Curriculum Design of Art Appreciation in Colleges Based on Kano Model Demand Analysis

• Published in: 2021 International Conference on Digital Society and Intelligent Systems (DSInS) pp. 67 - 71
• Main Authors: Song, Baoqing, Lin, Ruichong, Wang, Zehua, Cai, Yunji, Wang, Feiyu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 03.12.2021
• Subjects: Analytical models; Art appreciation; Atmospheric modeling; Big Data; Curriculum design; Data models; Indexes; Kano model; Training
• DOI: 10.1109/DSInS54396.2021.9670590

The cultivation of art appreciation ability can effectively improve the aesthetic and humanistic qualities of college students, and it is an indispensable link in aesthetic education. Based on the results of the Kano model demand survey (N=976), which was carried out before the application of big data analysis, the research team has set up a variety of experimental special courses on art appreciation with a combination of different course elements. The conclusion based on the scientific calculation method shows that: students have a high demand for curriculum elements such as professional performance team participation and interaction with artists on the same stage. A retrospective survey of 15% of students who have participated in the course was randomly selected (n=148). The students were satisfied with this experimental art appreciation course and showed higher expectations for the new art appreciation course. The article also puts forward suggestions for art appreciation courses: the combination of knowledge teaching and demonstration performances, enhanced interaction with students, and the level of artistic expression of the lecturers are all positive factors for the sustainable development of art appreciation courses.