From Diagnostic Analysis to Classroom Improvement: A Strategy-Based Approach to Enhancing Student Satisfaction in Face-to-Face Interactive Learning

This study examined how diagnostic analysis could be translated into classroom improvement to enhance student satisfaction in face-to-face interactive learning among media undergraduates at a private university in Shanghai, China. The study adopted a strategy-based design using a structured questionnaire validated through Item-Objective Congruence (IOC) and pilot testing (n = 35). In the baseline stage, survey data were collected from 90 students, and Multiple Linear Regression (MLR) was used to examine the effects of six predictors: Class Interaction Enjoyment (CIE), Teacher-Student Interaction (TSI), Teaching Care (TC), Information Quality (IQ), Service Efficiency (SE), and Teaching Quality (TQ) on Student Satisfaction. Based on the baseline findings, a 10-week Strategic Plan stage was implemented with a subgroup of 30 students, Paired-sample t-tests were conducted to compare students’ perceptions before and after the strategy stage. The regression model explained 74.5% of the variance in Student Satisfaction. Among the six predictors, CIE, IQ, and SE had significant positive effects, whereas TSI, TC, and TQ were not statistically significant in the baseline model. After the Strategic Plan stage, significant improvements were found in CIE, TC, IQ, SE, and overall Student Satisfaction, while TSI and TQ remained relatively stable. These findings suggest that baseline diagnostic evidence can be used not only to explain student satisfaction, but also to inform feasible classroom-level improvement in face-to-face interactive learning. The study therefore offers a strategy-based approach for linking empirical diagnosis with short-cycle instructional refinement in a resource-constrained private higher education context.