstract

This study introduces an effectiveness evaluation model for innovation and entrepreneurship education informatization, leveraging the association rule mining algorithm. The model establishes a comprehensive evaluation index system, deriving a three-dimensional structure to enable holistic assessments. Determination criteria, identified through data mining, are applied to score key indicators, resulting in an original index matrix and corresponding attribution vectors. This structured approach facilitates accurate and systematic evaluations of educational informatization effectiveness. The proposed model is particularly relevant to the biotechnology sector, where fostering innovation-driven talent is essential for translating scientific advancements into commercially viable solutions. By analysing the relationship between information technology adoption and the outcomes of entrepreneurship education, the model provides actionable insights for universities and biotechnology enterprises seeking to strengthen talent pipelines and commercialization capabilities. Experimental validation demonstrates that the model achieves a 51% improvement in processing power compared to traditional evaluation methods, underscoring its efficiency in managing complex educational data. This enhanced processing capability enables faster, more precise evaluations, which are crucial for aligning educational initiatives with the evolving needs of the biotechnology industry. Overall, the study offers a robust framework that bridges the gap between educational informatization and biotechnological commercialization, supporting sustainable growth and global competitiveness in the biotechnology sector.