Predicting student performance on the Texas Assessment of Academic Skills Exit Level Exam: Predictor modeling through logistic regression.

PDF Version Also Available for Download.

Description

The purpose of this study was to investigate predicting student success on one example of a "high stakes" test, the Texas Assessment of Academic Skills Exit Level Exam. Prediction algorithms for the mathematics, reading, and writing portions of the test were formulated using SPSS® statistical software. Student data available on all 440 students were input to logistic regression to build the algorithms. Approximately 80% of the students' results were predicted correctly by each algorithm. The data that were most predictive were the course related to the subject area of the test the student was taking, and the semester exam grade ... continued below

Creation Information

Rambo, James R. August 2004.

Context

This dissertation is part of the collection entitled: UNT Theses and Dissertations and was provided by UNT Libraries to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 392 times , with 4 in the last month . More information about this dissertation can be viewed below.

Who

People and organizations associated with either the creation of this dissertation or its content.

Chair

Committee Members

Publisher

Rights Holder

For guidance see Citations, Rights, Re-Use.

  • Rambo, James R.

Provided By

UNT Libraries

With locations on the Denton campus of the University of North Texas and one in Dallas, UNT Libraries serves the school and the community by providing access to physical and online collections; The Portal to Texas History and UNT Digital Libraries; academic research, and much, much more.

Contact Us

What

Descriptive information to help identify this dissertation. Follow the links below to find similar items on the Digital Library.

Description

The purpose of this study was to investigate predicting student success on one example of a "high stakes" test, the Texas Assessment of Academic Skills Exit Level Exam. Prediction algorithms for the mathematics, reading, and writing portions of the test were formulated using SPSS® statistical software. Student data available on all 440 students were input to logistic regression to build the algorithms. Approximately 80% of the students' results were predicted correctly by each algorithm. The data that were most predictive were the course related to the subject area of the test the student was taking, and the semester exam grade and semester average in the course related to the test. The standards of success or passing were making a 70% or higher on the mathematics, 88% or higher on the reading, and 76% or higher on the writing portion of the exam. The higher passing standards maintained a pass/fail dichotomy and simulate the standard on the new Texas Assessment of Knowledge and Skills Exit Level Exam. The use of the algorithms can assist school staff in identifying individual students, not just groups of students, who could benefit from some type of academic intervention.

Language

Identifier

Unique identifying numbers for this dissertation in the Digital Library or other systems.

Collections

This dissertation is part of the following collection of related materials.

UNT Theses and Dissertations

Theses and dissertations represent a wealth of scholarly and artistic content created by masters and doctoral students in the degree-seeking process. Some ETDs in this collection are restricted to use by the UNT community.

What responsibilities do I have when using this dissertation?

When

Dates and time periods associated with this dissertation.

Creation Date

  • August 2004

Added to The UNT Digital Library

  • Feb. 15, 2008, 3:34 p.m.

Description Last Updated

  • Feb. 26, 2008, 12:48 p.m.

Usage Statistics

When was this dissertation last used?

Yesterday: 0
Past 30 days: 4
Total Uses: 392

Interact With This Dissertation

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Rambo, James R. Predicting student performance on the Texas Assessment of Academic Skills Exit Level Exam: Predictor modeling through logistic regression., dissertation, August 2004; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc4577/: accessed December 10, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .