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Dissertation 4.4

Talent And Skills in Education Policy for Data Science Teams: A qualitative grounded theory

15
Pages
Chicago
Style
~ 15–24 mins
Reading Time
Telemedicine RPA BioMed
Abstract

This dissertation investigates “Talent And Skills in Education Policy for Data Science Teams: A qualitative grounded theory” using a social network analysis. Through a behavioral lens, the analysis integrates multi-source data to derive novel empirical evidence for researchers and practitioners.

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Talent And Skills in Education Policy for Data Science Teams: A qualitative grounded theory

ABSTRACT
Talent And Skills in Education Policy for Data Science Teams: A qualitative grounded theory is unpacked across themes: equity, change enablement, risks, and scalability. Limitations and future research paths are noted.
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