Doctor of Philosophy (PhD)


Human Resource Education and Workforce Development

Document Type



The construction industry is one of the largest providers of jobs in the United States. Between 2009 and 2013, approximately 20% of the 7.7 million Americans employed in construction related jobs (Bureau of Labor Statistics (BLS), 2009) would be eligible to retire. The industrial construction industry must attract, train, and retain a significant number of people to the construction industry. The primary purpose of this study was to determine the influence of selected personal demographic characteristics and academic behaviors of individuals participating in craft training courses offered by a large organization of member construction companies who successfully completed or left the construction training courses prior to its completion. The study used descriptive, comparative, and discriminant analytical statistical procedures to achieve the primary purpose. The population was defined as adult students who were enrolled in craft-training courses offered by one large organization of member construction companies during the 2008 Fall semester. Data was transferred from the training provider into a researcher design spreadsheet for analysis. The descriptive analysis found 96.6% of the respondents were male and 74.8% respondents were classified as non-metropolitan residents. Welding and Electrical crafts had the largest numbers of students enrolled. The comparative analyses found that crafts, craft levels, attendance, and grades tended to be related to course completion rates. Due to the findings that not all courses awarded grades, two discriminant analyses were used to identify substantively and statistically significant models that increased the researcher’s ability to explain the completion status of students enrolled in the craft training courses. The discriminant model for graded courses correctly classified 89.4% of the original grouped cases (completers and non-completers), which was a 64.8% improvement over chance. The discriminant model for non-graded courses correctly classified 83.0% of the original grouped cases (completers and non-completers), which was a 66.03% improvement over chance. The variable attendance had the greatest impact in both models. Since attendance was found to be related to completion status, the researcher recommended further studies on determining why students were absent from classes. Additionally the researcher recommends reviewing other possible variables that may influence students’ completion status.



Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Burnett, Michael F.