There have been a number of studies investigating the factors effecting students choosing engineering in college, but very few discuss the effect of curricular pathways on students’ engineering discipline choice after their first year engineering experience.
This study aims to analyze, and present different curricular patterns undergraduate students take before choosing an engineering discipline in an institution with first year engineering matriculation model. The study also investigates how these different clusters can influence students’ major choice.
This research uses a longitudinal dataset dating from 1989 to 2011 and includes over 35,000 undergraduate students matriculating in one of the big Midwestern engineering universities. The dataset includes undergraduate students who have ever declared engineering as major. The study focuses on students who matriculate in one of the seven big engineering disciplines: Aero Space, Chemical, Civil, Computer, Electrical, Industrial, and Mechanical engineering. At the first step, the courses students take are categorized into different categories such as introductory to engineering courses, core science courses (math, physics, and chemistry), general courses, engineering courses, and general courses. Then, a cluster analysis is conducted on courses students take before choosing an engineering discipline. Then a regression model is applied to investigate the effect of these clusters on student’s major choice.
The preliminary result show the variety of curricular clusters students take throughout their first semester. By considering the courses that are offered and recommended by the institution, we illustrate a comparison between courses that are offered, and courses students end up taking. The results also show the effect of curricular policies on students’ curricular pathways.
This effort will lead in establishing a standard database for course classification in engineering curricula. The established classification can be the foundation for creating a common language for future cross institution studies. The findings can also provide useful information for students, institution administrators, and local and national policy makers.
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