Document Type



Doctor of Education (EdD)


Curriculum and Instruction

First Advisor's Name

Thomas G. Reio Jr.

First Advisor's Committee Title

Major Professor

Second Advisor's Name

Isadore Newman

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Kyle Perkins

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Eric Dwyer

Fourth Advisor's Committee Title

Committee Member


Nonverbal, aptitude, Academic, Achievement, Bias, Standardized Test, Naglieri

Date of Defense



When a private school works to serve a diverse student population and provide excellence in education, academic aptitude is important to evaluate to better predict whether a student will be provided an education that is appropriately leveled.

Comparing the previous grades of a diverse applicant pool may prove problematic because of the differing scaling and grading methods utilized in differing educational systems. A nonverbal aptitude test may be utilized to fill this purpose by not only gauging a student’s aptitude, but also by minimizing bias associated with cultural or linguistic differences, as well as differences that may present themselves because of sex.

The present study included an ex post facto review of data collected over three academic years from 2013 to 2016 at a private secondary school. The nonverbal aptitude of applicants was gauged utilizing the Naglieri Nonverbal Aptitude Test (NNAT). The students’ overall GPA during their second semester at the school was identified to gauge academic achievement. These two values were then compared utilizing a hierarchical regression analysis to identify the ability of nonverbal aptitude to predict academic achievement. Additionally, the mean values of nonverbal aptitude between the sexes as


well as between native and non-native English speakers were compared utilizing a t-test. The sample consisted of 203 students. The study will add to the existing literature on the ability of nonverbal aptitude as measured by a nonverbal intelligence test to predict academic achievement in an academic setting.

The study found that the NNAT was statistically significant at the .005 alpha level in predicting academic achievement. The amount of variance explained by the overall model was 15.5% suggesting that other factors also explain the variance in academic achievement. Additionally, the t-tests performed in comparing the difference of means between the sexes as well as between native and non-native English speakers did not reflect any potential bias within the NNAT for these groups.

As part of an overall admissions process, the NNAT test can be utilized to better predict academic achievement while at the same time reduce bias toward minority students that is found in numerous aptitude tests commonly utilized in student placement processes.





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