Research on the Optimization Path of Visual Design Courses in the Artificial Intelligence Technology Environment

DOI: https://doi.org/10.62517/jhet.202615203

Author(s)

Yi Liao*, Jinghong Nie

Affiliation(s)

Guangzhou Xinhua University, Guangzhou, Guangdong, China *Corresponding Author

Abstract

With the rapid development of artificial intelligence (AI) and generative AI (AIGC), visual design education is facing profound changes and new demands. Traditional visual design courses overemphasize manual creation and experience teaching, which are inconsistent with the intelligent development trend of the design industry. Based on constructivist learning theory and human-AI collaborative innovation theory, this paper studies the optimization path of visual design courses in the AI environment. It proposes to update teaching content by adding AI tool application and data analysis modules, innovate teaching methods through human-AI collaborative projects and personalized learning, improve practical teaching by combining real industry projects, and establish a diversified evaluation system. Meanwhile, this paper analyzes the main challenges in implementation, including technical and cost constraints, teachers’ AI literacy, copyright and ethical issues, and students’ over-reliance on AI, and puts forward corresponding countermeasures. This study aims to promote the intelligent reform of visual design courses and cultivate compound talents with both design ability and AI application skills to meet the needs of the intelligent creative industry.

Keywords

Visual Design; Artificial Intelligence; Course Optimization

References

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