Research Article
Research on the Talent Training Mode of Industrial Design Majors Under the Background of Interdisciplinary
@INPROCEEDINGS{10.4108/eai.16-9-2022.2324901, author={Jianying Zhang and Xiaoping Mao and Yan Ding}, title={Research on the Talent Training Mode of Industrial Design Majors Under the Background of Interdisciplinary}, proceedings={Proceedings of the International Conference on Art Design and Digital Technology, ADDT 2022, 16-18 September 2022, Nanjing, China}, publisher={EAI}, proceedings_a={ADDT}, year={2022}, month={12}, keywords={new engineering industrial design new commission curriculum system interdisciplinary}, doi={10.4108/eai.16-9-2022.2324901} }
- Jianying Zhang
Xiaoping Mao
Yan Ding
Year: 2022
Research on the Talent Training Mode of Industrial Design Majors Under the Background of Interdisciplinary
ADDT
EAI
DOI: 10.4108/eai.16-9-2022.2324901
Abstract
With the transformation of China's manufacturing industry from "Made in China" to "In-telligent manufacturing in China", more and more industrial enterprises value importance of industrial design. Manufacturing also needs industrial design to increase added value of its products urgently. This paper collates and analyzes the definition of the new mission of industrial design majors in colleges and universities, and further analyzes and reflects on the training mode and curriculum construction system that integrates with regional economy. Under the current development status of artificial intelligence, big data, human-computer interaction technology, virtual reality and the background of new engineering, combined with the requirements of the training of application-oriented talents, the paper puts forward the construction of the curriculum system of industrial design majors and elaborates how to construct the interdisciplinary teaching system of the integration of science and technology and art in actual teaching. It also illustrates the goal and new mission of professional training through the comparative analysis of student's ability training data.