The effect of supportive strategies on computer anxiety and computer self-efficacy in nursing students
Authors: Dawn M. Specht
Venue:  (2008)

The purpose of this study was to investigate differences in computer anxiety and computer self-efficacy among nursing students who receive faculty support to complete a computer assignment, nursing students who utilized peer support, and nursing students who independently completed a computer assignment. A convenience sample was obtained from local nursing programs in the Mid-Atlantic region. Ninety-nine female nursing students participated in the study. Subjects were randomly assigned to treatment groups. This study used a quasi-experimental design. A pretest-posttest comparison group design was applied to three groups. In this design, the independent variable was support. Two types of support were utilized: faculty one-on-one support and peer support. A third group received no support and completed the computer activity independently, thus serving as a control group. The dependent variables were computer anxiety and computer self-efficacy. Computer anxiety was measured using the Computer Anxiety Scale (COMPAS) by Oetting (1983). Computer self-efficacy was measured using the beginning level scale of the Computer Self-Efficacy Scale (CSE), by Murphy, Coover, Owen (1989). A model of computer anxiety reduction was developed and it was hypothesized that support would decrease computer anxiety in nursing students. In this design, the influence of general self-efficacy and trait anxiety was statistically controlled through analysis of covariance. Trait anxiety was measured utilizing Spielberger's State Trait Anxiety Inventory Scale (STAI) (1999). General self-efficacy was measured with the General Self-Efficacy subscale (GSE) of the Self-Efficacy Scale by Sherer, Maddux, Mercandante, Dunn, Jacobs, and Rogers (1982). Computer exposure in hours per week, race and age of each participant were recorded using a demographic questionnaire. The pretest mean computer anxiety score of the subjects was 42.81 ( SD = 14.41) indicating low computer anxiety. The mean pretest computer self-efficacy score of the subjects was 66.89 (SD = 12.87) indicating high computer self-efficacy. There was not a significant change in posttest computer anxiety or computer self-efficacy based upon support. Computer anxiety was highly inversely correlated with computer self-efficacy, pre intervention (r = - .74, p = .000) and post intervention (r = - .76, p = .000). As computer anxiety increases, computer self-efficacy decreases. Years of computer experience relates to computer anxiety and computer self-efficacy; the more computer experience a student has, the less computer anxiety and more computer self-efficacy. The current study set out to test the Specht Interventional Model of Computer Anxiety. The model recognizes the unique characteristics a person brings to the computer interaction environment. Interventions should be aimed at increasing computer self-efficacy and decreasing computer anxiety. In the current study, the interventions did not significantly impact computer anxiety or computer self-efficacy as few students had computer anxiety. In future studies, the intervention may need to be longer. It may also be necessary to separate subjects based upon computer anxiety and computer self-efficacy scores as those with low or no computer anxiety may not be susceptible to interventions that are aimed at computer anxious subjects. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player