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Understanding the Self-Efficacy of Data Scientists

Understanding the Self-Efficacy of Data Scientists

Alamir Costa Louro, Marcelo Moll Brandão, Larissa Alves Sincorá
Copyright: © 2020 |Volume: 11 |Issue: 2 |Pages: 14
ISSN: 1947-3478|EISSN: 1947-3486|EISBN13: 9781799802310|DOI: 10.4018/IJHCITP.2020040104
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MLA

Louro, Alamir Costa, et al. "Understanding the Self-Efficacy of Data Scientists." IJHCITP vol.11, no.2 2020: pp.50-63. http://doi.org/10.4018/IJHCITP.2020040104

APA

Louro, A. C., Brandão, M. M., & Sincorá, L. A. (2020). Understanding the Self-Efficacy of Data Scientists. International Journal of Human Capital and Information Technology Professionals (IJHCITP), 11(2), 50-63. http://doi.org/10.4018/IJHCITP.2020040104

Chicago

Louro, Alamir Costa, Marcelo Moll Brandão, and Larissa Alves Sincorá. "Understanding the Self-Efficacy of Data Scientists," International Journal of Human Capital and Information Technology Professionals (IJHCITP) 11, no.2: 50-63. http://doi.org/10.4018/IJHCITP.2020040104

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Abstract

The self-efficacy of Brazilian data scientists' professional profiles was analyzed to launch new views on this profession, marked by fast technological changes and with a body of knowledge and an incommensurable scope of skills, as understood by these professionals. A grounded theory was built using a qualitative approach. It found the coping theory to explain the phenomenon after the emergence of self-preservation, as an adaptation strategy, and self-efficacy, as a striking feature of the profession. A practical implication is that self-efficacy has trade-offs both to threats and opportunities in the process of becoming a data scientist. The present article describes the value of the coping theory makes possible an in-depth view of the analytical expertise influence on threats and opportunities, and on technology adaptation choices.

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