Computer self-efficacy is frequently used as an explanatory variable in software training and technology acceptance investigations. It has been frequently used to predict training and learning outcomes and some investigations have examined the malleability of computer self-efficacy in response to positive and negative training experiences. Computer self-efficacy models identify prior experience with computers as an important determinant of self-efficacy judgments; however, few studies have systematically examined this. Gender and frequency of computer use have been identified as other predictors of generalized computer self-efficacy. In this investigation, proficiency ratings on nineteen dimensions of computer knowledge are used to measure prior experience/knowledge of computers. These were collected from more than 300 university students at the same time that they completed an online generalized computer self-efficacy scale. This data is used to test two predictions: 1) that greater prior experience with computers is directly related to higher computer self-efficacy scores and 2) that for comparable levels of prior experience/knowledge, males will have higher self-efficacy scores than females. Preliminary results provide support for the first prediction but not the second. Initial results also suggest that less common types of prior experience/knowledge are especially important to self-efficacy judgments.
Bullington, Joseph; Case, Thomas; and Han, Hjo-Joo, "The Role of Gender and Prior Experience in Judgments of Generalized Computer Self Efficacy " (2005). SAIS 2005 Proceedings. 39.