A model to evaluate data science in nursing doctoral curricula
| Autor: | Anne G. Rosenfeld, Mary P. Davis, Sheila M. Gephart, Kimberly M. Shea, Barbara B. Brewer, Jane M. Carrington |
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| Rok vydání: | 2019 |
| Předmět: |
030504 nursing
business.industry Data Science Data science Terminology Data-driven Nursing Research 03 medical and health sciences 0302 clinical medicine Nursing Multidisciplinary approach Coursework Health care ComputingMilieux_COMPUTERSANDEDUCATION Curriculum development Humans Curriculum 030212 general & internal medicine Sociology Doctoral education 0305 other medical science business Education Nursing Graduate General Nursing |
| Zdroj: | Nursing Outlook. 67:39-48 |
| ISSN: | 0029-6554 |
| DOI: | 10.1016/j.outlook.2018.10.007 |
| Popis: | Background Building on the efforts of the American Association of Colleges of Nursing, we developed a model to infuse data science constructs into doctor of philosophy (PhD) curriculum. Using this model, developing nurse scientists can learn data science and be at the forefront of data driven healthcare. Purpose Here we present the Data Science Curriculum Organizing Model (DSCOM) to guide comprehensive doctoral education about data science. Methods Our team transformed the terminology and applicability of multidisciplinary data science models into the DSCOM. Findings The DSCOM represents concepts and constructs, and their relationships, which are essential to a comprehensive understanding of data science. Application of the DSCOM identified areas for threading as well as gaps that require content in core coursework. Discussion The DSCOM is an effective tool to guide curriculum development and evaluation towards the preparation of nurse scientists with knowledge of data science. |
| Databáze: | OpenAIRE |
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