Abstract

Emerging technology has the power to impact institutions of higher education using predictive analytics. It is critical that nursing programs admit students with the highest probability of success. This study identified relationships between independent variables related to pre-nursing requirements and the dependent variable of successful completion of the nursing program.

Description

45th Biennial Convention 2019 Theme: Connect. Collaborate. Catalyze.

Author Details

Amanda L. Veesart, PhD, RN, CNE - School of Nursing, Texas Tech University Health Sciences Center, Lubbock, TX, USA; Kathryn Sridaromont, PhD, RN - Traditional BSN Program, Texas Tech University Health Sciences Center, Lubbock, TX, USA; Sharon Cannon, EdD, RN, ANEF - School of Nursing, Texas Tech University Health Sciences Center, Odessa, TX, USA

Sigma Membership

Non-member

Lead Author Affiliation

Texas Tech University Health Sciences Center, Lubbock, Texas, USA

Type

Poster

Format Type

Text-based Document

Study Design/Type

N/A

Research Approach

N/A

Keywords:

Admissions, Predicting Success in Nursing School, Predictive Models

Conference Name

45th Biennial Convention

Conference Host

Sigma Theta Tau International

Conference Location

Washington, DC, USA

Conference Year

2019

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.

All permission requests should be directed accordingly and not to the Sigma Repository.

All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Acquisition

Proxy-submission

Additional Files

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How to use emerging technology to predict success in undergraduate nursing programs

Washington, DC, USA

Emerging technology has the power to impact institutions of higher education using predictive analytics. It is critical that nursing programs admit students with the highest probability of success. This study identified relationships between independent variables related to pre-nursing requirements and the dependent variable of successful completion of the nursing program.