University of Illinois Chicago
Browse

Investigating the Validity of Using NWEA’s MAP Results to Predict PSAE and ACT Results

Download (1.26 MB)
thesis
posted on 2014-10-28, 00:00 authored by Jonathan E. Brown
This research explores the relationship between MAP and PSAE and MAP and ACT in an effort to suggest cut scores that can help educators determine a student’s academic trajectory. This study was conducted to answer the question: Are NWEA MAP, PSAE, and ACT scores related such that NWEA MAP scores can predict future student performance on the PSAE and ACT and if so, what are the minimum in a range of MAP scores needed for grades 5-10 that demonstrate that a student is on track to meet state standards on the grade 11 PSAE and the ACT college and career readiness benchmarks. Student NWEA MAP and PSAE or ACT test scores were paired according to the related subject area. Pearson correlation coefficients were found to be adequately high confirming linear relations among the test scores. Sequential logistic regression models were calculated and found to support the fact that adding additional years of student scores enhanced the predictive ability of the models. Thirty-six bivariate logistic regression models were then run to calculate the minimum in a range of cut scores for NWEA MAP that would indicate that a student was on track to meet standards on the grade 11 PSAE in math and reading, and the grade 11 ACT in math, reading, and English subject areas, and overall Composite score. Half of the models used MAP scores from grades 8-10 with grade 11 PSAE and ACT scores as the dependent variable in data set 1 and the other half of the models used MAP scores from grades 5-7 with a grade 8 MAP score as the dependent variable in data set. The grade 8 MAP score used in data set 2 was the result of the analyses from data set 1. Models were validated and final cut scores were presented and discussed.

History

Advisor

Pellegrino, James

Department

Educational Psychology

Degree Grantor

University of Illinois at Chicago

Degree Level

  • Doctoral

Committee Member

Smith, Jr., Everett Myford, Carol Yin, Yue Lawless, Kimberly Fu, Qiong

Submitted date

2014-08

Language

  • en

Issue date

2014-10-28

Usage metrics

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC