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Tiffany Tseng; Matt J. Davidson; Luis Morales-Navarro; Jennifer King Chen; Victoria Delaney; Mark Leibowitz; Jazbo Beason; R. Benjamin Shapiro – ACM Transactions on Computing Education, 2024
Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML systems requires significant considerations around how to design representative datasets. Yet, few novice-oriented ML modeling tools are designed to foster hands-on learning of dataset design practices, including how to design for data diversity and inspect…
Descriptors: Artificial Intelligence, Models, Data Processing, Design
Ismaila Temitayo Sanusi; Fred Martin; Ruizhe Ma; Joseph E. Gonzales; Vaishali Mahipal; Solomon Sunday Oyelere; Jarkko Suhonen; Markku Tukiainen – ACM Transactions on Computing Education, 2024
As initiatives on AI education in K-12 learning contexts continues to evolve, researchers have developed curricula among other resources to promote AI across grade levels. Yet, there is a need for more effort regarding curriculum, tools, and pedagogy, as well as assessment techniques to popularize AI at the middle school level. Drawing on prior…
Descriptors: Artificial Intelligence, Middle School Students, Learner Engagement, Technology Uses in Education
Jennifer Kahn; Shiyan Jiang – Information and Learning Sciences, 2024
Purpose: While designing personally meaningful activities with data technologies can support the development of data literacies, this paper aims to focuses on the overlooked aspect of how learners navigate tensions between personal experiences and data trends. Design/methodology/approach: The authors report on an analysis of three student cases…
Descriptors: Visual Aids, Trend Analysis, Data Science, Secondary School Students