Student Exam Satisfaction: Examining the Impact of Registration, Communication, Center’s Infrastructure and Exam Center Management - Acharya, Krishna Prasad (International Journal of Humanities, Education, and Social Sciences, 2025)
Student satisfaction with examination processes serves as a key indicator of academic service quality in higher education. Recognizing that operational dimensions such as registration systems, communication, infrastructure, and management significantly influence student experiences, this study investigates their impact on examination satisfaction within the context of Tribhuvan University. A quantitative cross-sectional design was employed, targeting BBS second-year and MBS second-semester students at Shanker Dev Campus and Nepal Commerce Campus. Using convenience sampling, 538 valid responses were gathered through structured questionnaires. Pearson correlation and multiple regression analyses were conducted to assess the relationships between registration, communication, infrastructure, exam center management, and student exam satisfaction. Model diagnostics were performed to ensure analytical validity. Bivariate analysis revealed significant correlations between all independent variables and student satisfaction with examinations (p < 0.001); however, regression analysis identified only three significant predictors: exam center management (ECM) (β = 0.227, p < 0.001), student registration experience (SRE) (β = 0.103, p = 0.006), and communication effectiveness (CE) (β = 0.084, p = 0.027), jointly accounting for 17.8% of the variance in satisfaction (F = 38.545, p < 0.001). Diagnostic tests confirmed model adequacy, showing normality (K-S p = 0.193), homoscedasticity, absence of multicollinearity (VIF < 1.5), and no influential outliers (Cook’s D < 0.032). The findings suggest that operational efficiency in examination center management, registration systems, and communication channels is more critical to student satisfaction than physical infrastructure or teaching delivery. The study contributes novel insights by: (1) identifying ECM as the dominant predictor (22.7% effect) in resource-limited contexts, (2) demonstrating the statistical insignificance of infrastructure (ECI) when operational variables are controlled, and (3) offering diagnostic validation for satisfaction modeling in developing country settings.