Abstract

ABSTRACT As the fashion industry is becoming ever more data-driven, this study intends to understand whether the current fashion curriculums in U.S. education institutions have sufficiently introduced fashion majors to the topic of data science and prepared students for related skillsets. The results of MANOVA analysis based on course information collected from 45 fashion curriculums offered by leading U.S.-based fashion programmes show that: First, fashion programmes, in general, have incorporated some but very limited data science-related courses into the fashion curriculum. Second, school affiliation and programme type are two factors that have statistically significant impacts on fashion programmes’ adoption of data science-related courses to the curriculum. Third, the current fashion curriculums are too rigid to allow more data science components without adding additional credit burdens. The findings call for a more balanced fashion curriculum to develop students’ data science-related skillsets and suggest rethinking the future of fashion education in U.S. colleges.

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