AI Technology Empowers the Study of Creative Transformation of Traditional Culture in Higher Vocational Environmental Art Design

With the rapid development of AI technology, higher vocational institutions face an urgent challenge in educational digital transformation: how to effectively implement AI technologies in environmental art education to genuinely enhance students' practical skills and improve institutional teaching efficiency. This study proposes a three-phase pedagogical model to empower students' design practices: Phase 1 establishes an AI-augmented material repository for classroom instruction, constructing a robust resource foundation for curriculum development. Phase 2 cultivates students' competence in intelligently extracting keywords from cultural semantics, enabling precise analysis of traditional patterns. Phase 3 develops a human-AI collaborative design workflow to guide students in completing design transformations. Experimental results demonstrate a 26.7% increase in pattern application accuracy within the test group after AI adoption. This research innovatively integrates AI tool adaptation with digital cultural verification and presentation systems, not only providing a replicable implementation framework for traditional culture pedagogy but also advancing the digital reform of teaching evaluation mechanisms. The findings offer paradigmatic significance for the intelligent transformation of art and design education.

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Publication Details

Published
2025-03-28
DOI
https://doi.org/10.1145/3745238.3745406
Primary Topic
Digital Media and Visual Art
Type
article
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article

AI Technology Empowers the Study of Creative Transformation of Traditional Culture in Higher Vocational Environmental Art Design

Zhongfeng Chen, Xianqiong Liao, Qianqian Ma, Hsiangchu Lai
Digital Media and Visual Art
article

AI Technology Empowers the Study of Creative Transformation of Traditional Culture in Higher Vocational Environmental Art Design

Zhongfeng Chen, Xianqiong Liao, Qianqian Ma, Hsiangchu Lai
article en

Abstract

With the rapid development of AI technology, higher vocational institutions face an urgent challenge in educational digital transformation: how to effectively implement AI technologies in environmental art education to genuinely enhance students' practical skills and improve institutional teaching efficiency. This study proposes a three-phase pedagogical model to empower students' design practices: Phase 1 establishes an AI-augmented material repository for classroom instruction, constructing a robust resource foundation for curriculum development. Phase 2 cultivates students' competence in intelligently extracting keywords from cultural semantics, enabling precise analysis of traditional patterns. Phase 3 develops a human-AI collaborative design workflow to guide students in completing design transformations. Experimental results demonstrate a 26.7% increase in pattern application accuracy within the test group after AI adoption. This research innovatively integrates AI tool adaptation with digital cultural verification and presentation systems, not only providing a replicable implementation framework for traditional culture pedagogy but also advancing the digital reform of teaching evaluation mechanisms. The findings offer paradigmatic significance for the intelligent transformation of art and design education.

Nanyang Polytechnic (SG), Guangdong Research Institute of Water Resources and Hydropower (CN)
Openalex Percentile: Top 67%
Digital Media and Visual Art
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AI Technology Empowers the Study of Creative Transformation of Traditional Culture in Higher Vocational Environmental Art Design — Zhongfeng Chen, Xianqiong Liao, et al. · (2025) | TGRS Research Map | TGRS