An innovative interdisciplinary approach to spatial modeling of student satisfaction from online courses

Introduction Student satisfaction is a critical metric for assessing the success of online courses. Understanding the factors influencing satisfaction allows educational institutions and faculty staff to take steps to improve the quality of training, which can lead to higher student engagement and retention and improved institutional reputation. Methods We examine the relationship between 213 students' satisfaction with the quality of an online course in Object-Oriented Programming developed to support traditional training, course grades, and in-course activity. Data analysis was conducted using a combination of classical (descriptive statistics, correlation analyses, and t-tests) and innovative methods. To provide a more nuanced analysis than traditional averages allow, we proposed a vector-based model to measure both the “total intensity” (overall strength) of satisfaction and the “structure of perception” (the balance and consistency across different areas). This integrated approach considers satisfaction a multidimensional and structured perception, revealing manifest and latent dependencies. Results The empirical findings reveal that student satisfaction is largely independent of academic performance; there was almost no correlation between satisfaction intensity and final course grades ( r =0.0255), suggesting that students evaluate course quality objectively regardless of their personal success. Despite the weak positive correlation ( r = 0.2042), there is a tendency for the satisfaction structure to become unbalanced as activity increases. More active students, who study more course material and complete more assignments, are more likely to notice inconsistencies or weaknesses in organisation, content, or grading, leading to more complex and sometimes contradictory perceptions. The study introduces a Satisfaction by Intensity and Orientation index (SIO-index) to quantify these multidimensional perceptions. Discussion Based on these results, the paper provides recommendations for enhancing course design to better align with student expectations and foster engagement. Future research may focus on empirically validating the model in different educational contexts and exploring relationships of the satisfaction space and other key variables.