Integrating AI to Personalize Biotechnology Education: Enhancing Learning Outcomes and Industry Preparedness

Abstract

This study evaluates an Artificial Intelligence-Based Teaching Mode Identification Method for College Civic Education. It utilizes big data analytics and a model process framework to develop an AI-driven teaching mode. By analyzing student data, the method predicts learning outcomes, helping educators assess if students can successfully complete the course after a specific instruction period. The final assessment identifies learning challenges early, enabling targeted interventions. This approach not only aids teachers in adjusting teaching strategies in real time but also enhances the adaptive and personalized capabilities of the educational platform, easing the teaching burden.