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Assessing an Adaptive Expertise Instrument in Computer-aided Design (CAD) Courses at Two Campuses

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Collection

2012 ASEE Annual Conference & Exposition

Location

San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012

ISSN

2153-5965

Conference Session

NSF Grantees' Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

18

Page Numbers

25.212.1 - 25.212.18

Permanent URL

https://peer.asee.org/20972

Download Count

14

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Paper Authors

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Michael Johnson Texas A&M University Orcid 16x16 orcid.org/0000-0001-5328-8763

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Michael D. Johnson is an Assistant Professor in the Department of Engineering Technology and Industrial Distribution at Texas A&M University. Prior to joining the faculty at Texas A&M, he was a senior product development engineer at the 3M Corporate Research Laboratory in St. Paul, Minn. He received his B.S. in mechanical engineering from Michigan State University and his M.S. and Ph.D. from the Massachusetts Institute of Technology. Johnson’s research focuses on design tools; specifically, the cost modeling and analysis of product development and manufacturing systems; computer-aided design methodology; and engineering education. His work has been published in the International Journal of Production Economics, IEEE Transactions on Engineering Management, and the Journal of Engineering Design.

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Elif Ozturk Texas A&M University

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Joshua Johnson Prairie View A&M University

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Bugrahan Yalvac Texas A&M University

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Bugrahan Yalvac is an Assistant Professor of science education in the Department of Teaching, Learning, and Culture at Texas A&M University, College Station. He received his Ph.D. in science education at the Pennsylvania State University in 2005. Prior to his current position, he worked as a learning scientist for the VaNTH Engineering Research Center at Northwestern University for three years. Yalvac’s research is in STEM education, 21st century skills, and design and evaluation of learning environments informed by the How People Learn framework.

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Xiaobo Peng Prairie View A&M University

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Xiaobo Peng is an Associate Professor in the Department of Mechanical Engineering at Prairie
View A&M University.

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Abstract

Assessing an Adaptive Expertise Instrument in Computer-aided Design (CAD) Courses at Two CampusesIn today’s highly competitive market, CAD tools are widely used and thought to reduce time tomarket and increase engineering productivity. However, to take advantage of these putativebenefits requires proper use of CAD tools. Merely teaching declarative knowledge (particularkeystrokes and button picks) in CAD is not sufficient; students should acquire deeper proceduralknowledge (design strategy) in CAD. This will allow them to gain a level of expertise that isadaptive in nature. Recent research in engineering education finds that experts demonstrate twodistinct characteristics: adaptive versus routine expertise. Adaptive experts possess the contentknowledge similar to routine experts in the field, but also the ability to effectively utilize andextend their content knowledge. Epistemological beliefs, metacognitive skills, multipleperspectives, and learning orientations are among the constructs that can define adaptiveexpertise.This work will describe the implementation of an instrument used to measure adaptive expertisein two courses at two universities. The instrument contains questions covering four dimensions:multiple perspectives, meta-cognitive self-assessment, goals and beliefs, and epistemology. Inone university setting, freshmen engineering students will be surveyed with the instrument; in theother junior level engineering students will be surveyed. In addition to the student participants,practicing engineers from industry will be surveyed using the instrument. Participantdemographic, education, and engineering experience data will also be collected. These data willbe used to examine the relationships among expertise related responses and demographicvariables. We anticipate finding differences between students’ and practicing engineers’responses as well as differences among each group’s demographic characteristics and theiroverall scores for each of the four dimensions cited above.

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