Council for At Risk Student Education and Professional Standards

• In Event: Council for At Risk Student Education and Professional Standards

Short Description

In this study, we developed a deep learning-based art learning support tool to improve art expression ability in elementary school art classes based on the analysis of educational needs. The prototype was revised and supplemented through two rounds of expert validation and usability testing, and the improved prototype was tested in elementary school art classes. Afterwards, we confirmed the applicability of the prototype using a questionnaire and interview with the learners.

Authors

• Contributor: Unggi Lee, Seoul National University

• Contributor: SangHee Kang, Seoul National University

• Contributor: Jongchan Lee, Seoul National University

• Contributor: Seoyeon Choi, Seoul National University

• Contributor: Ukmyung Choi, Seoul National University

• Presenter: Cheolil Lim, Seoul National University