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A Collaborative K-12 STEM Education Framework Using Traffic Flow as a Real-world Challenge Problem

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2014 ASEE Annual Conference & Exposition


Indianapolis, Indiana

Publication Date

June 15, 2014

Start Date

June 15, 2014

End Date

June 18, 2014



Conference Session

K-12 and Pre-College Engineering Division Poster Session

Tagged Division

K-12 & Pre-College Engineering

Page Count


Page Numbers

24.28.1 - 24.28.9

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Paper Authors

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Shashank Shekhar Vanderbilt University

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Faruk Caglar Vanderbilt University

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Anton Dukeman Vanderbilt University

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Liyan Hou


Aniruddha Gokhale Vanderbilt University

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Aniruddha Gokhale is an Associate Professor of Computer Science and Engineering in the Dept of Electrical Engineering and Computer Science at Vanderbilt University, Nashville, TN, USA. Prof. Gokhale got his BE (Computer Engineering) from Pune University, Pune, India in 1989; MS (Computer Science) from Arizona State University, Tempe, AZ in 1992; and PhD (Computer Science) from Washington University in St. Louis, St. Louis, MO in 1998. Prior to his current position at Vanderbilt University, he was a Member of Technical Staff at Lucent Bell Labs. He is a Senior Member of both the IEEE and ACM.His research interests are in solving distributed systems challenges for real-time and embedded systems through effective software engineering principles and algorithm development. He is applying these expertise to develop an effective, cloud-based and ubiquitous infrastructure for scalable, collaborative STEM education.

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John S. Kinnebrew Vanderbilt University


Gautam Biswas Vanderbilt University

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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. As part of this work, he has worked on fault diagnosis and fault-adaptive control of secondary sodium cooling systems for nuclear reactors, automobile engine coolant systems, fuel transfer systems for aircraft, Advanced Life Support systems and power distribution systems for NASA. He has also initiated new projects in health management of complex systems, which includes online algorithms for distributed monitoring, diagnosis, and prognosis. More recently, he is working on data mining for diagnosis, and developing methods that combine model-based and data-driven approaches for diagnostic and prognostic reasoning. This work, in conjunction with Honeywell Technical Center and NASA Ames, includes developing sophisticated data mining algorithms for extracting causal relations amongst variables and parameters in a system. For this work, he recently received the NASA 2011 Aeronautics Research Mission Directorate Technology and Innovation Group Award for Vehicle Level Reasoning System and Data Mining methods to improve aircraft diagnostic and prognostic systems.

In other research projects, he is involved in developing simulation-based environments for learning and instruction. The most notable project in this area is the Teachable Agents project, where students learn science by building causal models of natural processes. More recently, 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. His research has been supported by funding from NASA, NSF, DARPA, and the US Department of Education. His industrial collaborators include Airbus, Honeywell Technical Center, and Boeing Research and Development. He has published extensively, and has over 300 refereed publications.

Dr. Biswas is an associate editor of the IEEE Transactions on Systems, Man, and Cybernetics, Prognostics and Health Management, and Educational Technology and Society journal. He has served on the Program Committee of a number of conferences, and most recently was Program co-chair for the 18th International Workshop on Principles of Diagnosis and Program co-chair for the 15th International Conference on Artificial Intelligence in Education. He is currently serving on the Executive committee of the Asia Pacific Society for Computers in Education and is the IEEE Computer Society representative to the Transactions on Learning Technologies steering committee. He is also serving as the Secretary/Treasurer for ACM Sigart. He is a senior member of the IEEE Computer Society, ACM, AAAI, and the Sigma Xi Research Society.

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An Evaluation of a Collaborative STEM Education Framework for High and Middle School Students (Research-to-practice studies)Effective STEM education needs teaching tools that promote critical thinking and modalities toput learning in the context of real world problems. This is further emphasized in the nextgeneration science standards (NGSS) for high school engineering that expects students to engagewith the global issues at the interface of science, technology, society and environment( ). Study of traffic patterns is one such real world problemdomain to stimulate student interest in STEM. However, existing tools for modeling and analysisof traffic systems are too complex for high-school and middle-school students.To scaffold students’ analysis of traffic problems, we have developed a suite of intuitive, easy-to-use and grade-appropriate tools used in two stages that provide input and output interfaces tomore complex traffic simulation systems. First, agent-based simulations are used by studentsindividually to help them understand and model the dynamics of traffic flows in terms of physicsand mathematical models. Second, a collaborative tool available on ubiquitous user devices, suchas tablets, is used to apply the concepts learned in the first stage, and solve traffic flow problemsboth individually and collaboratively on a traffic simulator. The complexities of the simulator arehidden from the students by hosting it in the cloud. Instead, the intuitive Google maps serve asthe input interface that renders traffic dynamics from the simulator, and allows students to set upparameters for running a variety of traffic simulation scenarios. The output interfaces includeplot routines to support interpretation and analysis of the simulation results.An initial prototype of the system was evaluated by introducing it to two groups of students withone group of seven 10th and 11th graders who were pursuing an Engineering track in their highschool, and a second group of nine middle school students, who were attending a sciencesummer camp. The students first used the agent-based modeling environment to build models ofvehicle movement through STOP signs and intersections using their knowledge of physics(Newton’s laws) and mathematics (elementary calculus). In the next step, they continued to workindividually with the collaborative tool working on problems to minimize waiting time andqueue length, and to maximize traffic flow by experimenting with ranges of vehicle parameters,vehicle turn ratios and traffic signal timing. Next, they worked collaboratively in groups todetermine traffic signal logic to optimize traffic flow through multiple intersections.The results of our initial experiments are encouraging and demonstrate the flexibility of theframework to cater to both high school and middle school students. Although some of the highschool students lacked important physics knowledge, with some initial scaffolding they wereable to understand and apply the fundamental concepts. The students successfully solved thegiven problems using a combination of STEM and computational thinking concepts. Based onfeedback we have received, we are enhancing the tool capabilities for use in a STEM curriculumat two high schools in Spring 2014.

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