Artificial Intelligence Generation Content Empowering Java Framework Application Course for Software Technology Major
Year: 2025
Type: conference-paper
Abstract: With the rapid development of artificial intelligence-generated content (AIGC) technology, its application in the field of education has gradually become an important direction of teaching reform. This paper takes the course of “Java Framework Application “in software technology major as the research object, discusses how to empower the traditional teaching mode through AIGC technology, and improve the teaching quality and practical effect of the course. Firstly, the pain points existing in the current Java framework course teaching were analyzed, including the shortage of case resources, the single practice scene, and the lack of personalized guidance. Secondly, combined with the technical characteristics of AIGC, a multi-dimensional application model covering code generation, intelligent question answering, scene simulation and learning effect evaluation was constructed. By introducing a large language model to automatically generate customized case codes of mainstream frameworks such as Spring Boot and MyBatis, conversational AI is used to assist students to solve development problems in real time, and a virtual project scene is constructed based on generative technology to strengthen engineering practice ability. Teaching practice shows that the application of AIGC technology greatly improves students 'code standardization and project development efficiency, and teachers can accurately locate learning weaknesses through intelligent analysis tools. This study provides a reusable implementation path for the intelligent transformation of technology courses, and verifies the empowering value of generative artificial intelligence in the field of vocational education, which has important reference significance for the optimization of future curriculum system.
Author: Jiahao Zhang
Institution: Guangzhou Huanan Business College
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4412789939