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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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Carrie Wright; Qier Meng; Michael R. Breshock; Lyla Atta; Margaret A. Taub; Leah R. Jager; John Muschelli; Stephanie C. Hicks – Journal of Statistics and Data Science Education, 2024
With unprecedented and growing interest in data science education, there are limited educator materials that provide meaningful opportunities for learners to practice "statistical thinking," as defined by Wild and Pfannkuch, with messy data addressing real-world challenges. As a solution, Nolan and Speed advocated for bringing…
Descriptors: Statistics, Statistics Education, Open Educational Resources, Case Method (Teaching Technique)
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Reza Moeti; Abolfazl Rafiepour; Mohammad Reza Fadaee – Mathematics Teaching Research Journal, 2024
Despite the increasing interest in data science education in the world, its teaching is not included in the curricula (junior secondary) and there is little information about it. Google Trends is discussed as a tool and database in school data science. Also, in different subjects, students were able to create and interpret graphs using this tool.…
Descriptors: Foreign Countries, Data Science, Statistics Education, Middle School Students