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Title: A DSML for a Robotics Environment to Support Synergistic Learning of CT and Geometry. Kong, S. C., Sheldon, J., & Li, K. Y.. (Eds.). Conference
Synergistic learning of computational thinking (CT) and STEM has proven to be an effective method for enhancing CT education as well as advancing learning in many STEM domains. Domain Specific Modeling Languages (DSML) facilitate the building of computational modeling frameworks that are directly linked to STEM content, thus making it easier for students to focus on concepts and practices. At the same time, teachers can more easily relate curricular content to the model building tasks. This paper discusses the design, development, and implementation of a robotics DSML to support a middle school geometry curriculum.
Authors:
Award ID(s):
1735909
Publication Date:
NSF-PAR ID:
10072963
Journal Name:
Proceedings of International Conference on Computational Thinking Education 2018.
Page Range or eLocation-ID:
77-82
Sponsoring Org:
National Science Foundation
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