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An Exploration of Course Design Heuristics Identified from Design Meetings, Design Artifacts, and Educator Interviews

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2019 ASEE Annual Conference & Exposition


Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

June 19, 2019

Conference Session

ERM Technical Session 22: Perspectives and Evaluation of Engineering Design Education

Tagged Division

Educational Research and Methods

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Paper Authors


Nicholas D. Fila Iowa State University

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Nicholas D. Fila is a postdoctoral research associate in Electrical and Computer Engineering and Industrial Design at Iowa State University. He earned a B.S. in Electrical Engineering and a M.S. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign and a Ph.D. in Engineering Education from Purdue University. His current research interests include innovation, empathy, engineering design, instructional design heuristics.

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Seda McKIlligan Iowa State University Orcid 16x16

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Dr. Seda McKilligan is an Associate Professor in the Department of Industrial Design at Iowa State University, in the United States. She has a B.I.D. in Industrial Design from METU in Turkey and an M.F.A. in Design and a Ph.D. in Design Science from the University of Michigan, in the US. Her current research on approaches in the design innovation process, ideation flexibility, investigations of problem-solution spaces, and concept generation and development practices of novices through practitioners is supported by multiple grants from the National Science Foundation. She produces theory, design principles and systems to support design, engineering and educational innovation processes, through studying experiences of individuals and teams that lead to innovative thinking and through integrating that knowledge into organizational change.

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This research paper investigates differences between course design heuristics that have been identified from three distinct data sources: course design team meetings, educator interviews, and course design papers. The study of heuristics used by experts in a discipline can have several practical benefits. They can (1) be employed as tools to scaffold expert behavior among novices, (2) be translated into processes to make challenging tasks more efficient, and (3) provide deeper insights into the nature of a domain, task, or discipline. While the study of heuristics remains robust across domains, they have demonstrated differences in format and have been identified through a variety of data types. The purpose of this study is to unpack differences in heuristics independently identified through different data types in order to better understand the role these types of data can play in understanding of heuristics for course design, especially as related to engineering courses.

We utilized thematic analysis to explore the patterns of differences between heuristics identified from the three settings in three related, but distinct studies. Datasets includes audio-recordings from a four-month team course redesign process, five approximately hour-long educator interviews, and 183 peer-reviewed course design papers.

We identified four themes representing differences across the datasets: (1) differences in volume/frequency of heuristics, (2) differences in breadth, specificity, and conceptualizations evidenced by categories of heuristics, (3) individual heuristic specificity, and (4) locus of clarity in heuristic examples. These results inform a set of four considerations for selecting data sources for studies of heuristics within engineering course design and other domains.

Fila, N. D., & McKIlligan, S. (2019, June), An Exploration of Course Design Heuristics Identified from Design Meetings, Design Artifacts, and Educator Interviews Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32060

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