ERIC Number: ED642221
Record Type: Non-Journal
Publication Date: 2021
Pages: 220
Abstractor: As Provided
ISBN: 979-8-7906-2605-0
ISSN: N/A
EISSN: N/A
Available Date: N/A
Non-Cognitive Skills as Predictors of Academic Performance: How Differential Item Functioning Affects Prediction of College Enrollment
Juliana Cerentini Pacico
ProQuest LLC, Ph.D. Dissertation, The University of Iowa
The 2015 Every Student Succeeds Act (ESSA) emphasized that students, regardless of group membership, should graduate ready for college or work. The economic impact of not being ready is significantly negative. Non-cognitive skills (NCSs) assessments have been used to identify students at risk and intervene to help prevent undesirable outcomes. This dissertation intended to answer three main research questions. The first investigated if items on an instrument of NCSs showed significant differential item functioning (DIF) for relevant groups of students. DIF analyses were performed to verify if items are functioning appropriately for different ethnicity (Hispanic and non-Hispanic) and race (African American and White) groups. Results suggested that the 23 out of 45 polytomous items selected from the NCSs instrument showed significant DIF for the groups compared. The second research question investigated how NCSs would increment the prediction of academic performance (measured by ACT composite score and college enrollment). Several models were compared using linear and logistic regression. The results suggested that NCSs assessments do not improve the amount of variance explained on the outcome variable (ACT composite score) or the quality of the model fit. For the logistic models used for predicting college enrollment, the NCSs did not improve the ability of the model in predicting the outcome. Last, the third research question investigated if the prediction of academic outcomes would change if the items flagged for DIF were removed from the NCSs instrument when performing the regression analyses. The parameters used to compare the models, R square and RMSE (for linear regression) and c-statistic and Akaike Information Criterion were nearly identical to when the items have not been removed from the instrument. The results suggested that the removal of the items flagged for DIF from the NCSs instrument did not affect the prediction of academic performance. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]
Descriptors: Educational Legislation, Elementary Secondary Education, Federal Legislation, Test Bias, College Enrollment, Prediction, Skills, Minority Group Students, Academic Achievement
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Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Elementary Secondary Education; Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Laws, Policies, & Programs: Every Student Succeeds Act 2015
Grant or Contract Numbers: N/A
Author Affiliations: N/A