Title page for ETD etd-06102010-120904


Type of Document Dissertation
Author Brown, Michael E.
Author's Email Address thlender@cox.net
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
Abstract
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.

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