Treffer: Bridging Data and Art: Investigating Data-Art Connections in a Data-Art Inquiry Program.

The current data science education requires educators to provide more personally meaningful and culturally relevant data science learning experiences. By incorporating art production, we designed a data-art inquiry program to teach students data science basics and enable them to use art techniques to visualize their data. To understand how students established connections between data and art, we employed epistemic network analysis (ENA) at two levels to explore how they combine their data practices and art processes. Our study had three primary findings: (1) students have a personalized way of combining data and art; (2) data collection appears to be a key practice in our data-art inquiry program; (3) art production empowers students to better understand and communicate their data. In the future design of a data-art inquiry program, we suggest programming might (1) encourage students to explore personalized art formats to present their data, (2) emphasize the role of data collection, and (3) provide sufficient space and time for art processes to ensure the connections between data and artwork. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Science Education & Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)