Evaluation of undergraduate academic programs through data envelopment analysis and time-to-degree estimates at Spanish public universities
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Salas Velasco, ManuelEditorial
Elsevier
Materia
Data envelopment analysis Duration analysis Higher education
Date
2024-03-29Referencia bibliográfica
M. Salas-Velasco Evaluation of undergraduate academic programs through data envelopment analysis and time-to-degree estimates at Spanish public universities 93 (2024) 101878 [https://doi.org/10.1016/j.seps.2024.101878]
Sponsorship
Funding for open access charge: Universidad de Granada / CBUAAbstract
This article proposes nonparametric and parametric methods for conducting meaningful evaluations of academic
programs. In particular, it proposes the use of data envelopment analysis (DEA) along with regression analysis for
the evaluation of Spanish public universities’ undergraduate curricula. Unlike the radial DEA models, which
assume an equiproportional expansion of all outputs to achieve efficiency, the current study also relies on the use
of non-radial DEA models for assessing the efficiency of Spanish public universities. A non-radial DEA measure
(the so-called Russell measure) allows for unlike proportional augmentations in each positive output. In this
study, non-radial DEA measures allow us to identify different levels of inefficiency for each output considered
(social sciences and non-social sciences degrees). Specifically, the results show that the inefficiency in the production
of scientific and technical degrees is greater than that in the production of humanities and social sciences
degrees, although there are differences among institutions. Bachelor’s degree production time is also estimated,
and a duration analysis explains the time to degree. A worrying result is the "excessive" time it takes for a
university to produce four-year undergraduate degree programs. The mean graduation time is 5.7 years. The Cox
proportional hazards regression shows that a shorter time to graduation is associated with higher teaching
quality as well as a higher faculty-to-student ratio. Parametric survival analysis using a lognormal distribution
with gamma frailty also verifies these latter results.