A Fuzzy Information Evaluation Model for Scientific Innovation of Art Talents in Colleges

• Main Author: Fanwen Kong
• Format: Article
• Language: English
• Published: Kassel University Press 2020-06-01
• Series: International Journal of Emerging Technologies in Learning (iJET)
• Online Access: https://online-journals.org/index.php/i-jet/article/view/14529

In most colleges, the current scientific innovation model for art talents is not well implemented. Besides, it is a complex task to evaluate the effect of the said model. To solve the problems, this paper attempts to renovate the scientific innovation model for art talent in colleges. Firstly, the authors identified the problems in the current scientific innovation model for art talent training in colleges, and put forward several countermeasures. To evaluate the scientific innovation model, the performance indicators were selected and weighted based on analytical hierarchy analysis (AHP). Next, a fuzzy information evaluation model was established based on the weighted indicators. The research results provide strong supports to the scientific innovation of art talents in colleges.