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Board 77: Visual Representations Guide Students’ Use of Conceptual Knowledge and Problem-solving Strategies

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2019 ASEE Annual Conference & Exposition


Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

October 19, 2019

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

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Paper Authors


Nicole Johnson-Glauch California Polytechnic State University

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Dr. Nicole Johnson-Glauch is a lecturer in the Materials Engineering Department at California Polytechnic State University in San Luis Obiso, California. Her current research interests are in how visual representations help or hinder student learning and how the structure of outreach activities impact underrepresented students' interest and belonging in engineering.

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Geoffrey L. Herman University of Illinois, Urbana-Champaign Orcid 16x16

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Dr. Geoffrey L. Herman is a teaching assistant professor with the Deprartment of Computer Science at the University of Illinois at Urbana-Champaign. He also has a courtesy appointment as a research assistant professor with the Department of Curriculum & Instruction. He earned his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign as a Mavis Future Faculty Fellow and conducted postdoctoral research with Ruth Streveler in the School of Engineering Education at Purdue University. His research interests include creating systems for sustainable improvement in engineering education, conceptual change and development in engineering students, and change in faculty beliefs about teaching and learning. He serves as the Publications Chair for the ASEE Educational Research and Methods Division.

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By graduation, engineering students are expected to learn engineering concepts from and solve problems with several types of visual representations (e.g., free-body diagrams, graphs, or schematics). Prior studies in engineering education have shown that students struggle to do both. Researchers in cognitive science suggest that learning from representations is an iterative process that depends on students’ prior knowledge, their goals, and what the features in a representation look like. However, these studies have not yet studied situations in which students modify the initial representation or handle multiple representations during a problem-solving task. Additionally, while researchers have studied what types of representations give better performance, less is known about why students perform better with certain types of representations. Under this NSF-EEC grant, we filled this gap in the literature by investigating the interplay between features that students notice in a representation, how they express their conceptual knowledge and the way they approach solving problems. We studied this interplay by conducting think-aloud interviews with students from two courses that represent two engineering disciplines that use multiple visual representations: statics and digital logic. We analyzed these interviews using the constant comparative method, which resulted in three emergent themes that describe ways that features of representations potentially hinder students’ ability to learn and use engineering concepts. Two of these were present in both datasets while one was only present in the statics dataset. We expanded upon this work by conducting a classroom intervention in the university’s large-enrollment statics course to test the generalizability of our findings. This paper will highlight the major findings from the cross-disciplinary analysis and discuss future research directions.

Johnson-Glauch, N., & Herman, G. L. (2019, June), Board 77: Visual Representations Guide Students’ Use of Conceptual Knowledge and Problem-solving Strategies Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32426

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