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Understanding the Self-Efficacy of Data Scientists
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Author(s): Alamir Costa Louro (Federal University of Espírito Santo, Vitória, Brazil), Marcelo Moll Brandão (Federal University of Espírito Santo, Vitória, Brazil)and Larissa Alves Sincorá (Federal University of Espírito Santo, Vitória, Brazil)
Copyright: 2020
Volume: 11
Issue: 2
Pages: 14
Source title:
International Journal of Human Capital and Information Technology Professionals (IJHCITP)
Editor(s)-in-Chief: Sanjay Misra (Institute for Energy Technology, Halden, Norway)
DOI: 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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