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Predictors of Community College Stud...

Rudnick, Virginia Rae,

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Predictors of Community College Student Attrition /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Predictors of Community College Student Attrition // Virginia Rae Rudnick.
Author:	Rudnick, Virginia Rae,
Description:	1 electronic resource (201 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-12, Section: A.
Contained By:	Dissertations Abstracts International86-12A.
Subject:	Community college education. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32046927
ISBN:	9798315793342

Predictors of Community College Student Attrition /
Rudnick, Virginia Rae,

Predictors of Community College Student Attrition /Virginia Rae Rudnick. - 1 electronic resource (201 pages)

Source: Dissertations Abstracts International, Volume: 86-12, Section: A.

This quantitative correlational-predictive study examined if or to what extent age, high school academic performance, enrollment status, educational goal, and college academic performance individually predict the attrition of first-time matriculated students from a public community college in New York State. The Non-Traditional Undergraduate Student Attrition Model provided the theoretical framework for the research. The sample included archival data for 254 students who were enrolled during the Fall 2022 term at the site institution, a public community college in central New York State, who were first-time, non-transfer, associate degree seeking, 18 years of age or older. The research questions considered if or to what extent each predictor variable individually predicted the attrition of first-time matriculated students from a public community college. The predictor variables included: age, high school academic performance (operationally defined as high school grade average), enrollment status (full- or part-time), educational goal (student's primary reason for enrolling at site institution), and college academic performance (first-term college GPA). Results from the binomial logistic regression indicate that the model was statistically significant, X2(7) = 92.780, p < .001. The model explained between 30.6% (Cox & Snell R2) and 40.8% (Nagelkerke R2) of the variance in attrition. The percentage accuracy in classification was 75.2%, sensitivity was 66.9%, specificity was 83.1%, positive predictive value was 79.0%, and negative predictive value was 72.5%. First-term college GPA was a statistically significant predictor of student attrition, while the other predictor variables were not statistically significant predictors of attrition.

English

ISBN: 9798315793342Subjects--Topical Terms:

2122836
Community college education.
Subjects--Index Terms:

Attrition

Predictors of Community College Student Attrition /
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245 1 0 $a Predictors of Community College Student Attrition / $c Virginia Rae Rudnick.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2025
300 $a 1 electronic resource (201 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 86-12, Section: A.
500 $a Advisors: Eskelinen, Holli Committee members: Davidson, Phillip; Leahy, Elise.
502 $b D.B.A. $c Grand Canyon University $d 2025.
520 $a This quantitative correlational-predictive study examined if or to what extent age, high school academic performance, enrollment status, educational goal, and college academic performance individually predict the attrition of first-time matriculated students from a public community college in New York State. The Non-Traditional Undergraduate Student Attrition Model provided the theoretical framework for the research. The sample included archival data for 254 students who were enrolled during the Fall 2022 term at the site institution, a public community college in central New York State, who were first-time, non-transfer, associate degree seeking, 18 years of age or older. The research questions considered if or to what extent each predictor variable individually predicted the attrition of first-time matriculated students from a public community college. The predictor variables included: age, high school academic performance (operationally defined as high school grade average), enrollment status (full- or part-time), educational goal (student's primary reason for enrolling at site institution), and college academic performance (first-term college GPA). Results from the binomial logistic regression indicate that the model was statistically significant, X2(7) = 92.780, p < .001. The model explained between 30.6% (Cox & Snell R2) and 40.8% (Nagelkerke R2) of the variance in attrition. The percentage accuracy in classification was 75.2%, sensitivity was 66.9%, specificity was 83.1%, positive predictive value was 79.0%, and negative predictive value was 72.5%. First-term college GPA was a statistically significant predictor of student attrition, while the other predictor variables were not statistically significant predictors of attrition.
546 $a English
590 $a School code: 1582
650 4 $a Community college education. $3 2122836
650 4 $a Higher education administration. $3 2122863
650 4 $a Educational evaluation. $3 526425
653 $a Attrition
653 $a Binomial logistic regression
653 $a Community college
653 $a Enrollment status
653 $a High school average
653 $a Retention
690 $a 0310
690 $a 0446
690 $a 0275
690 $a 0443
710 2 $a Grand Canyon University. $b College of Doctoral Studies. $e degree granting institution. $3 3759077
720 1 $a Eskelinen, Holli $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-12A.
790 $a 1582
791 $a D.B.A.
792 $a 2025
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