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Autor/inWheeler, Edward W.
TitelDetermination of a Predictive Model for the Fundamentals of Engineering Examination
Quelle(2012), (64 Seiten)
PDF als Volltext Verfügbarkeit 
Ed.D. Dissertation, The University of Memphis
Spracheenglisch
Dokumenttypgedruckt; online; Monographie
ISBN978-1-3031-8273-0
SchlagwörterHochschulschrift; Dissertation; Engineering; Engineering Education; Models; Prediction; Bachelors Degrees; Higher Education; Difficulty Level; Mathematics Education; Science Education; Predictor Variables; Grade Point Average; Educational Testing; Regression (Statistics); Tennessee
AbstractIn early 1995, the University of Tennessee at Martin (UTM) sought permission to terminate three existing engineering technology degree programs and replace them with a single Bachelor of Science in Engineering (BSE) degree. As part of the requirements to proceed with the implementation of an engineering program, the University of Tennessee system mandated the program be unique and different from any other engineering program in the state. In compliance with those guidelines, the curriculum was built with no separable majors. In addition, passing the Engineer-in-Training (now the Fundamentals of Engineering (FE)) examination was incorporated as a degree requirement. This examination tests fundamental knowledge of engineering. The requirement to pass the exam was viewed as a means to validate the content and rigor of the program. Also, in view of the fact that the BSE program was developed as a general engineering program, including the passing of the general FE examination was consistent with the goal of graduating engineers who would have a broad understanding of the basic fundamentals of engineering. Using logistic regression, this study identified the factors that influence the first-time pass rate on the Fundamentals of Engineering Exam (FE) at UTM. The study focused on the basic mathematics, science and engineering science courses that are part of the curriculum. Grades received in each course and the number of times each course is taken were considered as the influencing factors. The predictive model was built using SPSS's logistic regression forward stepwise likelihood ratio, backward stepwise likelihood ratio, and enter methods. In order to test the significance of each model developed, the null hypothesis, H[subscript 0]: The model can predict, was tested using the Hosmer-Lemeshow statistic, with a = 0.05. For each model developed, the calculated "p" was greater than 0.05 resulting in a model that was capable of predicting the pass/fail outcome. The variables remaining in the final model were prior semester GPA and the GPA in engineering economy using all attempts in the course. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.] (As Provided).
AnmerkungenProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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