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Research on the Strategy of Enhancing Practice Teaching Effectiveness in Professorship Education Through CAD and Neural Network Technology

Author

Listed:
  • Yuemin Gao

    (Qinhuangdao Vocational and Technical College, China)

  • Wei Wang

    (Qinhuangdao Vocational and Technical College, China)

  • Wenqiang Dai

    (Qinhuangdao Vocational and Technical College, China)

  • Qiongyao Liu

    (Qinhuangdao Vocational and Technical College, China)

  • Guoxin Li

    (Qinhuangdao Vocational and Technical College, China)

Abstract

This study explored the integration of computer-aided design (CAD) and neural network technology in vocational education, focusing on course design, skill training, and project-based learning. Through analysis, the study reveals how this technological integration improved students' practical skills, innovative thinking, and problem-solving abilities. Feedback from students indicated high satisfaction with the personalized resources provided by the system, which effectively met their learning needs. Empirical findings showed significant improvements in students' practical capabilities after applying CAD and neural network technology. Compared to traditional models, students demonstrated faster execution and better reporting skills. This integration marks a breakthrough in practical teaching in professorship education, enhancing both instructional effectiveness and the overall learning experience.

Suggested Citation

  • Yuemin Gao & Wei Wang & Wenqiang Dai & Qiongyao Liu & Guoxin Li, 2025. "Research on the Strategy of Enhancing Practice Teaching Effectiveness in Professorship Education Through CAD and Neural Network Technology," International Journal of Information System Modeling and Design (IJISMD), IGI Global, vol. 16(1), pages 1-19, January.
    • Handle: RePEc:igg:jismd0:v:16:y:2025:i:1:p:1-19
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