Accurately Determining Self-Efficacy for Computer Application Domains: An Empirical Comparison of Two Methodologies

Computer self-efficacy (CSE) has been used in many studies as a predictor of individual competence or performance, usage behavior, and a variety of attitudes. Although CSE has been effective in explaining a variety of human computing interactions, there have been a number of studies in which the relationship was weak or nonexistent. One reason for such findings concerns how CSE is operationalized. Many (if not most) leading cognitive theorists (Bandura, 1997; Gist & Mitchell, 1992; Marakas et al., 1998) rather emphatically state that actual tasks must be used to most accurately determine an individual’s perception of ability (i.e., self-efficacy) for some task or domain. They suggest that using tasks, of incremental difficulty level within the intended domain, most accurately presents an individual’s self-efficacy and leads to stronger relationships with outcomes such as competence or performance. Yet one of the most utilized measures of self-efficacy uses levels of assistance (GCSE of Compeau & Higgins, 1995a), and not tasks. This study examines which methodology provides a stronger relationship with competence and performance. Using a sample of 610, self-efficacy (using both methodologies) and competence or performance were measured for six different application domains. Results indicate that for domains in which individual’s had lower ability, actual tasks were superior. For domains of higher ability, however, levels of assistance yielded stronger relationships. This study clarifies the relationship between self-efficacy and performance as an individual moves from low to high ability as a result of training or experience. Implications and suggestions for further study are included.