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Title: Supporting Multidimensional Data Analysis for High-School Students in the Era of Machine Learning
Machine Learning (ML) opens exciting scientific opportunities in K-12 STEM classrooms. However, students struggle with interpreting ML patterns due to limited data literacy. Face glyphs offer unique benefit by leveraging our brain’s facial feature processing. Yet, they have limitations like lacking contextual information and data biases. To address this, we created three enhanced face glyph visualizations: feature-independent and feature-aligned range views, and the sequential feature inspector. In a study with 25 high school students, feature-aligned range visualization helped contextual analysis, and the sequential feature inspector reduced missing data risks. Face glyphs also benefit the global interpretation of data.  more » « less
Award ID(s):
2225227
PAR ID:
10519137
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
International Society of the Learning Sciences
Date Published:
Page Range / eLocation ID:
1255 to 1258
Format(s):
Medium: X
Location:
Buffalo, New York
Sponsoring Org:
National Science Foundation
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