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ImageSTEAM

Product or Programme · All products and programmes
Evidence · 1 claim (1 for) · 1 study (1 causal), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

ImageSTEAM is a freely available computer-vision professional-development and curriculum programme in which teachers learn and implement no-code, browser-based computer-vision lessons using tools such as Teachable Machine, Pixlr, GauGAN, and Tinkercad.

Components

  • ImageSTEAM computer vision PD intervention using free online tools (pixlr, Teachable Machine, GauGAN, Tinkercad) with teachers co-creating and delivering lessons to middle school students: The intervention was a two-to-three-week professional development experience in which in-service middle school teachers from Title I schools learned computer vision technologies and then taught lessons to middle school students. Tools used were free, browser-based, and required no programming: "pixlr (an image editing software)", "Google's Teachable Machine (a tool which allows students to capture image or audio data, define a class for the data, and train a classification-based neural network)", NVIDIA's GauGAN, and Tinkercad, plus custom Google Colaboratory notebooks demonstrating vision algorithms. Curricular materials are freely available at https://www.imagesteam.org. (Kurz et al. (2026))

Claims

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Key Sources

  • Kurz, T. L., Jayasuriya, S., Swisher, K., Mativo, J., Pidaparti, R., & Robinson, D. T. (2026). Computer vision versus human vision: analyzing middle school teachers' construct restructuring following computer vision professional development. Education Tech Research Dev. https://doi.org/10.1007/s11423-026-10594-2
Page metadata
Field Value
type product
id imagesteam
title ImageSTEAM
description ImageSTEAM is a freely available computer-vision professional-development and curriculum programme in which teachers learn and implement no-code, browser-based computer-vision lessons using tools such as Teachable Machine, Pixlr, GauGAN, and Tinkercad.
status review
product_kind programme
generated by process:settle-candidates on 2026-10-28
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