Development of a Biotechnology Student Education Management System Using a Commercial Decision Tree Algorithm for Enhanced Decision-Making

Abstract

The rapid development of biotechnology requires the students' education management system to have dynamic adaptability and accurate decision-making ability. However, the traditional management mode relies more on experience judgment and is difficult to effectively integrate multidimensional data such as academic performance, practical ability and scientific research participation, resulting in the lagging development of personalized training programs. Building an education management system based on business decision tree algorithm can identify key factors affecting students' growth (such as course relevance, experiment failure rate, career inclination) in a data-driven way, and realize academic early warning, optimal allocation of resources, and career development path prediction. This paper deeply analyzes the transformation of Biotechnology Students' education management mode in universities in the era of mega data, analyzes the trend of the transformation of Biotechnology Students' education management mode in universities in the era of mega data, and puts forward the coping strategies and the model of Biotechnology Students' education management system through concept renewal. Knowing the Biotechnology Students' situation through the forecast results is of great significance for doing a good job in education, improving teaching effect and cultivating talents.