Article Details

Abstract

To meet the need for transforming software design pattern teaching in the large-model era, this paper reconstructs the teaching content by replacing the traditional pattern-based classification with a “design problem domain” framework, focuses on five major problem domains, and develops an “identification–evaluation–reconstruction” three-level competency model. During teaching, methods assisted by Artificial Intelligence (AI) are integrated to guide students through the entire design practice process, from the analysis of case requirements and solution generation and evaluation to coding and verification. The reconstructed process-oriented diversified evaluation system incorporates students’ performance in AI practice into process-based assessment and evaluates their genuine understanding of what they have learned. The results show that software design pattern teaching integrated with AI practice effectively improves students’ three-level competencies and overall competence and promotes the transformation of software engineering education from knowledge transmission to competency development.

Keywords

design pattern; design problem domain; three-level competency model; AI assistance

References

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Funding

Wuchang Institute of Technology School level Teaching Reform Research Project (2026JY04)

About the authors

Wang Huifang (1992-), female, Han ethnicity, from Anqing, Anhui Province, is a senior engineer and a master's student. Her research interests include intelligent computing and computer applications.