A model to evaluate data science in nursing doctoral curricula

Kimberly D. Shea; Barbara B. Brewer; Jane M. Carrington; Mary Davis; Sheila Gephart; Anne Rosenfeld

doi:10.1016/j.outlook.2018.10.007

A model to evaluate data science in nursing doctoral curricula

Kimberly D. Shea, Barbara B. Brewer, Jane M. Carrington, Mary Davis, Sheila Gephart, Anne Rosenfeld

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	39-48
Number of pages	10
Journal	Nursing outlook
Volume	67
Issue number	1
DOIs	https://doi.org/10.1016/j.outlook.2018.10.007
State	Published - Jan 1 2019

Keywords

PhD education
curriculum
data science
framework
nursing
nursing informatics

ASJC Scopus subject areas

General Nursing

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10.1016/j.outlook.2018.10.007

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title = "A model to evaluate data science in nursing doctoral curricula",

abstract = "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.",

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AU - Brewer, Barbara B.

AU - Carrington, Jane M.

AU - Davis, Mary

AU - Gephart, Sheila

AU - Rosenfeld, Anne

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

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KW - PhD education

KW - curriculum

KW - data science

KW - framework

KW - nursing

KW - nursing informatics

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A model to evaluate data science in nursing doctoral curricula

Abstract

Keywords

ASJC Scopus subject areas

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