Type of Document Dissertation Author Brown, Michael E. Author's Email Address email@example.com URN etd-06102010-120904 Title The Influence of Computer User Knowledge and Selected Demographic Characteristics on the Academic Achievement of High School Seniors Degree Doctor of Philosophy (Ph.D.) Department Human Resource Education Workforce Development Advisory Committee
Advisor Name Title Burnett, Michael F. Committee Chair Johnson, Earl C. Committee Member Kennedy, Eugene Committee Member Machtmes, Krisanna L. Committee Member Kosar, Tevfik Dean's Representative Keywords
- high school classroom technology
Date of Defense 2010-05-07 Availability unrestricted AbstractThe 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
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