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A Study on Measuring Self-efficacy in Engineering Modeling and Design Courses

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

Electrical and Computer Division Technical Session 4

Tagged Division

Electrical and Computer

Page Count

13

Permanent URL

https://peer.asee.org/29730

Download Count

39

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Paper Authors

biography

Muhammad Safeer Khan Arkansas Tech University

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Muhammad Khan received Ph. D. degree in Electrical and Computer Engineering from the University of North Carolina at Charlotte, Charlotte, NC, USA in 2013. He is an Assistant Professor in the Department of Electrical Engineering at Arkansas Tech University (ATU). His research interests include signal processing for audio and acoustics, Wireless Communications, Internet of Things applications, non-destructive evaluation, engineering and integrated STEM education and K-12 and higher education collaboration. Dr. Khan is a faculty counselor for ATU IEEE Student Branch and is also Vice-Chair for IEEE Arkansas River Valley section. He is also active member of Arkansas Academy of Science and ASEE.

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biography

Nansong Wu Arkansas Tech University

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Nansong Wu received M.S. and Ph.D. degrees in Electrical and Computer Engineering from Florida International University, Miami, FL, USA, in 2008 and 2012. He is an assistant professor in the Department of Electrical Engineering, Arkansas Tech University. Previously, he was a faculty member in the Department of Electrical and Computer Engineering, Florida International University. His research interests include high-performance embedded systems, image processing, wireless communication, and IoT applications.

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Mohamed Ibrahim Arkansas Tech University

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Mohamed Ibrahim, PhD
Associate Professor of Curriculum and Instruction
College of Education
Arkansas Tech University
(479) 964-0583 ext. 2452

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Abstract

Preparing future engineers to model and design engineering systems is one of the primary objectives of engineering education. Rapid advances in technologies such as high performance computing, rapid prototyping through additive manufacturing, robotics, automation, nanotechnology and instrumentation have increased the complexity of engineering systems. The engineering design process involves knowledge of multiple domains of engineering and collaborative work among multi-disciplinary teams. The design process is also complicated by the safety, practicality and cost constraints. In light of these challenges, the engineering education needs to maintain its focus on principles of engineering design that can effectively prepare engineering graduates to meet the challenges posed by rapid technological growth in engineering and manufacturing technologies. The effectiveness of engineering education in modeling and design courses, traditionally, is measured through quizzes, exams and course projects that are aimed at measuring level of developed skills. For engineering students to be successful, it is not only essential that they possess required skills and competencies but should also have the belief that they will be able to perform with those skills. This self-belief in one's ability to perform assigned tasks for attainment of a specified objective has been described as "self-efficacy" construct in terms of Bandura's Social Cognitive Theory. An important research question is how to measure the developed self-confidence of engineering students in modeling and design courses. To address this question, present study proposes development of a self-efficacy measure. The proposed measure has been used to collect pre and post course data on self-efficacy through student surveys in engineering modeling and design courses at Arkansas Tech University. The collected data is being analyzed with Statistical Package for the Social Sciences (SPSS). The analysis involves computation of correlations and reliability coefficients, t-tests and analysis of variance (ANOVA). The results will enable researchers to plan and implement changes in curriculum or instructional delivery methods to achieve student learning outcomes.

Khan, M. S., & Wu, N., & Ibrahim, M. (2018, June), A Study on Measuring Self-efficacy in Engineering Modeling and Design Courses Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/29730

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