Characteristics of Students Placed in College Remedial Mathematics: Using the ELS 2002/2006 Data to Understand Remedial Mathematics Placements

abstract: More than 30% of college entrants are placed in remedial mathematics (RM). Given that an explicit relationship exists between students' high school mathematics and college success in science, technology, engineering, and mathematical (STEM) fields, it is important to understand RM stu...

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Bibliographic Details
Other Authors: Barber, Rebecca Tants (Author)
Format: Doctoral Thesis
Language:English
Published: 2011
Subjects:
ELS
Online Access:http://hdl.handle.net/2286/R.I.8960
id ndltd-asu.edu-item-8960
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spelling ndltd-asu.edu-item-89602018-06-22T03:01:32Z Characteristics of Students Placed in College Remedial Mathematics: Using the ELS 2002/2006 Data to Understand Remedial Mathematics Placements abstract: More than 30% of college entrants are placed in remedial mathematics (RM). Given that an explicit relationship exists between students' high school mathematics and college success in science, technology, engineering, and mathematical (STEM) fields, it is important to understand RM students' characteristics in high school. Using the Education Longitudinal Survey 2002/2006 data, this study evaluated more than 130 variables for statistical and practical significance. The variables included standard demographic data, prior achievement and transcript data, family and teacher perceptions, school characteristics, and student attitudinal variables, all of which are identified as influential in mathematical success. These variables were analyzed using logistic regression models to estimate the likelihood that a student would be placed into RM. As might be expected, student test scores, highest mathematics course taken, and high school grade point average were the strongest predictors of success in college mathematics courses. Attitude variables had a marginal effect on the most advantaged students, but their effect cannot be evaluated for disadvantaged students, due to a non-random pattern of missing data. Further research should concentrate on obtaining answers to the attitudinal questions and investigating their influence and interaction with academic indicators. Dissertation/Thesis Barber, Rebecca Tants (Author) Garcia, David R (Advisor) Powers, Jeanne (Committee member) Rodrigue Mcintyre, Lisa (Committee member) Arizona State University (Publisher) Education Policy Higher Education developmental ELS mathematics remedial self-efficacy eng 131 pages Ph.D. Educational Leadership and Policy Studies 2011 Doctoral Dissertation http://hdl.handle.net/2286/R.I.8960 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2011
collection NDLTD
language English
format Doctoral Thesis
sources NDLTD
topic Education Policy
Higher Education
developmental
ELS
mathematics
remedial
self-efficacy
spellingShingle Education Policy
Higher Education
developmental
ELS
mathematics
remedial
self-efficacy
Characteristics of Students Placed in College Remedial Mathematics: Using the ELS 2002/2006 Data to Understand Remedial Mathematics Placements
description abstract: More than 30% of college entrants are placed in remedial mathematics (RM). Given that an explicit relationship exists between students' high school mathematics and college success in science, technology, engineering, and mathematical (STEM) fields, it is important to understand RM students' characteristics in high school. Using the Education Longitudinal Survey 2002/2006 data, this study evaluated more than 130 variables for statistical and practical significance. The variables included standard demographic data, prior achievement and transcript data, family and teacher perceptions, school characteristics, and student attitudinal variables, all of which are identified as influential in mathematical success. These variables were analyzed using logistic regression models to estimate the likelihood that a student would be placed into RM. As might be expected, student test scores, highest mathematics course taken, and high school grade point average were the strongest predictors of success in college mathematics courses. Attitude variables had a marginal effect on the most advantaged students, but their effect cannot be evaluated for disadvantaged students, due to a non-random pattern of missing data. Further research should concentrate on obtaining answers to the attitudinal questions and investigating their influence and interaction with academic indicators. === Dissertation/Thesis === Ph.D. Educational Leadership and Policy Studies 2011
author2 Barber, Rebecca Tants (Author)
author_facet Barber, Rebecca Tants (Author)
title Characteristics of Students Placed in College Remedial Mathematics: Using the ELS 2002/2006 Data to Understand Remedial Mathematics Placements
title_short Characteristics of Students Placed in College Remedial Mathematics: Using the ELS 2002/2006 Data to Understand Remedial Mathematics Placements
title_full Characteristics of Students Placed in College Remedial Mathematics: Using the ELS 2002/2006 Data to Understand Remedial Mathematics Placements
title_fullStr Characteristics of Students Placed in College Remedial Mathematics: Using the ELS 2002/2006 Data to Understand Remedial Mathematics Placements
title_full_unstemmed Characteristics of Students Placed in College Remedial Mathematics: Using the ELS 2002/2006 Data to Understand Remedial Mathematics Placements
title_sort characteristics of students placed in college remedial mathematics: using the els 2002/2006 data to understand remedial mathematics placements
publishDate 2011
url http://hdl.handle.net/2286/R.I.8960
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