A 3-year study was conducted to document individual differences in computer interest and use among middle school students and the psychological and social processes that may contribute to these differences. A questionnaire was used to assess the computer interest and use of a sample of approximately 400 middle school students at the end of each of the 3 years. The dependent measures--interest in learning about computers, plans to take elective computer classes, willingness to consider a computer career, and non-school computer use--and outcome measures were combined into a computer interest and use composite score. Eight independent variables were selected: mathematics interest, current goals for computer use, mathematics achievement, perceived parental encouragement for computing activities, perceived peer reactions to computer involvement, perceived relevance of computing skills for the future, perceived self-efficacy for computer-related tasks, and affective responses to the computer. These variables were organized using a newly developed version of "living systems" theory and students were asked to rate them on a scale of 1 to 5. Regression analysis of the data from the questionnaires and additional demographic and descriptive data showed that: (1) the gender of the subject appears to be an important social characteristic to consider in predicting computer interest and use since there were significant differences in favor of males; (2) boys may be more involved in computers as the result of more opportunities for mastery, more role models to emulate, greater verbal encouragement, and less fear of the machines; and (3) boys express a more positive attitude about the benefits of computers to society than do girls. Although there was a decline within grade levels from year to year over the 3-year period the variables showed consistent gender differences in favor of males. (DJR)
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education