Atlanta, Georgia
June 23, 2013
June 23, 2013
June 26, 2013
2153-5965
Educational Research and Methods
17
23.1284.1 - 23.1284.17
10.18260/1-2--22669
https://peer.asee.org/22669
1304
Philip Brown is a Ph.D. candidate in Virginia Tech's Department of Engineering Education. He has a B.S. from Union College and a M.S. from Duke University, both in Electrical Engineering. His research interests include informed career decisions, mixed methods research, motivation and learning theories and intervention development.
Unlocking Student Motivation: Development of an Engineering Motivation SurveyStudent motivation is an important part of student’s engagement in learning. Researchers andeducators across broad educational contexts have identified and investigated a variety of specificmotivation-related constructs related to learning. However, few studies have developed andtested survey instruments for measuring motivation constructs within engineering education ina valid and reliable way. Specifically, a single instrument survey measuring all of the the taskvalues and expectancy of success from Expectancy-Value theory in engineering students doesnot exist. Such an instrument could aid future studies in concisely measuring these constructs inengineering student populations. This study describes the development and piloting of such a survey through numeroussteps of validity and reliability testing. The survey items consist of 35 Likert scale questionsmeasuring attainment value, interest-enjoyment value, utility value, cost and expectation ofsuccess for students obtaining a degree in engineering. Initial development of the survey wasbased on previously published instruments measuring expectancy-value constructs, as well asconsultation with two experts on motivation research and one expert on survey development.Further validity was reached via interviews with research peers and focus groups of engineeringundergraduates. The survey was piloted with 219 engineering students at a large public university locatedin the mid-Atlantic United States. To determine if items were appropriately loading on factors,Factor analysis was performed on survey responses using principal axis factoring. This methodwas chosen due to its applicability to non-normal data sets such the one resulting from this pilot.An oblique rotation method was used, as constructs are not expected to be uncorrelated.Outcomes of the factor analysis suggest that our instrument measures the five expectancy-valueconstructs separately from each other (with some item overlap between attainment value, utilityvalue and interest-enjoyment value) but that there may actually be seven factors. The additionaltwo factors . present the possibility that cost and utility value, as measured by this instrument,have sub-constructs. This is consistent with some recent studies suggesting that utility value mayconsist of multiple constructs. Resulting internal consistency ratings using Cronbach’s alphaproduce within-factor ratings higher than 0.75 in all cases. Ultimately, this instrument will be useful to the to the engineering education communitybecause of its potential to concisely measure all of the expectancy-value constructs (task valuesand expectancy of success) in engineering students. Scores on the expectancy of success andvalue scales could be compared to other data such as persistence rates and measurements ofcareer goals to better understand the decisions that students make about their engineeringeducation and career by measuring such connections.
Brown, P. R., & Matusovich, H. M. (2013, June), Unlocking Student Motivation: Development of an Engineering Motivation Survey Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--22669
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