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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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Marijel Melo; Laura March; Kimberly Hirsh; Emily Arnsberg – TechTrends: Linking Research and Practice to Improve Learning, 2024
To better grasp the issue of underrepresentation in makerspaces, it's crucial to closely examine the environment where these problems arise. A spatial enumeration of a makerspace, which is a complete listing of items within a collection or environment, extends such an evaluation. By responding to this overarching research question, "why do…
Descriptors: Technology, Shared Resources and Services, Minority Group Students, Perception
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Branko Andic; Andrej Sorgo; Robert Weinhandl; Mirjana Maricic; Zsolt Lavicza – TechTrends: Linking Research and Practice to Improve Learning, 2024
Despite numerous studies indicating the positive contribution of 3D modeling and printing (3DMP) in learning settings, its current educational use is still rather limited. For the adoption of 3DMP in classrooms, it is critical to understand the views and perceptions of teachers on such new technology. To better understand how teachers perceive…
Descriptors: Secondary School Teachers, Printing, Foreign Countries, Shared Resources and Services