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This study addresses the persistent shortage of psychometrically validated instruments for assessing higher-order competencies in undergraduate microeconomics—skills central to sustainable human capital formation aligned with Sustainable Development Goal 4 (Quality Education). Its objective was to design and validate a brief multidimensional assessment based on Bloom's revised taxonomy, covering conceptual reasoning, graphical interpretation, and quantitative problem-solving. Using data from business undergraduates, a rigorous psychometric pipeline was implemented, including multidimensional screening, exploratory factor analysis, principal component analysis, Rasch (Item Response Theory, IRT; one-parameter logistic, 1 PL) calibration, and confirmatory factor analysis. The original 40-item pool was reduced to a parsimonious 12-item instrument while preserving measurement precision. In line with the Rasch model, items shared a common discrimination parameter, and difficulty estimates fell within the recommended −3 to +3 range. Item characteristic curves (ICCs) showed appropriate horizontal dispersion: conceptual items clustered at lower difficulty levels, graphical items displayed the widest distribution across the latent continuum, and quantitative items ranged from easy to moderate, with parallel slopes supporting 1 PL assumptions. The three-factor structure demonstrated excellent fit (RMSEA = 0.000; CFI = 1.000). Criterion validity was supported by regression results indicating that quantitative ability (standardized β = 0.363, p < 0.001) and conceptual understanding (standardized β = 0.238, p = 0.029) significantly predicted course performance, explaining 26.2% of grade variance. No differential item functioning by gender or cohort was observed. Overall, results confirm the multidimensional nature of economic cognition and provide a scalable Rasch-based framework for efficient competency diagnostics in quantitatively oriented disciplines.
Manuel Salas-Velasco (Sat,) studied this question.