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Noncognitive Characteristics Of Incoming Engineering Students Compared To Incoming Engineering Technology Students: A Preliminary Examination

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2008 Annual Conference & Exposition


Pittsburgh, Pennsylvania

Publication Date

June 22, 2008

Start Date

June 22, 2008

End Date

June 25, 2008



Conference Session

Engineering and ET Relationships & Professional Development

Tagged Division

Engineering Technology

Page Count


Page Numbers

13.933.1 - 13.933.11



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Paper Authors

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Kenneth Reid Indiana University-Purdue University-Indianapolis

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P.K. Imbrie Purdue University

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

Noncognitive Characteristics of Incoming Engineering Students Compared to Incoming Engineering Technology Students: A Preliminary Examination

Abstract: Studies have shown promise in predicting success for students in engineering based on noncognitive or affective characteristics. However, little if any literature exists on similar studies in the related discipline of engineering technology.

Data has been collected from incoming engineering students in a large, Midwestern university using an instrument assessing students’ self-reported noncognitive characteristics over a four year period. The instrument has been shown to be stable and repeatable over this four year period. Cluster analysis has shown that students entering engineering cluster into three distinct groups. Five additional constructs have been added to the survey for the current cohort of students.

This paper will examine results of an analysis of students in a pilot study in engineering technology using the same instrument already in use for incoming engineering students. Differences found between engineering and technology cohorts will be presented to the extent that the relatively small sample of technology students will allow. Finally, suggestions for future work in this area, the suggested applicability of individual items in the instrument and potential findings within the data will be presented.

An effective instrument will allow for the development of a model to predict success, currently operationalized as retention into the second year. Such a model should prove to be valuable to address long standing issues of gender and ethnic disparities within engineering technology and should lead to improved advising and improved overall student success.


Engineering and engineering technology are comparatively lucrative fields of employment with continued strong demand. These fields attract academically strong students; however, graduation rates in engineering programs have been shown to be at or around 50% nationwide. Astin1 showed that only 44% of students entering engineering showed engineering as their major four years later. The National Academies report “Rising Above the Gathering Storm”2 describes technical programs as having some of the lowest retention rates among academic disciplines. Studies have shown that students who leave engineering tend to show differences in their noncognitive characteristics rather than cognitive ability or academic performance3,4.

An instrument consisting of 161 items designed to assess noncognitive characteristics of incoming students was originally designed to assess characteristics of incoming engineering students. The instrument was used to assess nine noncognitive constructs, specifically focusing on those characteristics for which an institution may be able to develop intervention strategies / programs rather than an attempt to simply collect a wide range of data. Data has been collected for a four year period for incoming engineering students and were found to be psychometrically

Reid, K., & Imbrie, P. (2008, June), Noncognitive Characteristics Of Incoming Engineering Students Compared To Incoming Engineering Technology Students: A Preliminary Examination Paper presented at 2008 Annual Conference & Exposition, Pittsburgh, Pennsylvania. 10.18260/1-2--4133

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