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Collaborative Problem-solving Using a Cloud-based Infrastructure to Support High School STEM Education

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Conference

2015 ASEE Annual Conference & Exposition

Location

Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015

ISBN

978-0-692-50180-1

ISSN

2153-5965

Conference Session

Research to Practice: STRAND 1 – Addressing the NGSS: Supporting K-12 Teachers in Engineering Pedagogy and Engineering Science Connections (Part 2)

Tagged Division

K-12 & Pre-College Engineering

Page Count

21

Page Numbers

26.359.1 - 26.359.21

DOI

10.18260/p.23698

Permanent URL

https://peer.asee.org/23698

Download Count

683

Paper Authors

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Satabdi Basu Vanderbilt University, Institute for Software Integrataed Systems

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Satabdi Basu is a Ph.D. candidate in the Department of Electrical Engineering and Computer Science at Vanderbilt University. She has an undergraduate degree in Computer Science and Engineering from West Bengal University Of Technology, India, and a M.S. degree in Computer Science from Vanderbilt University. Her research interests include learning from multi-agent simulation models, computational thinking, scaffolding learning analytics and user modeling. She is currently a Research Assistant at the Institute for Software Integrated Systems and works on a NSF-funded project for teaching middle school students science and computational thinking simultaneously in curricular settings.

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John S Kinnebrew Vanderbilt University

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Shashank Shekhar Vanderbilt University

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Faruk Caglar

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Tazrian Haider Rafi Vanderbilt University

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Tazrian Haider Rafi is an undergraduate student studying computer science at Vanderbilt University.

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Gautam Biswas Vanderbilt University Orcid 16x16 orcid.org/0000-0002-2752-3878

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Gautam Biswas is a Professor of Computer Science, Computer Engineering, and Engineering Management in the EECS Department and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University. He has an undergraduate degree in Electrical Engineering from the Indian Institute of Technology (IIT) in Mumbai, India, and M.S. and Ph.D. degrees in Computer Science from Michigan State University in E. Lansing, MI.
Prof. Biswas conducts research in Intelligent Systems with primary interests in hybrid modeling, simulation, and analysis of complex embedded systems, and their applications to diagnosis, prognosis, and fault-adaptive control. He is also involved in developing simulation-based environments for learning and instruction. In his research, he has exploited the synergy between computational thinking ideas and STEM learning to develop systems that help students learn science and math concepts by building simulation models. He has also developed innovative educational data mining techniques for studying students’ learning behaviors and linking them to metacognitive strategies. Prof. Biswas is a Fellow of the IEEE.

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Aniruddha Gokhale Vanderbilt University

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Abstract

Collaborative Problem Solving using a Cloud-based Infrastructure to Support High School STEM Education (RTP, Strand 1)With the introduction of the next generation science standards into the high school curriculum,students are expected to employ critical thinking and problems-solving skills while engagingwith challenging STEM problems and concepts. To support STEM learning and development ofproblem-solving skills, we have developed a web- and server-based implementation of C3STEM– the Challenge-based Collaborative Community-center STEM learning environment. Thechallenges ground STEM instruction and learning in real-world applications to provide studentsboth a focus and a motivation for learning and problem solving. C3STEM uses transportation as areal-world domain to define STEM problems for students to solve. It also provides acollaborative environment for learning 21st century social and collaboration skills as studentswork together to decompose complex problems into parts and then combine partial solutions togenerate the best solution they can for the problem. The C3STEM system comprises two primarylearning environments: (1) the Computational Thinking through Simulation and Modeling(CTSiM) environment that allows students to build computational models of vehicles and trafficoperations using visual programming, and (2) the Cloud-based, Collaborative, Scaled-upModeling (C2SuMo) environment in which students apply the concepts they learned in CTSiM toscaled-up traffic flow problems, such as designing traffic light cycles to optimize traffic flow forlocal streets.We have extended our preliminary work on C3STEM in a number of ways: (1) enhanced andextended the basic simulation units in CTSiM, where students use fundamental knowledge ofphysics and math to develop models of vehicle movement and driver behavior; (2) redesignedthe C2SuMo environment to improve the accessibility of the interfaces for traffic simulationexperiments; and (3) introduced functionality for collaborative problem solving that allowsstudents to engage with C2SuMo while collaborating in a Google Hangout. We present resultsfrom two studies that included 62 Chattanooga, TN 11th- and 12th-grade students and 26 10th-grade students from a STEM outreach program in Nashville, TN. Our primary research questionsrevolved around: (1) assessing the usability of the CTSiM and C2SuMo components of thesystem; (2) establishing the extent to which students learned computational thinking (CT) skillsand STEM concepts in the problem domain; and (3) evaluating how the collaborativeenvironment supported students working together to derive solutions to problems.We study these three research questions using a variety of process (i.e., logged behavior in theenvironments), product (i.e., models and solutions created), interview, and pre-/post-test datagathered during the studies. Initial results indicate that the intervention helped improve students’understanding and ability to apply the relations among physics concepts like distance, velocity,and acceleration. In terms of computational skills, we find that students improved on theirunderstanding and usage of specific CT constructs, but still had problems with modeling somecomplex scenarios. For both science and CT learning, we observe a wide variation in students’performance and analyze potential relationships with other factors like prior knowledge andbehavior in the learning environments. Based on these results, we present specific lessonslearned and corresponding changes planned for improvement of the learning environments andcurriculum.

Basu, S., & Kinnebrew, J. S., & Shekhar, S., & Caglar, F., & Rafi, T. H., & Biswas, G., & Gokhale, A. (2015, June), Collaborative Problem-solving Using a Cloud-based Infrastructure to Support High School STEM Education Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23698

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