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Predicting student success in a buil...

Orth, Daryl L.

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Predicting student success in a building construction management program.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Predicting student success in a building construction management program./
Author:	Orth, Daryl L.
Description:	99 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-10, Section: A, page: 3618.
Contained By:	Dissertation Abstracts International64-10A.
Subject:	Education, Industrial. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3108391

Predicting student success in a building construction management program.
Orth, Daryl L.

Predicting student success in a building construction management program. - 99 p.

Source: Dissertation Abstracts International, Volume: 64-10, Section: A, page: 3618.

Thesis (Ph.D.)--Purdue University, 2003.

The purpose of this dissertation was to: (1) identify the variables that prove to be the best predictors of graduation in the Building Construction Management (BCM) Department at Purdue University, (2) identify factors to use as a recruiting/marketing tool for the BCM program, (3) provide a basis for educators to better understand the selection criteria for admission of students in the field of construction, construction science, construction management, and construction technology, and (4) help other university construction management programs to identify predictor variables that can serve as valid predictors of college success for their own construction management programs.Subjects--Topical Terms:

1017516
Education, Industrial.

Predicting student success in a building construction management program.
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100 1 $a Orth, Daryl L. $3 1948163
245 1 0 $a Predicting student success in a building construction management program.
300 $a 99 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-10, Section: A, page: 3618.
500 $a Major Professors: James D. Russell; Duane D. Dunlap.
502 $a Thesis (Ph.D.)--Purdue University, 2003.
520 $a The purpose of this dissertation was to: (1) identify the variables that prove to be the best predictors of graduation in the Building Construction Management (BCM) Department at Purdue University, (2) identify factors to use as a recruiting/marketing tool for the BCM program, (3) provide a basis for educators to better understand the selection criteria for admission of students in the field of construction, construction science, construction management, and construction technology, and (4) help other university construction management programs to identify predictor variables that can serve as valid predictors of college success for their own construction management programs.
520 $a Logistic regression was the statistical procedure used to make an association among the independent predictor variables (high school rank, high school GPA, high school senior class size, number of high school science courses, number of high school math courses, SAT composite score, matriculation age, gender, race, and residence) and the dependent variable graduation. A sample of approximately 400 students who originally enrolled in Purdue University's BCM Department from the fall semester 1992 to the fall semester 1997 was used for this study. This relationship was tested using logistic regression at the 0.05 level of confidence. The results of the test show that two independent variables are significant: high school GPA and number of high school math semesters.
520 $a The following conclusions were derived from the results of this study: (1) the independent predictor variables number of high school math semesters, high school GPA, matriculation age, and SAT composite score were significant when they were the single independent variable in the model; (2) when all the independent predictor variables were grouped together in the combine model, only number of high school math semesters and high school GPA were significant; (3) matriculation age has a negative relationship and not a positive relationship with graduation; (4) SAT composite score was correlated with number of high school math semesters and high school GPA. As a result of this a fitted parameter model was developed for predicting the probability of a student graduating with a BCM baccalaureate degree.
590 $a School code: 0183.
650 4 $a Education, Industrial. $3 1017516
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773 0 $t Dissertation Abstracts International $g 64-10A.
790 1 0 $a Russell, James D., $e advisor
790 1 0 $a Dunlap, Duane D., $e advisor
790 $a 0183
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3108391