Psychological Fitness Education Driven by Artificial Intelligence Technology and Its Influence on Education Assessment

Abstract

To maximally capture the information conveyed by students' psychological fitness data, this paper examines strategies for enhancing psychological fitness education and its assessment through AI technology. It introduces an assessment model based on fuzzy mathematics and neural network technology. This model processes students' psychological fitness data to quickly identify anomalies, thereby detecting potential psychological fitness issues. Utilizing the MATLAB simulation tool, the model is trained with psychological fitness instructional data. The training results show that the algorithm achieves an accuracy of 95.97%, surpassing other comparison algorithms. The comparison of simulation experiments confirms the significant positive impact of the proposed AI-driven psychological fitness assessment model on education.