Assessing Student Satisfaction: An Application of Logistic Regression Analysis to Methodist University College Ghana (MUCG) Data

by Open Science Repository Mathematics
(December 2013)

Abstract

Determining students’ satisfaction is an essential concern especially for university administration, in order to advance student services and opportunities as well as creating a good image for the university itself. For the purpose of this study, the data was extracted from the faculties of Methodist University College Ghana during the 2011/2012 academic year. Student satisfaction questionnaire was admitted to a total of 500 university students, consisting of 325 female and 175 male students, and satisfaction was measured by asking students to respond to 21 questionnaire items. Here, we analyzed the data by employing logistic regression techniques. In the analysis, it was found that the explanatory variables such as registration, department, electives, facilities, union, scholarship, decision, delegates, websites, consultancy, environment, library, teaching assistance, and parking space were significantly associated with student’s satisfaction at the university. That is, students satisfied with these explanatory variables turns out to be satisfied with the university in general. In addition, the overall accuracy of the classification was found to be 84.0%.

Keywords: students’ satisfaction, logistic regression, explanatory variable.

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Assessing Student Satisfaction: An Application of Logistic Regression Analysis to Methodist University College Ghana (MUCG) Data