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Predicting Student Performance to Help the Groups at Risk

Ifte Choudhury Texas A&M University College Station, TX

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The purpose of this study was to examine the effects of overall academic capability of students on their performance in the Environmental Control Systems courses offered by the Department of Construction Science, Texas A&M University. It is indicated by a number of studies that student performance is affected the overall academic capability of a student, measured by Grade Point Average. Some other studies suggest that student characteristics, class size, and the major pursued by the student are also correlated with student performance in a course. The study population consisted of the students who attended the Environmental Control System courses in Fall, Spring, and Summer semesters from 1997 through 2001. Sample size of the study was 329 students. Relevant data was collected from the Student Information Management System database of the university. In order to obtain a better fit of the data, a quadratic term of the independent variable was used in the model. The data was analyzed using a simple regression analysis procedure. The findings generated from the analysis of the data indicated that overall academic capability and the major of a student have statistically significant effects on student performance in the Environmental Control Systems courses. The model conceived could be used for predicting student performance in these courses in order to enable the instructors to formulate teaching strategies geared toward helping the students at risk.

I. Statement of the problem

The Department of Construction Science within the College of Architecture at Texas A&M University offers Environmental Control Systems courses at an undergraduate level. The courses deal with building sub-systems such as HVAC (heating, ventilating, and air-conditioning), plumbing, lighting, and electrical wiring. Students completing these courses should be able to design these sub-systems and integrate them with the total building systems. It appeared that the students with higher academic capabilities performed better in the courses.

Studies on education indicate that any particular course grade is positively correlated with overall grade point average. Findings by Seymour et al. 1 reveal that most significant factor in predicting success in a business microcomputer course is the overall grade point average of a student. Similar findings have been reported by Rose et al. 2 in a study of student performance in an introductory psychology course. Vaidyanathan et.al. 3 have

Proceedings of the 2002 American Society for Engineering Education Annual Conference & Exposition Copyright © 2002, American Society for Engineering Education

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Choudhury, I. (2002, June), Predicting Student Performance To Help The Groups At Risk Paper presented at 2002 Annual Conference, Montreal, Canada. 10.18260/1-2--11128