Multidimensional Assessment of Professional Internships in Construction Engineering (UMAG, 2011-2022): A Comparative Study of Traditional vs. transferable credits (TC) Models

Abstract

This research study compares the psychometric properties of the traditional evaluation model (average of six dimensions) and an innovated model based on Transferable Credits (TC) (five weighted components) applied to Construction Engineering students at the University of Magallanes (UMAG), Chile. An instrumental study was conducted with 56 students in their professional internship, 28 evaluated with the traditional model (2011–2015 cohort) and 28 with the innovated TC model (2018–2022 cohort). Cohen’s d, correlation matrix, t test, coefficient of variation (CV), variance inflation factor (VIF), and an exploratory cluster analysis were computed. The comparison between cohorts showed a very large effect size (d = 1.80, p < 0.0001), and the innovated model exhibited greater discriminative capacity (CV = 8.3% vs 5.6%, equivalent to a 47.8% improvement). The Company component showed the highest correlation with the final grade (r = 0.68), followed by the Report assessment (r = 0.59) and Oral defense (r = 0.57), in line with ABET Student Outcomes 2, 6, and 3, respectively. The VIF analysis ruled out multicollinearity issues (mean VIF = 1.18), and the exploratory cluster analysis suggested six preliminary student profiles, although with low stability (ARI = 0.094) due to the small sample size. Consequently, the TC model shows a very large effect size and high discriminative capacity, providing robust evidence to support its implementation in Construction Engineering programs.