Predicting students' satisfaction with academic services at a multicultural engineering university in Bangladesh: A multiple regression analysis.

Abstract

This empirical study sought to determine the levels of satisfaction among engineering students enrolled at a multicultural international institution in Bangladesh with a reputation for excellence. An assortment of first- and fourth-year undergraduate students participated in the study by completing an online survey. The study focused on selected determinants namely; support services (SS), campus life (CL), economic factors (EF) and University corporate image (CI). The researchers used a survey research design (SRD) to illuminate students' opinions and views. A multiple regression analysis (MRA) was used to regress opinions of 326 respondents who participated in the study. The disproportional stratified random sampling was used to determine the samples. The study was guided by two hypotheses. The study analyzed predictors of student satisfaction with academic services by employing standard multiple regression analysis. The findings showed that the four determinants SS, CL, EF and CI were statistically significant to predict students' satisfaction levels [F(4,321) = 143.786, p < .001]. It was empirically discovered that Support Services had the highest impact to the model [β = .496, p < .05] followed by university Corporate Image [β = .365, p < .05]. The findings showed that Campus Life and Economic Factors were not statistically significant (p>.05) in the model of predictors implying that they do not influence students' satisfaction levels on their academic career at the university. The researchers recommend that in order to maintain students' satisfaction levels on their academic experiences, universities should consolidate on support services provided to the students as well as improving their corporate image and world view.