AI Integration Strategies for the ADTE Teaching Model in Vocational Undergraduate Design Practice Courses
Abstract
role in bridging the gaps between theoretical knowledge and industry role requirements. The ADTE teaching method is based on an articulation ? design ? training ? evaluation integrated closed-loop mechanism, which meets the needs of design practice teaching. However, in
its application process, there are drawbacks such as lack of targeted teaching design, insufficient heuristic guidance, and monotonous evaluation methods. Personalized customization, intelligent simulation, big data analysis, and other advantages of artificial intelligence technology
can precisely address these issues. Effective integration across all pivotal levers can enhance efficiency and improve quality. Grounding in the
practice course characteristics of design, this paper elaborates on the significance and current challenges in the integration of the two dimensions, and proposes corresponding countermeasures for the reform reference of practice courses, so as to better cultivate applied design talents
that meet the social needs.
Keywords
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DOI: http://dx.doi.org/10.70711/wef.v3i12.9447
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