Reform and Practice of "Capability-Targeted" Algorithm Analysis and Design Course Based on Deep Learning

Abstract

This paper focuses on the teaching reform of the "Algorithm Analysis and Design" course, proposing a competency-targeted teaching model in conjunction with deep learning technology. Based on AE dimensionality reduction and K-means, an intelligent learning situation analysis model is designed. The teaching content is reconstructed in a tiered manner, and a targeted teaching method is innovatively proposed relying on a dynamic difficulty adjustment mechanism. Additionally, a diversified assessment method is innovated to comprehensively assess students' abilities. Practice has shown that this model significantly enhances students' algorithm design capabilities and engineering practice literacy, providing a replicable path for the reform of computer science courses in the intelligent era.