Modeling First-Year Engineering Student Performance During the Pandemic
Pub. online: 23 September 2026
Type: Case Study, Application, And/or Practice Article
Open Access
Open Access
Area: Spatial and Environmental Statistics
Accepted
2 September 2026
2 September 2026
Published
23 September 2026
23 September 2026
Abstract
Prompted by social upheaval in 2019, Chile initiated its first foray into entirely online education. Subsequently, owing to the global pandemic in 2020, all activities underwent an unavoidable shift to digital platforms, both on a global scale and within the university context. In response to this novel distance-learning system, the university encountered and surmounted new challenges during the four semesters that were conducted in this modality. This paper examines from a spatial statistics perspective the academic performance of first-year students enrolled in basic science courses across all engineering majors at Universidad Técnica Federico Santa María (USM) in Chile. This article emphasizes students’ performance as a georeferenced variable in space and compares it with a regular semester in which lectures are conducted in a face-to-face format. In particular, we discuss (a) the spatial patterns observed in the two largest cities, (b) the social variables that are pertinent for the study, and (c) the quality and performance of conditionally autoregressive (CAR)-type processes in modeling multivariate lattice data. We also reflect on the opportunity to enhance the learning experience linked to the retention rate of freshman engineering students.
Supplementary material
Supplementary MaterialThe online Supplementary Material provides comprehensive details regarding the Moran index, the structure of matrix Λ, and the Bayesian inference framework employed in the estimation process. Additionally, we include the complete dataset used in the application, along with tables detailing supplementary results. Finally, this material features a dedicated section on the sensitivity study of the MCAR models.
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