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The prediction of dropout in an entry level trades training program

University of British Columbia

Withdrawal from a program of studies can have negative consequences that extend beyond those that directly affect the dropouts. Beyond the lack of employment related skills and the impact that dropping out may have on students' confidence in their ability as learners, attrition also has an effect on the educational institute and sponsoring agencies. For example, program attrition leaves the training provider with empty seats but no corresponding reduction in training costs and the sponsoring agencies with a limited return on their training investments. This study examined attrition in short-term vocational programs to determine if factors from research on other postsecondary populations are applicable to these kinds of students. A formula was also developed to predict, early in the program, which students are most likely to withdraw. A review of the research confirmed that what is known about factors related to attrition for students in short-term vocational programs is limited. This necessitated a "borrowing" of factors from research directed at high school students and those in adult and higher education programs. By means of a mailed questionnaire, and using institute records, data were collected for those factors relevant to the population and program under study. These factors were divided into those students brought with them and those they experienced after they began their training. Of the 36 pre-entry factors studied, 12 produced statistically significant relationships when compared to persistence/withdrawal. The significant factors included high school graduation; test scores on reading vocabulary, reading comprehension, reference skills, math computation, math concepts and applications, and combined reading and combined math scores; mean differences in age; the student's socioeconomic status; certainty of program choice; and locus of control as related to high school persistence/withdrawal. Of those categorized as postentry, 10 of the 28 factors produced statistically significant relationships when compared to the indicator variable. These factors were enough study time, study time compared to others, hours per week at PVI, tests passed per attempt, tests exceeded per attempt, feeling that friends had gained from the program, estimation of program success, financial concern, agency sponsorship, and the use of Training Consultants. Combining the statistically significant factors using multiple regression analysis produced a prediction formula which included tests passed per attempt, combined math scores, study time compared, age, and feeling that friends had gained from the program. Conclusions based upon the results of the study centered around the application of attrition factors from the study of other populations and the utility of prediction for practitioners. In essence, the researcher believes it is inappropriate to make assumptions regarding attrition by short-term vocational students based upon research findings from other populations. In addition, even though the findings which characterized persisters as "good students" indicate that attrition rates may be reduced by either restricting admission by students who do not fit the profile or by providing these students with additional support, the amount of variance accounted for (16 percent) based upon the results of the multiple regression analysis suggest caution be used in making any decision. The researcher concludes by recommending that future studies examine attrition by using a variety of research methods in an attempt to clarify which factors are related to student attrition.

Text

2011-02-04

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http://hdl.handle.net/2429/31102

Educational Studies

University of British Columbia

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