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Developing an Assessment of Informal Data Science Learning: Two Cycles of Development, Implementation, and Revision

Fri, April 25, 11:40am to 1:10pm MDT (11:40am to 1:10pm MDT), The Colorado Convention Center, Floor: Meeting Room Level, Room 403

Abstract

Despite the increasing presence of data in youth’s lives, few quantitative assessments of data science skills exist—especially for informal learning environments. We report on the initial development of a data science assessment for middle school-aged learners within the context of a week-long, museum-based, community data science program. Our work is informed by H. Lee et al.’s (2022) framework on the steps and perspectives of data science work and V. Lee et al.’s (2021) humanistic data science and is methodologically guided by Wilson’s (2005, 2023) constructing measures approach. We share the construct maps and items for the areas of framing problems, considering & gathering data, and exploring & visualizing data that resulted from two cycles of development, implementation, and revision.

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