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The Interplay Between Engineering Students' Modeling and Simulation Practices and Their Use of External Representations: An Exploratory Study

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Conference

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

Classroom Practice III: Student-Centered Instruction

Tagged Division

Educational Research and Methods

Page Count

14

DOI

10.18260/p.26200

Permanent URL

https://strategy.asee.org/26200

Download Count

189

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Paper Authors

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Hayden Fennell Purdue University Polytechnic Institute Orcid 16x16 orcid.org/0000-0003-3730-3235

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Hayden Fennell is a Ph.D. student in the department of Computer and Information Technology at Purdue University. He holds an M.S.E. degree in Materials Science and Engineering from Johns Hopkins University and a B.S. in Mechanical Engineering from the University of South Carolina.

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Camilo Vieira Purdue University Orcid 16x16 orcid.org/0000-0001-8720-0002

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PhD Candidate at Purdue University
Master of Engineering in Educational Technologies - Eafit University
Systems Engineer - Eafit University

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Genisson Silva Coutinho Instituto Federal de Educação, Ciência e Tecnologia da Bahia

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Genisson Silva Coutinho is a Ph.D. student at the School of Engineering Education at Purdue University. He is a CAPES grantee and also professor in the Department of Mechanical and Materials Technology at the Instituto Federal de Educação, Ciência e Tecnologia da Bahia. He is a mechanical engineer and holds a Bachelor's degree in law and a Master's degree in mechanical engineering. He has been teaching at different levels, from the first year of technical high school to the final year of mechatronic engineering course, since 1995. He also has considerable experience in the design and implementation of mechatronic and production engineering courses. His non-academic career is centered on product development and manufacturing processes.

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Alejandra J. Magana Purdue University, West Lafayette Orcid 16x16 orcid.org/0000-0001-6117-7502

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Alejandra Magana is an Associate Professor in the Department of Computer and Information Technology and an affiliated faculty at the School of Engineering Education at Purdue University. She holds a B.E. in Information Systems, a M.S. in Technology, both from Tec de Monterrey; and a M.S. in Educational Technology and a Ph.D. in Engineering Education from Purdue University. Her research is focused on identifying how model-based cognition in STEM can be better supported by means of expert technological and computing tools such as cyberinfrastructure, cyber-physical systems, and computational modeling and simulation tools.

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R. Edwin García Purdue University, West Lafayette

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Prof. R. Edwin García is an Associate Professor of Materials Engineering at the School of Materials Engineering at Purdue University (2011-present). He earned the Physics degree at the National University of Mexico in 1996, and his Ph.D. in Materials Science and Engineering at the Massachusetts Institute of Technology in 2003. His research group focuses on the design of materials and devices through the development of a fundamental understanding of the solid state physics of the individual phases, their short and long range interactions, and its associated microstructural properties and time evolution.

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Abstract

The Interplay between Engineering Students Modeling and Simulation Practices and their use of External Representations: An Exploratory Study (Research)

Background and Motivation Advances in computing and information technology contribute to science and engineering discovery, innovation, and education by facilitating the processing, storage, analyses, simulation, and visualization of unprecedented amounts of experimental and observational data. These advancements have resulted in computational tools that allow us to address complex problems that affect health, energy, the environment, security, and overall quality of life. Future scientists and engineers need to be prepared to exploit them to generate effective knowledge and solutions to human challenges. Thus, the ability to use and create modern engineering tools derived from or validated with experimental data is required to support engineering design and problem solving to contribute to and to compete in our fast-changing and global society. This study explores how students engage in experimentation strategies and how they combine those strategies with the modeling and simulation process. Specifically, this study will identify how students model phenomena and solve a design problem, starting from experimental data. The research questions are: how do students experience modeling and simulation practices in the context of rechargeable battery systems? How do students’ implementations of the modeling and simulation process relate to the quality of their battery system design? How do students use external representations in each step of the modeling and simulation process?

Methods This exploratory study consists of a quantitative component and a qualitative component. Participants of this study include 40 undergraduate and graduate students from a materials science course at a Midwestern University. These students were engaged in experimentation and modeling practices in the context of rechargeable batteries. The course consists of a theoretical component and a practical component. In the theoretical component students learn about basic electrochemistry theory, principles of electrochemical devices, and electroactive materials as used in rechargeable battery systems. The practical component provides fundamental analytical and computational modeling techniques used by the battery industry by teaching the practical aspects of battery fabrication. The procedures of the study were embedded in the practical component of the course, where as part of a final project, students modeled and analyzed a graded porous electrode to be used as part of a rechargeable battery system. The submitted individual course assignments served as the raw data used to examine students’ modeling and simulation practices. The quantitative component of the study consists of identifying students’ abilities in implementing the steps of the modeling and simulation process and proposing a feasible solution to the design challenge. To this end, we developed a rubric based on Shiflet and Shiflet (2004) description of the modeling and simulation process (see Table 1 for a description of the process). The qualitative component consists of a recorded think-aloud protocol with three students who will describe how they approached each of the stages of the modeling and simulation process. Data analysis will consists of a verbal protocol analysis that will explicitly identify when and how often students use external representations in each of the steps of the modeling and simulation process.

Results To approach our qualitative and quantitative analysis we have developed a coding scheme that will allow us to describe and quantify how students engaged with modeling and simulation practices. Our framework is an adaptation from Shiflet and Shiflet (2014, pp. 9-11). Results of the quantitative component will report descriptive statistics of scores assigned to students’ implementation of each step of the modeling and simulation process. This analysis will be performed on the total sample of the 40 students. We will also perform a correlation analysis to identify the relationship between students’ performance in each step. Finally, we will report on characteristics of students’ implementation of the modeling and simulation process, and compare those to the quality of their design solutions. Results of the qualitative component will include descriptions of the types and frequency of use of external representations. This analysis will be performed with a sample of three students who will participate in the think-aloud procedure. The verbal protocol analysis will start by first identifying the enacted modeling and simulation step using the coding scheme from Shiflet and Shiflet. Then, in a second iteration we will identify how students used external representations in each stage. For that end, a second coding scheme developed by Cardella Atman and Adams (2006), will be adapted and implemented.

Conclusion and Implications This study is relevant because the use of external representations has been identified as central to the practices of engineering. Specifically, this study will identify how external representations and representational processes are used as part of the modeling and simulation process allowing individuals to gain insight into the material world by representing it through diagrams, graphs, algorithms, computer simulations, and so on. The implications of this study lay a foundation of future research of graphical representations in engineering and will provide in-depth details of how learners use multiple forms of representations and tools during the modeling and simulation process. Implications of this study also relate to the development of learning materials, scaffolding methods and pedagogical approaches that can guide the design and integration of expert practices and computational tools into the undergraduate curricula.

Fennell, H., & Vieira, C., & Coutinho, G. S., & Magana, A. J., & García, R. E. (2016, June), The Interplay Between Engineering Students' Modeling and Simulation Practices and Their Use of External Representations: An Exploratory Study Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.26200

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