Home
Resource
Improving educational outcomes for STEM students at Rutgers University-Camden
PDF
PDF format is widely accepted and good for printing.
Plug-in required
PDF-1(7.63 MB)
Citation & Export
View Usage Statistics
Staff View

Citation & Export
Hide

Simple citation

Pelullo, Arthur P.. Improving educational outcomes for STEM students at Rutgers University-Camden. Retrieved from https://doi.org/doi:10.7282/T3CJ8HJF

Export

Click here for information about Citation Management Tools at Rutgers.

Statistics
Hide

Description

TitleImproving educational outcomes for STEM students at Rutgers University-Camden
NamePelullo, Arthur P. (author); Shende, Sunil (chair); Rutgers University; Camden Graduate School
Date Created2017
Other Date2017-10 (degree)
SubjectComputer Science, Science--Study and teaching, Technology--Study and teaching, Engineering--Study and teaching, Mathematics--Study and teaching
Extent1 online resource (xii, 98 p. : ill.)
DescriptionThe goal of this thesis is to demonstrate how machine-learning techniques can be used to improve educational outcomes for STEM students at Rutgers University-Camden. The three main areas of focus are: identifying changes in the academic landscape throughout a 15-year period, identifying predictors of student success, and using these predictors to develop a recommendation system to assist at-risk students. The data in the study con- sists of student demographic and academic records from 2003-2017. Simple exploratory data analysis is used to highlight changes in student performance over time. Next, a deeper analysis is performed by training three classifiers - logistic regression with L1 penalty, logistic regression with L2 penalty, and a random forest model - to predict the probability that students will graduate. Finally, the predictions of each classifier are calibrated and combined to form a robust recommendation system which can be used to alert advisers when a student is struggling.
NoteM.S.
NoteIncludes bibliographical references
Noteby Arthur P. Pelullo
Genretheses, ETD graduate
Persistent URLhttps://doi.org/doi:10.7282/T3CJ8HJF
Languageeng
CollectionCamden Graduate School Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
Version 8.5.5
Rutgers University Libraries - Copyright ©2024