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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
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Rick A. Hudson; Gemma F. Mojica; Hollylynne S. Lee; Stephanie Casey – Computers in the Schools, 2025
Innovative dynamic data tools afford opportunities for K-12 students and teachers to explore multivariate data and create linked data representations. These tools also support engagement in data moves, which are transnumerative actions to process, organize, and visualize data. The current study sought to understand how prospective K-12 mathematics…
Descriptors: Statistics Education, Visualization, Data Science, Preservice Teachers