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Measuring Community College Students’ Self-efficacy Toward Circuit Analysis

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2015 ASEE Annual Conference & Exposition


Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015





Conference Session

Two-year College Division: Authors Address Transfer Matters-Part I

Tagged Division

Two Year College Division

Tagged Topic


Page Count


Page Numbers

26.1137.1 - 26.1137.12



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Paper Authors


Carl Whitesel Mesa Community College

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Carl Whitesel has spent his career teaching Engineering Technology, and has taught in the community college setting since 2007. He is currently teaching Robotics and Automated Systems within the Arizona Advanced Manufacturing Institute at Mesa Community College. His teaching focus is primarily on circuit analysis, electronics, motors and sensors. He earned his Ph.D. in Engineering Education - Curriculum and Instruction, from Arizona State University in 2014. His primary research interests are conceptual knowledge, concept inventories and self-efficacy.

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Adam R. Carberry Arizona State University Orcid 16x16

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Dr. Adam Carberry is an assistant professor at Arizona State University in the Fulton Schools of Engineering Polytechnic School. He earned a B.S. in Materials Science Engineering from Alfred University, and received his M.S. and Ph.D., both from Tufts University, in Chemistry and Engineering Education respectively. Dr. Carberry was previously an employee of the Tufts’ Center for Engineering Education & Outreach and manager of the Student Teacher Outreach Mentorship Program (STOMP).

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Measuring Community College Students’ Self-Efficacy toward Circuit AnalysisDC circuit analysis is considered a difficult course for engineering students. Research on thedifficulties students face regarding this topic focuses solely on 4-year university students,neglecting the population studying this topic within community colleges. Prior literature hasshown that community college students are different from university students, with one commonlink, self-efficacy. This is rooted in the fact that many strategies to increase student interest,achievement, retention and persistence in engineering are based on increasing self-efficacy.An instrument was created in the fall 2013 semester to measure the relationships between self-efficacy for DC circuit analysis and personal and academic characteristics. Study participantswere students enrolled in three engineering technology circuit analysis courses at a southwesterncommunity college. The instrument asked students questions related to their confidence in theiranswers to a concept inventory. Questions were worded as “How confident are you about youranswers given for parts 1 (multiple choice assessment of understanding) and 2 (writtendescription of understanding)?” Responses were reported using a 100-point range on a Likertscale with 10-unit intervals. Prompts were provided at 0 - “Not at all confident”, 40 - “Maybe-Not Sure”, 70 - “Pretty Confident”, and 100 - “Completely Confident”. This was consistent withprior approaches in the literature. Personal and academic characteristics were measured viademographic questions that had been found in the literature to be related to self-efficacy.The instrument was given as part of a pre- and post-test to a sample (N = 37) of the population ofstudents enrolled in three engineering technology circuit analysis courses. SAS statisticalanalysis software was used to analyze the data. Internal reliability of the instrument was checkedfor both the pre- and post-test, and was found to be excellent (α = 0.935). Face and contentvalidity were established via research on past studies that used this approach for domains outsideof circuit analysis. Construct validity was not established due to the low number of subjects andthe large number of characteristics measured. Group effects for the population from the threeseparate classes was analyzed using Analysis of Variance (ANOVA). No differences werepresent for the pre-test [F(2,36) = 0.50, p = 0.612] or the post-test [F(2,36) = 0.20, p = 0.817].Finally, the data set was analyzed for correlations between self-efficacy for circuit analysis andthe personal and academic characteristics of the subjects. Two characteristics on the post-testwere found to be significantly correlated with self-efficacy for circuit analysis. Subject’s agewas moderately and positively correlated (R = 0.43, p = 0.008), while subject’s father’seducation level was weakly and negatively correlated (R = -0.34, p = 0.042). These results areinteresting because they are not common in the literature for students enrolled in 4-yearinstitutions. The community college population being different from the university studentpopulation may indicate another difference between the two populations. Knowing thisdifference could potentially lead to better approaches for improving the self-efficacy ofcommunity college students enrolled in a course that is traditionally considered difficult.

Whitesel, C., & Carberry, A. R. (2015, June), Measuring Community College Students’ Self-efficacy Toward Circuit Analysis Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24474

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