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Explicating Computer Self-Efficacy Relationships: Generality and the Overstated Case of Specificity Matching

Explicating Computer Self-Efficacy Relationships: Generality and the Overstated Case of Specificity Matching

James P. Downey Jr. (University of Central Arkansas, USA), R. Kelly Rainer (Auburn University, USA), and Summer E. Bartczak (Air Force Institute of Technology, USA)
Copyright: © 2008 |Pages: 19
DOI: 10.4018/joeuc.2008070102
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Abstract

Computer self-efficacy is known to operate at multiple levels, from application-specific subdomains like spreadsheets to a judgment of ability for the entire computing domain (general computer self-efficacy, GCSE). Conventional wisdom and many recent studies contend that the level of self-efficacy (specific to general) should match the level of its related constructs to maximize predictive power (Bandura, 1997; Chen, Gully, & Eden, 2001; Pajares, 1996). This thinking claims, for example, that GCSE should be used with a general attitude like computer anxiety (and vice versa). This study examines whether such a limitation is theoretically and empirically sound given that SE judgments generalize across domains.

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