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Unsuccessful Performance and Future Computer Self-Efficacy Estimations: Attributions and Generalization to Other Software Applications

Unsuccessful Performance and Future Computer Self-Efficacy Estimations: Attributions and Generalization to Other Software Applications

Richard D. Johnson, Yuzhu Li, James H. Dulebohn
Copyright: © 2016 |Volume: 28 |Issue: 1 |Pages: 14
ISSN: 1546-2234|EISSN: 1546-5012|EISBN13: 9781466688780|DOI: 10.4018/JOEUC.2016010101
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MLA

Johnson, Richard D., et al. "Unsuccessful Performance and Future Computer Self-Efficacy Estimations: Attributions and Generalization to Other Software Applications." JOEUC vol.28, no.1 2016: pp.1-14. http://doi.org/10.4018/JOEUC.2016010101

APA

Johnson, R. D., Li, Y., & Dulebohn, J. H. (2016). Unsuccessful Performance and Future Computer Self-Efficacy Estimations: Attributions and Generalization to Other Software Applications. Journal of Organizational and End User Computing (JOEUC), 28(1), 1-14. http://doi.org/10.4018/JOEUC.2016010101

Chicago

Johnson, Richard D., Yuzhu Li, and James H. Dulebohn. "Unsuccessful Performance and Future Computer Self-Efficacy Estimations: Attributions and Generalization to Other Software Applications," Journal of Organizational and End User Computing (JOEUC) 28, no.1: 1-14. http://doi.org/10.4018/JOEUC.2016010101

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Abstract

Using data from 100 individuals, this study examined the role of performance attributions (stability and locus of causality) and computer self-efficacy (CSE) for spreadsheets and databases in the training context. The results show that both self-efficacy and attributions (locus of causality and stability) for unsuccessful performance on one software package affected future efficacy estimations for both the same software package (spreadsheet) as well as for a related software package (database). These findings extend previous research by illustrating that through the generality of CSE estimations, users' performance on one software package are related to self-efficacy estimations on a different, distally similar, software application. This suggests that trainers and managers cannot overlook the importance of self-efficacy generality in the design of technology training initiatives. Early, unsuccessful experiences for those with limited technology experience can make it more challenging to adapt to, and learn to use, new technologies.

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