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Is Modeling of Freshman Engineering Success Different from Modeling of Non‐Engineering Success?
Author(s) -
Veenstra Cindy P.,
Dey Eric L.,
Herrin Gary D.
Publication year - 2008
Publication title -
journal of engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.896
H-Index - 108
eISSN - 2168-9830
pISSN - 1069-4730
DOI - 10.1002/j.2168-9830.2008.tb00993.x
Subject(s) - engineering education , test (biology) , psychology , multilevel model , mathematics education , rank (graph theory) , regression analysis , engineering , medical education , engineering management , mathematics , medicine , statistics , paleontology , combinatorics , biology
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.