The Influence of Computer User Knowledge and Selected Demographic Characteristics on the Academic Achievement of High School Seniors

The primary purpose of this study was to identify the influence of computer user knowledge as measured by the Computer User Knowledge Survey (CUKS), and the personal demographic characteristics of Gender, Age, and Race on academic achievement as measured by the Graduation Exit Examination-21 (GEE-21...

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Bibliographic Details
Main Author: Brown, Michael E.
Other Authors: Kennedy, Eugene
Format: Others
Language:en
Published: LSU 2010
Subjects:
Online Access:http://etd.lsu.edu/docs/available/etd-06102010-120904/
Description
Summary:The primary purpose of this study was to identify the influence of computer user knowledge as measured by the Computer User Knowledge Survey (CUKS), and the personal demographic characteristics of Gender, Age, and Race on academic achievement as measured by the Graduation Exit Examination-21 (GEE-21), among high school seniors in public schools in a parish in South Louisiana. The CUKS and the Gender and Race data were collected from the self-perceived CUKS survey administered to 295 seniors registered in English IV classes at a school in South Louisiana. The academic achievement data and the ages of the student subjects were retrieved from the Louisiana Department of Education GEE-21 data base. Each of the six CUKS sub-scales, Basic Knowledge CUKS, Windows CUKS, Word Processing CUKS, Internet CUKS, Multimedia CUKS, and Computer Games CUKS, and the Overall CUKS score were correlated with each of the four GEE-21 academic achievement categories, Math, English, Science, and Social Studies. The results showed that Multimedia CUKS (r = .16; p = .018) and Basic Knowledge CUKS (r = .04; p = .037) were significantly related to English scores. No other significant relationships were found among the CUKS subscales and the GEE-21 scores. Regression analysis was used to determine if models existed which explained a significant portion of the variance in academic achievement scores. The regression models showed that Multimedia CUKS explained 2.3% of the variance in English scores; Gender explained 3.8% and Hispanic explained 1.9% of the variance in Science scores; and Gender explained 5% and Multimedia CUKS 1.9% of the variance in Social Studies scores. Conclusion included: 1) the racial make-up of the sample was very atypical for public schools in South Louisiana; 2) there was little or no correlation between computer user knowledge and academic achievement; 3) the scores of the student participants were exceptionally high on the self-perceived CUKS; 4) sample students typically scored in higher achievement levels than students statewide, and outstandingly so in Math. Recommendations included finding and using more objective computer knowledge assessments in future studies to reduce the possibility of student response error in similar studies.