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This paper examines young students’ computational thinking (CT) practices in a humanoid-robotics programming environment. CT has been growing in importance and applicable to many science, math, and computer science settings, yet there is a lack of definitional consensus or agreement how to identify it in real time data despite research aiming to build consensus. From an open-ended grounded analysis of pair-interviews that were conducted with 5th graders whose classroom partook in a humanoid-robotics programming curriculum, we examine various CT practices. Results show that affordances of the environment and task influence which CT practices were most realized in this drag and drop environment, suggesting that these practices might also be most realized in similar programming environments.
Lauren Barth-Cohen, University of Utah
Shiyan Jiang, University of Miami
Ji Shen, University of Miami
Guanhua Chen, University of Miami
Moataz Eltoukhy, University of Miami