dc.contributor.advisor | Sterba, Sonya K. | |
dc.contributor.author | Fuller, Lydia | |
dc.date.accessioned | 2014-04-12T18:15:15Z | |
dc.date.available | 2014-04-12T18:15:15Z | |
dc.date.issued | 2014-04-06 | |
dc.identifier.uri | http://hdl.handle.net/1803/6290 | |
dc.description | Thesis completed in partial fulfillment of the Honors Program in Psychological Sciences under the direction of Dr. Sonya Sterba. Employs Latent Class Growth Modeling techniques to describe and predict heterogeneous learning patterns among adult female students at a GED preparation program. | en_US |
dc.description.abstract | Each year, 500,000 adults take the General Education Development (GED) exam, the
gateway to a high school equivalency diploma. Nearly 40 percent fail. Little research exists on
the relation between preparation experiences and exam success. This thesis investigated
heterogeneous learning patterns among women at a GED preparation program in Detroit,
Michigan during their first ten months of enrollment. Using Latent Class Growth Modeling,
patterns among repeated measures on math and on reading were best accounted for by three
latent trajectory classes per subject. Classes followed unique and non-overlapping achievement
trajectories. Five factors were assessed as potential predictors of trajectory class membership.
Younger age, non-English native language, and employment predicted a higher-achieving math
trajectory, while being a native English speaker and being a single head of household predicted a
higher-achieving reading trajectory. Last school grade completed was not predictive of
achievement in either subject domain. Associations between math and reading achievement
trajectories were also analyzed, with students generally exhibiting similar levels of achievement
across subjects, though high math achievement trajectory membership was more predictive of
high reading achievement trajectory membership than vice versa. Finally, membership in classes
following higher achievement trajectories was determined to be associated with a greater
likelihood of success on the GED exam. | en_US |
dc.description.sponsorship | Thesis completed in partial fulfillment of the requirements of the Honors Program in Psychological Sciences under
the direction of Dr. Sonya Sterba. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Vanderbilt University | en_US |
dc.subject | GED | en_US |
dc.subject | Student Achievement | en_US |
dc.subject | Mixture Modeling | en_US |
dc.subject | Latent Class Growth Model | en_US |
dc.subject.lcsh | Psychology -- Quantitative research | en_US |
dc.subject.lcsh | GED tests | en_US |
dc.subject.lcsh | Women -- Education | en_US |
dc.subject.lcsh | Prediction of scholastic success | en_US |
dc.title | GED Student Achievement Trajectories and Predictors: Using the Latent Class Growth Model to Understand Heterogeneous Learning Patterns | en_US |
dc.type | Thesis | en_US |
dc.description.college | Peabody College | en_US |
dc.description.school | Vanderbilt University | en_US |
dc.description.department | Psychology and Human Development | en_US |