DOI: https://doi.org/10.61957/joerai-20250105

Title: Research on Teaching Reform of Web Development Course Based on DeepSeek Technology

Author: Long Qin, Lin Zhang, Jing Ma

Abstract

Aiming at the core problems of lagging teaching content, insufficient practical training and single evaluation method in the traditional Web Development Technology course, this study carries out systematic teaching reform based on the DeepSeek artificial intelligence platform. Through the construction of “three-in-one” innovative teaching mode: intelligent personalized learning system, real-time AI code tutoring and adaptive learning path; enterprise-level project training platform, simulating the whole process of real development; multi-dimensional dynamic evaluation system, comprehensive evaluation of code quality, architecture design and other key capabilities. Teaching practice shows that the reform has achieved significant results: project development efficiency of students in the experimental class has increased by 32%, code quality scores have increased by 41%, and 82% of the final projects have reached the enterprise standard that can be directly deployed. DeepSeek platform has outstanding performance in intelligent code review (accuracy rate of 92%), personalized learning support, etc., and the students' ability of solving complex engineering problems has increased by 56%, and the competitiveness index of employment has increased by 40%. metrics increased by 40%. The study also proposes an AI application ability training program for teachers and a data security protection strategy, providing a replicable implementation framework for the intelligent transformation of technical courses. This study not only verifies the feasibility of AI technology-enabled professional teaching, but also provides an important reference for education and teaching reform in the context of new engineering disciplines.