CLUSTER PROFILES OF ACTIVE LEARNING AND ACADEMIC ENGAGEMENT IN ECUADORIAN TECHNICAL EDUCATION
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Abstract
Most quantitative research on active learning methodologies (ALM) and academic engagement (AE) in higher education compares predefined groups, such as academic programs, using a variable-centered logic that reports average differences between categories the researcher already knows. This study instead asks a person-centered question: do naturally occurring configurations of students exist within a single technical and technological higher education institution, independent of the program they are enrolled in? Using data from 130 students across six academic programs at an Ecuadorian technical and technological higher education institute, hierarchical (Ward's method) and k-means cluster analysis were applied to seven ALM and AE subdimension scores. A three-cluster solution was retained based on silhouette width, the Calinski-Harabasz index, and bootstrap stability (adjusted Rand index = .957 across 200 resamples): a Critically Disengaged profile (n = 13, 10.0%; ALM and AE means near 1.3 of 5), a Moderate-Favorable profile (n = 58, 44.6%; means near 3.9-4.0), and a Highly Engaged profile (n = 59, 45.4%; means near 4.8). Cluster membership was statistically independent of academic program (chi-square = 15.21, df = 10, p = .125) and gender (chi-square = 1.82, df = 2, p = .402), indicating that these profiles cut across, rather than coincide with, the program-based differences documented in a companion comparative study using the same dataset. The findings suggest that a small but identifiable subgroup of students combines low active-learning exposure with low engagement regardless of program, a pattern invisible to between-program comparisons alone, with direct implications for targeted, rather than program-wide, institutional support.
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