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Developing An Instrument To Measure Engineering Design Self Efficacy

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2009 Annual Conference & Exposition


Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009



Conference Session

Measurement Tools

Tagged Division

Educational Research and Methods

Page Count


Page Numbers

14.450.1 - 14.450.14

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Paper Authors


Adam Carberry Tufts University

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Adam Carberry is a doctoral student in the Math, Science, Technology, and Engineering Education program at Tufts University. He serves as a research assistant and director of the Student Teacher Outreach Mentorship Program (STOMP) at the Tufts University Center for Engineering Education & Outreach. His dissertation research involves the development of assessment instruments for investigating the impact of service-learning on engineering students.

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Matthew Ohland Purdue University Orcid 16x16

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Matthew W. Ohland is an Associate Professor in the School of Engineering Education at Purdue University and is the Past President of Tau Beta Pi, the engineering honor society. He received his Ph.D. in Civil Engineering from the University of Florida in 1996. Previously, he served as Assistant Director of the NSF-sponsored SUCCEED Engineering Education Coalition. He studies longitudinal student records in engineering education, team-member effectiveness, and the implementation of high-engagement teaching methods.

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Hee-Sun Lee Tufts University

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Hee-Sun Lee is an assistant professor in the Math, Science, Technology, and Engineering Program of the Education Department at Tufts University. She earned her Ph.D. in science education from the University of Michigan. Her research interests include research and development of science curriculum, technology, and assessment that can help middle and high school students develop an integrated understanding across topics and disciplines over time.

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Developing an Instrument to Measure Engineering Design Self-Efficacy: A Pilot Study

Keywords: self-efficacy, engineering design


The following pilot study is an investigation of how to develop an instrument that measures students’ self-efficacy regarding engineering design. 36 items were developed and tested using three types of validity evidence. First, the content of the instrument was tested to ensure that the full domain (each subdimension) of the engineering design process was represented. Second, the instrument was tested for whether responses to the instrument could identify groups with various levels of engineering design experience. Finally, theoretical connections between motivation, expectancy for success, and anxiety were tested to determine their appropriateness in the measurement of self-efficacy. Results confirmed an accurate reading of engineering design self-efficacy for 82 volunteer respondents with diverse engineering expertise.


Self-efficacy is a motivational construct regarding an individual’s belief or judgment in their capability to organize and execute courses of action for a given domain-specific task.[1, 2] An individual’s self-efficacy plays a crucial role in their ability to conduct a particular task; however, self-efficacy toward engineering concepts is rarely analyzed. Information about engineering student levels of self- efficacy on engineering tasks can be useful for educators to plan and structure engineering courses.

The following paper describes an exploratory pilot study conducted to inform the development of an instrument designed to identify self-efficacy toward engineering design. Engineering design, or the process used to devise a system, component, or process to meet a desired need, was chosen as the focus because of its importance in the field of engineering.[3]

Instrument development was guided by three questions:

1. How should the engineering design domain be represented? 2. Does the instrument predict differences in self-efficacy held by subjects with a range of engineering experience? 3. Does the instrument predict relationships among constructs adopted in this study?

These questions are explored through three forms of validity evidence [4]: content, criterion-related, and construct. The paper begins by defining each validity type to establish the necessity for each validation step. Previous research in the realm of


Carberry, A., & Ohland, M., & Lee, H. (2009, June), Developing An Instrument To Measure Engineering Design Self Efficacy Paper presented at 2009 Annual Conference & Exposition, Austin, Texas.

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