Predicting success on Gateway exams using TCAP Achievement Test data
Abstract
This research examined the relationship between student academic attainment as measured by TCAP (Terra Nova) standardized tests in the benchmark grades three, five, and eight; Tennessee Value Added Assessment Predictor Scores (TVAAS); and future performance on the Tennessee Gateway Mathematics, English, and Science exit examinations. Test data was also examined for differences in scores based upon students' gender, socioeconomic status, and eligibility for special education services. Academic records for 314 students enrolled in Sequatchie County High during academic terms Fall 2001 through Spring 2003 were analyzed. Results revealed statistically significant relationships for Terra Nova achievement test data and performance on Gateway examinations. Statistically significant differences were also found for each subgroup. Findings also revealed that each subgroup had differences in which specific Terra Nova subtest subjects were predictors of success on Gateway examinations. All statistical analyses were conducted at the p > .01 level of significance. This research revealed that Terra Nova achievement data was a statistically significant predictor of Gateway examination scores. Based on the results of this research it was recommended that Terra Nova data be used as a single measure in a multiple-measure model to identify students needing intervention to ensure their success on Gateway examinations. It was also recommended that TVAAS predictor scores be used to help course assignments and as an objective data source in conferences with parents, students, and teachers. Recommendation was made that similar studies be conducted in the future as the format of the Terra Nova moves from a norm-referenced to criterion-referenced test.
Subject Area
Educational evaluation|Elementary education|Secondary education
Recommended Citation
Gwen Whitlow Hobbs,
"Predicting success on Gateway exams using TCAP Achievement Test data"
(2005).
ETD Collection for Tennessee State University.
Paper AAI3167776.
https://digitalscholarship.tnstate.edu/dissertations/AAI3167776