skip to main content

Title: Examining Synergistic Learning of Physics and Computational Thinking through Collaborative Problem Solving in Computational Modeling
Computational modeling has been shown to benefit integrated learning of science and computational thinking (CT), however the mechanics of this synergistic learning are not well understood. In this research, we examine discourse during collaborative computational model building through the lens of a collaborative problem solving framework to gain insights into collaboration and synergistic learning of high school physics and CT. We pilot our novel approach in the context of C2STEM, a designed modeling environment, and examine collaboration and synergistic learning episodes in a video capture of a dyad modeling 2D motion with constant velocities. Our findings exhibit the promise of our approach and lay the foundation for guiding future automated approaches to detecting the synergistic learning of science and CT.
; ; ; ;
Award ID(s):
Publication Date:
Journal Name:
Annual Meeting of the American Education Research Association
Sponsoring Org:
National Science Foundation
More Like this
  1. 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 classroommore »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« less
  2. 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 resultsmore »of key evaluation schemes to analyze collaborative synergistic learning of physics and CT concepts and practices.« less
  3. The introduction of computational modeling into science curricula has been shown to benefit students’ learning, however the synergistic learning processes that contribute to these benefits are not fully understood. We study students’ synergistic learning of physics and computational thinking (CT) through their actions and collaborative discourse as they develop computational models in a visual block-structured environment. We adopt a case study approach to analyze students synergistic learning processes related to stopping conditions, initialization, and debugging episodes. Our findings show a pattern of evolving sophistication in synergistic reasoning for model-building activities.
  4. Engaging students in science learning that integrates disciplinary knowledge and practices such as computational thinking (CT) is a challenge that may represent unfamiliar territory for many teachers. CompHydro Baltimore is a collaborative partnership aimed at enacting Next Generation Science Standards (NGSS)–aligned instruction to support students in developing knowledge and practice reflective of the goals laid out in A Framework for K–12 Science Education (National Research Council 2012) “... that by the end of 12th grade, all students possess sufficient knowledge of science and engineering to engage in public discussion on related issues … and are careful consumers of scientific andmore »technological information related to their everyday lives.” This article presents the results of a partnership that generated a new high school level curriculum and teacher professional development program that tackled the challenge of integrating hydrologic learning with computational thinking as applied to a real-world issue of flooding. CompHydro Baltimore produced Baltimore Floods, a six-lesson high school unit that builds students’ water literacy by engaging them in computational thinking (CT) and modeling practices as they learn about water system processes involved in urban flooding (See Computational Thinking and Associated Science Practices). CompHydro demonstrates that broad partnerships can address these challenges, bringing together the diverse expertise necessary to develop innovative CT-infused science curriculum materials and the teacher supports needed for successful implementation.« less
  5. There is increasing interest in broadening participation in computational thinking (CT) by integrating CT into pre-college STEM curricula and instruction. Science, in particular, is emerging as an important discipline to support integrated learning. This highlights the need for carefully designed assessments targeting the integration of science and CT to help teachers and researchers gauge students’ proficiency with integrating the disciplines. We describe a principled design process to develop assessment tasks and rubrics that integrate concepts and practices across science, CT, and computational modeling. We conducted a pilot study with 10 high school students who responded to integrative assessment tasks asmore »part of a physics-based computational modeling unit. Our findings indicate that the tasks and rubrics successfully elicit both Physics and CT constructs while distinguishing important aspects of proficiency related to the two disciplines. This work illustrates the promise of using such assessments formatively in integrated STEM and computing learning contexts.« less