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SeHee Jung; Hanwen Wang; Bingyi Su; Lu Lu; Liwei Qing; Xiaolei Fang; Xu Xu – TechTrends: Linking Research and Practice to Improve Learning, 2025
This study presents a mobile application (app) that facilitates undergraduate students to learn data science using their own full-body motion data. The app captures a user's movements through the built-in camera of a mobile device and processes the images for data generation using BlazePose, an open-source computer vision model for real-time pose…
Descriptors: Undergraduate Students, Data Science, Handheld Devices, Open Source Technology
Danielle Herro; Golnaz Arastoopour Irgens; Jeremiah Akhigbe; McKenzie Martin Rowland – Journal of Digital Learning in Teacher Education, 2025
Preparing elementary-aged children to practice data science literacies is important and understudied. Our research investigates how data science curricula might be effectively designed and integrated into elementary classroom instruction. We use narrative case study methodology, focusing on a single case detailing a second-grade teacher's approach…
Descriptors: Data Science, Computer Games, Handheld Devices, Grade 2