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In the age of the Internet, the teaching of dynamic visual communication design (DVCD) is an irresistible trend for the innovation of visual art teaching. The DVCD teaching quality can be improved to a new level by providing feedbacks to applications with the data on students’ needs for practical perception (PPN). However, the current practical perception and service applications rarely tackle the feature extraction and application of high-level needs for practical perception in the context of digital media. To solve the problem, this paper explores the practical perception and quality evaluation for DVCD teaching in the context of digital media. Specifically, the students’ PPN feature extraction problem was described in the field of DVCD teaching, and fuzzy clustering was introduced to extract students’ PPN features. Then, the authors detailed the dynamic evolution of students’ PPN in the context of digital media, and selected multiple layers of evaluation indices for DVCD teaching quality. Finally, the evolution drivers and patterns of students’ PPN were demonstrated, and the distribution of teaching quality scores was obtained through experiments.
Li et al. (Tue,) studied this question.