Multidimensional patterns of learning in higher education: an evidence-based statistical analysis on thickness

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Patricia Moyota- Amaguaya
María Eugenia Rodríguez-Durán
Lina Morales-Rodas
Daniel Hernán Millán-Ramos

Resumen

We examined the multidimensional structure of constructs related to learning in Higher Education (HE) using an integrated statistical analysis. The aim was to understand whether Geertz's concept of depth description can be useful for improving English language proficiency. The model included cognitive, metacognitive, affective, and contextual scales in university students from different academic programs. To this end, we analyzed a set of standardized instruments, bibliographic resources, conceptual understanding, learning strategies, metacognitive regulation, cognitive performance, affective engagement, and demographic factors to measure the perceived improvement in English language proficiency. We collected data using descriptive statistics, distribution analysis, box plots, and pairwise correlation matrices to assess central tendency, as well as the potential for dispersion, skewness, and intervariate relationships. The results revealed heterogeneous distribution patterns, the presence of significant outliers, and non-normal behavior across several scales, particularly within the cognitive and metacognitive dimensions. Moderate and statistically significant correlations were identified between conceptual understanding and metacognitive strategies, as well as between metacognitive and affective dimensions, indicating a structural interdependence between learning processes.

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Multidimensional patterns of learning in higher education: an evidence-based statistical analysis on thickness. (2026). Encuentros. Revista De Ciencias Humanas, Teoría Social Y Pensamiento Crítico., 28 (septiembre-diciembre), 190-206. https://doi.org/10.5281/zenodo.21895447

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