An extended End-User Computing Satisfaction model for learning systems in higher education
Journal
Frontiers in Education
ISSN
2504-284X
Publisher
Frontiers Media SA
Date Issued
2026
Author(s)
Gregori, Andres
Rivera-López, Mauricio
Noguez, Julieta
Type
text::journal::journal article
Abstract
Background: This study reports an exploratory, single-institution scale-development pilot of a learner-centered extension to the End-User Computing Satisfaction (EUCS) framework, hereafter EUCS-LS, that adds three candidate dimensions, user participation, technical support, and multimodal accessibility, to the five classic EUCS dimensions for use with higher-education learning systems. Methods: A cross-sectional pilot survey was administered to undergraduate students at one private university using stratified sampling with a proportional allocation target across ten faculties; after deduplicating by student ID, the analytic sample was N=394. Each of the eight constructs was operationalized as a single-item indicator. Joint covariation with overall satisfaction was assessed using hierarchical OLS regression with an intercept, principal component analysis, single-factor maximum-likelihood exploratory factor analysis, partial least squares regression with Variable Importance in Projection (VIP) scores, and post-stratification weighted least squares as a sensitivity check. Variance inflation factors, the Kaiser-Meyer-Olkin measure, Bartlett’s test of sphericity, and scale-level Cronbach’s alpha were used as diagnostics, and the OLS assumptions (linearity, normality, homoscedasticity, and independence of residuals across faculties) were tested formally, with heteroscedasticity-consistent (HC3) and faculty-clustered standard errors estimated as robustness checks. Results: The eight items jointly accounted for 62.1% of the variance in overall satisfaction (adjusted R2; F(8,385)=81.50, p<.001), and adding the three candidate learner-centered items to the classic block produced a small block-level gain (ΔR2=0.041, F-change(3,385)=14.24, p<.001). Seven of the eight items reached the p<.05 threshold; timeliness did not (p=.093). Collinearity diagnostics were unproblematic (all VIF between 1.75 and 2.24), yet the predictors shared a single dominant covariance pattern: one principal component captured 59.0% of their joint variance, PLS VIP scores fell within a narrow band (0.928–1.091, spread 0.16), and treating the eight constructs as items of one general scale yielded Cronbach’s alpha=0.900. Formal assumption tests supported linearity and independence, detected mild non-normality and heteroscedasticity, and the substantive conclusions were preserved under robust standard errors. Together, these diagnostics indicate that the predictor set behaves as a single general perceived-quality factor with several correlated facets and that the rank order of individual coefficients is not statistically identifiable at this sample size. © The authors ©Frontiers Media SA
License
Acceso Abierto
How to cite
Gregori A, Rivera-López M, Noguez J, Escobar-Castillejos D and Barrera-Animas AY (2026) An extended End-User Computing Satisfaction model for learning systems in higher education. Front. Educ. 11:1871433. doi: 10.3389/feduc.2026.1871433