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Identification of cognitive and non-...

Hayes, Catherine.

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Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi./
Author:	Hayes, Catherine.
Description:	53 p.
Notes:	Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1395.
Contained By:	Dissertation Abstracts International66-03B.
Subject:	Health Sciences, Nursing. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3167299
ISBN:	0542026708

Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi.
Hayes, Catherine.

Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi. - 53 p.

Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1395.

Thesis (Ed.D.)--Delta State University, 2005.

This study sought to identify a variable or variables predictive of attrition among baccalaureate nursing students. The study was quantitative in design and multivariate correlational statistics and discriminant statistical analysis were used to identify a model for prediction of attrition. The analysis then weighted variables according to their predictive value to determine the most parsimonious model with the greatest predictive value.

ISBN: 0542026708Subjects--Topical Terms:

1017798
Health Sciences, Nursing.

Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi.
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100 1 $a Hayes, Catherine. $3 1939602
245 1 0 $a Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi.
300 $a 53 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1395.
500 $a Chair: Camille Baker Branton.
502 $a Thesis (Ed.D.)--Delta State University, 2005.
520 $a This study sought to identify a variable or variables predictive of attrition among baccalaureate nursing students. The study was quantitative in design and multivariate correlational statistics and discriminant statistical analysis were used to identify a model for prediction of attrition. The analysis then weighted variables according to their predictive value to determine the most parsimonious model with the greatest predictive value.
520 $a Three public university nursing education programs in Mississippi offering a Bachelors Degree in Nursing were selected for the study. The population consisted of students accepted and enrolled in these three programs for the years 2001 and 2002 and graduating in the years 2003 and 2004 (N = 195).
520 $a The categorical dependent variable was attrition (includes academic failure or withdrawal) from the program of nursing education. The ten independent variables selected for the study and considered to have possible predictive value were: Grade Point Average for Pre-requisite Course Work; ACT Composite Score, ACT Reading Subscore, and ACT Mathematics Subscore; Letter Grades in the Courses: Anatomy & Physiology and Lab I, Algebra I, English I (101), Chemistry & Lab I, and Microbiology & Lab I; and Number of Institutions Attended (Universities, Colleges, Junior Colleges or Community Colleges).
520 $a Descriptive analysis was performed and the means of each of the ten independent variables was compared for students who attrited and those who were retained in the population. The discriminant statistical analysis performed created a matrix using the ten variable model that was able to correctly predicted attrition in the study's population in 77.6% of the cases. Variables were then combined and recombined to produce the most efficient and parsimonious model for prediction. A six variable model resulted which weighted each variable according to predictive value: GPA for Prerequisite Coursework, ACT Composite, English I, Chemistry & Lab I, Microbiology & Lab I, and Number of Institutions Attended.
520 $a Results of the study indicate that it is possible to predict attrition among students enrolled in baccalaureate nursing education programs and that additional investigation on the subject is warranted.
590 $a School code: 0877.
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773 0 $t Dissertation Abstracts International $g 66-03B.
790 1 0 $a Branton, Camille Baker, $e advisor
790 $a 0877
791 $a Ed.D.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3167299