Is Modeling of Freshman Engineering Success Different from Modeling of Non‐Engineering Success?
dc.contributor.author | Veenstra, Cindy P. | en_US |
dc.contributor.author | Dey, Eric L. | en_US |
dc.contributor.author | Herrin, Gary D. | en_US |
dc.date.accessioned | 2013-01-03T19:44:50Z | |
dc.date.available | 2013-01-03T19:44:50Z | |
dc.date.issued | 2008-10 | en_US |
dc.identifier.citation | Veenstra, Cindy P.; Dey, Eric L.; Herrin, Gary D. (2008). "Is Modeling of Freshman Engineering Success Different from Modeling of Non‐Engineering Success?." Journal of Engineering Education 97(4). <http://hdl.handle.net/2027.42/95487> | en_US |
dc.identifier.issn | 1069-4730 | en_US |
dc.identifier.issn | 2168-9830 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/95487 | |
dc.description.abstract | The engineering community has recognized the need for a higher retention rate in freshman engineering. If we are to increase the freshman retention rate, we need to better understand the characteristics of academic success for engineering students. One approach is to compare academic performance of engineering students to that of non‐engineering students. This study explores the differences in predicting academic success (defined as the first year GPA) for freshman engineering students compared to three non‐engineering student sectors (Pre‐Med, STEM, and non‐STEM disciplines) within a university. Academic success is predicted with pre‐college variables from the UCLA/CIRP survey using factor analysis and regression analysis. Except for the factor related to the high school GPA and rank, the predictors for each student sector were discipline specific. Predictors unique to the engineering sector included the factors related to quantitative skills (ACT Math and Science test scores and placement test scores) and confidence in quantitative skills. | en_US |
dc.publisher | Wiley Periodicals, Inc. | en_US |
dc.publisher | Blackwell Publishing Ltd | en_US |
dc.subject.other | CIRP Survey | en_US |
dc.subject.other | Pre‐College Characteristics | en_US |
dc.subject.other | Freshman Engineering Success | en_US |
dc.title | Is Modeling of Freshman Engineering Success Different from Modeling of Non‐Engineering Success? | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Engineering Education | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Industrial and Operations Engineering University of Michigan | en_US |
dc.contributor.affiliationum | Department of Industrial and Operations Engineering University of Michigan | en_US |
dc.contributor.affiliationum | School of Education University of Michigan | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/95487/1/j.2168-9830.2008.tb00993.x.pdf | |
dc.identifier.doi | 10.1002/j.2168-9830.2008.tb00993.x | en_US |
dc.identifier.source | Journal of Engineering Education | en_US |
dc.identifier.citedreference | Nicholls, G. 2007. Draft of chapter 3 of Ph.D. dissertation, University of Pittsburgh. | en_US |
dc.identifier.citedreference | Sacre, Besterfield M., C. Atman and L. Shuman, 1997. Characteristics of freshman engineering students: Models for determining student attrition in engineering. Journal of Engineering Education, 86 ( 2 ): 139 – 49. | en_US |
dc.identifier.citedreference | Burtner, J. 2004. Critical‐to‐quality factors associated with engineering student persistence: the influence of freshman attitudes. 34th ASEE/ISEE Frontiers in Education Conference (F2E‐1). Available at: http:fie.engrng.pitt.edufie2007index.html. | en_US |
dc.identifier.citedreference | Clough, G. 2004. The engineer of 2020: Visions of engineering in the new century. Washington, DC: National Academy of Engineering (NAE ). | en_US |
dc.identifier.citedreference | Cokeley, S., M. Brynes, G. Markley, and S. Keely, eds. 2006. Transformation to performance excellence. Milwaukee, WI: ASQ Press. | en_US |
dc.identifier.citedreference | French, B., J. Immekus, W. Oakes. 2005. Research brief: An examination of indicators of engineering students' success and persistence. Journal of Engineering Education 94 ( 4 ): 419 – 25. | en_US |
dc.identifier.citedreference | Levin, J., and J. Wyckoff. 1988. Effective advising: Identifying students most likely to persist and succeed in engineering. Engineering Education (December): 178 – 82. | en_US |
dc.identifier.citedreference | Lotkowski, V., S. Robbins, and R. Noeth, 2004. The role of academic and non‐ academic factors in improving college retention. ACT, Inc., http:www.act.orgresearchpolicymakerspdfcollege_retention.pdf (last accessed July 2008). | en_US |
dc.identifier.citedreference | Matney, M. 2005. College of engineering: Entering student survey 2004: Summary data from the Cooperative Institutional Research Program (CIRP). Ann Arbor: University of Michigan Division of Student Affairs. | en_US |
dc.identifier.citedreference | Matney, M. 2006. E‐mail communication, April 20, 2006. | en_US |
dc.identifier.citedreference | Matthews, P.G. 2005. Design of experiments with Minitab. Milwaukee, WI: ASQ Quality Press. | en_US |
dc.identifier.citedreference | Myers, R. and D. Montgomery. 2002. Response surface methodology ( 2nd ed. ). New York: John Wiley & Sons, Inc. | en_US |
dc.identifier.citedreference | National Academy of Sciences (NAS). Committee on Science, Engineering, and Public Policy (COSEPUP). 2005. Rising above the gathering storm: Energizing and employing America for a brighter economic future. Washington, DC: The National Academies Press. | en_US |
dc.identifier.citedreference | National Science Foundation. 2004. NSB science and engineering indicators report. Available at http:www.nsf.govstatisticsseind04. | en_US |
dc.identifier.citedreference | National Science Foundation. 2006. NSB science and engineering indicators report. Available at http:www.nsf.govstatisticsseind06. | en_US |
dc.identifier.citedreference | Nicholls, G., H. Wolfe, M. Besterfield Sacre, L. Shuman, S. Larpkiattaworn. 2007. A method for identifying variables for predicting STEM enrollment. Journal of Engineering Education 96 ( 1 ): 33 – 44. | en_US |
dc.identifier.citedreference | Seymour, E., and N. Hewitt. 1997. Talking about leaving: Why undergraduates leave the sciences. Boulder, CO: Westview Press. | en_US |
dc.identifier.citedreference | Shuman, L., M. Besterfield Sacre, D. Budny, S. Larpkiattaworn, O. Muogboh, S. Provezis, H. Wolfe, 2003. What do we know about our entering students and how does it impact upon performance ? In Proceedings of the 2003 American Society for Engineering Education Annual Conference and Exposition, Session 3553. Washington, DC: American Society for Engineering Education. Available at: www.asee.org. | en_US |
dc.identifier.citedreference | SPSS Inc. 2006. SPSS 15.0 for Windows Software, Help Command. | en_US |
dc.identifier.citedreference | University of Michigan. 2007. Freshman class profile, dated 1/17/2007, viewed at http:sitemaker.umich.eduobpinfo, on 2/7/07. | en_US |
dc.identifier.citedreference | Veenstra, C. and G. Herrin, 2006. Using the SAT and ACT scores for placement into engineering freshman classes. In Proceedings of the 2006 American Society for Engineering Education World Conference, 2006–771. Washington, DC: American Society for Engineering Education. Available at: www.asee.org. | en_US |
dc.identifier.citedreference | Veenstra, C., G. Herrin, and E. Dey, 2007. Development of a freshman engineering retention model based on pre‐college characteristics. IOE Technical Report 07–04. March 27. Available at: http:ioe.engin.umich.edutechrprtpdfTR07‐04.pdf. | en_US |
dc.identifier.citedreference | Zhang, G., Y. Min, M. Ohland, and T. Anderson, 2006. The role of academic performance in engineering attrition. In Proceedings of the 2006 American Society for Engineering Education World Conference, 2006 – 1336. Washington DC: American Society for Engineering Education. Available at: www.asee.org. | en_US |
dc.identifier.citedreference | Astin, A., and H. Astin. 1992. Undergraduate science education: The impact of different college environments on the educational pipeline in the sciences. Sponsored by the National Science Foundation. Los Angeles: University of California, Los Angeles, Higher Education Research Institute. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.