Introducing computational modeling into STEM classrooms can provide opportunities for the simultaneous learning of computational thinking (CT) and STEM. This paper describes the C2STEM modeling environment for learning physics, and the processes students can apply to their learning and modeling tasks. We use an unsupervised learning method to characterize student learning behaviors and how these behaviors relate to learning gains in STEM and CT.
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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.
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- Award ID(s):
- 1735909
- PAR ID:
- 10072963
- Date Published:
- Journal Name:
- Proceedings of International Conference on Computational Thinking Education 2018.
- Page Range / eLocation ID:
- 77-82
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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C2STEM is a web-based learning environment founded on a novel paradigm that combines block-structured, visual programming with the concept of domain specific modeling languages (DSMLs) to promote the synergistic learning of discipline-specific and computational thinking (CT) concepts and practices. Our design-based, collaborative learning environment aims to provide students in K-12 classrooms with immersive experiences in CT through computational modeling in realistic scenarios (e.g., building models of scientific phenomena). The goal is to increase student engagement and include inclusive opportunities for developing key computational skills needed for the 21st century workforce. Research implementations that include a semester-long high school physics classroom study have demonstrated the effectiveness of our approach in supporting synergistic learning of STEM and CS/CT concepts and practices, especially when compared to a traditional classroom approach. This technology demonstration will showcase our CS+X (X = physics, marine biology, or earth science) learning environment and associated curricula. Participants can engage in our design process and learn how to develop curricular modules that cover STEM and CS/CT concepts and practices. Our work is supported by an NSF STEM+C grant and involves a multi-institutional team comprising Vanderbilt University, SRI International, Looking Glass Ventures, Stanford University, Salem State University, and ETR. More information, including example computational modeling tasks, can be found at C2STEM.org.more » « less
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Synergistic learning of computational thinking (CT) and STEM has proven to effective in helping students develop better understanding of STEM topics, while simultaneously acquiring CT concepts and practices. With the ubiquity of computational devices and tools, advances in technology,and the globalization of product development, it is important for our students to not only develop multi-disciplinary skills acquired through such synergistic learning opportunities, but to also acquire key collaborative learning and problem-solving skills. In this paper, we describe the design and implementation of a collaborative learning-by-modeling environment developed for high school physics classrooms. We develop systematic rubrics and discuss the results of key evaluation schemes to analyze collaborative synergistic learning of physics and CT concepts and practices.more » « less
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Despite increasing attention to the potential benefits of infusing computational thinking into content area classrooms, more research is needed to examine how teachers integrate disciplinary content and CT as part of their pedagogical practices. This study traces how middle and high school teachers (n = 24) drew on their existing knowledge and their experiences in a STEM professional development program to infuse CT into their teaching. Our work is grounded in theories of TPACK and TPACK-CT, which leverage teachers’ knowledge of technology for computational thinking (CT), CT as a disciplinary pedagogical practice, and STEM content knowledge. Findings identify three key pedagogical supports that teachers utilized and transformed as they taught CT-infused lessons (articulating a key purpose for CT infusion, scaffolding, and collaborative contexts), as well as barriers that caused teachers to adapt or abandon their lessons. Implications include suggestions for future research on CT infusion into secondary classrooms, as well as broader recommendations to support teachers in applying STEM professional development content to classroom practice.more » « less
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