June 14, 2015
June 14, 2015
June 17, 2015
NSF Grantees Poster Session
26.346.1 - 26.346.9
Characterizing and Modeling the Experience of Transfer Students in Engineering— Progress on NSF Award 0969474Quantitative analysis of MIDFIELD databaseOur analysis used records for 94,732 undergraduate students from the Multiple-InstitutionDatabase for Investigating Engineering Longitudinal Development (MIDFIELD). MIDFIELDcomprises a census of undergraduate students who attended 11 public institutions between 1988and 2008. MIDFIELD institutions represent public universities that educate large numbers ofengineering students.From the 977,950 records available, we restricted our sample to those who (1) were domesticstudents (927,350), (2) were in the data set early enough for us to observe the possibility ofgraduation within six years (677,691), and (3) declared a major in engineering or otherwiseexpressed the intent to study engineering in the fifth semester of their programs (94,732). Fortransfer students, we estimated placement using transfer hours, assuming that 15 credit hoursequals one semester; we also used the fifth semester as the reference point to capture mosttransfer students at the point of matriculation to ensure a valid comparison of transfers to non-transfers. This approach resulted in a sample of 21,542 transfer and 73,190 non-transferengineering students included in this analysis.Semi-structured interviewsCampus representatives at two MIDFIELD institutions sent an invitation to all engineeringstudents who had transferred into the institution in the two semesters preceding the semester ofthe interview. Interested students completed a survey to provide demographic and schedulinginformation. Participants were chosen from six engineering majors - civil, chemical, computer,electrical, industrial, and mechanical - and were diverse with respect to gender and ethnicity.Selected students were interviewed in Fall 2011 and in Spring 2012.We used a semi-structured interview protocol to learn more about student experiences with thetransfer process. We used a constant comparative coding method, whereby emerging conceptswere constantly compared to data that had already been coded.Overview of Progress Identifying and Describing the Entry Points into Engineering Transfer Pathways: A preliminary study relied on 52 of the 86 students who were interviewed across five campuses to understand their reasons for choosing engineering as a field of studies and the transfer pathway to enter the field. Studying the Motivations and Experiences of Older Transfer Students in Engineering: Of the 86 students who were interviewed on the five campuses, the 15 students who were 25 years of age or older at the time of the interview were selected for this study. Studying the Performance of Black transfer students: based on a logistic regression model refined to include transfer pathway (2-year vs. 4-year), we learned that: Studying the Mean Grade Differential by Course Discipline: For engineering transfer and first-time-in-college (FTIC) students, we computed average grades in STEM courses by discipline, and by institution.
Ohland, M. W., & Cosentino, C. M., & Brawner, C. E., & Mobley, C., & Long, R. A. (2015, June), Characterizing and Modeling the Experience of Transfer Students in Engineering—Progress on NSF Award 0969474 Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23685
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