Evaluación económica de intervenciones educativas en la LOMLOE: propuestas de mejora con inteligencia artificial




* Organic Law 3/2020, of 29 December, which amends Organic Law 2/2006, of 3 May, on Education (LOMLOE).

This research aims to demonstrate the need for an economic evaluation of the Or­ganic Law that modifies the Organic Law of Education (LOMLOE), especially after the in­vestment of EU Next Generation funds that open new opportunities that were lacking in the initial drafting of the law. The challenge for Public Administrations is to use this addi­tional investment efficiently.

Our analysis shows that artificial intelli­gence models can predict whether educational support programmes will help increase the like­lihood that students who lag behind will pass the 4th grade of ESO (Compulsory Secondary Education). In this way, we can calculate the social return of one of these programmes and contribute to their ex-ante design to achieve higher success rates for students.

To complement the models already used by Public Administrations, we use robust Machine Learning (ML) models such as CHAID decision trees and artificial neural networks to analyse the characteristics of the groups of students and the interven­tion they have been part of. The conclusions allow us to improve educational reinforce­ment programmes in the coming years to support students with lower chances of ac­ademic success.

Please, cite this article as follows: Ballestar, M. T., Sainz, J., & Sanz, I. (2022). Evaluación económica de intervenciones educativas en la LOMLOE: propuestas de mejora con inteligencia artificial |An economic evaluation of educational interventions in the LOMLOE*: Proposals for improvement with artificial intelligence. Revista Española de Pedagogía, 80 (281), 139-160. 10.22550/REP80-1-2022-09

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Author Biography

María Teresa Ballestar holds a de­gree in Statistics from the University of Zaragoza, a degree in Market Research and Techniques and a Master’s degree in Information and Knowledge Society from the Universitat Oberta de Catalunya. PhD in Big Data methodologies and tech­nologies applied to Economics at the Uni­versidad Rey Juan Carlos. She is also an Associate Professor at the Universidad Rey Juan Carlos. In recent years she has held management positions and led pro­jects in digital transformation, innovation, data analytics and data science. She has published more than a dozen scientific pa­pers and collaborated with various media.


Jorge Sainz Orcid holds a degree in Economics from the Universidad Com­plutense de Madrid and in Law from the UNED. He holds a PhD in Economics (URJC) and an MBA (specialising in finance and pub­lic policy) from the Simon School, University of Rochester. He is Professor of Applied Eco­nomics at the Universidad Rey Juan Carlos de Madrid and Visiting Fellow at the Institute for Policy Research, University of Bath.

He has been Advisor to the Cabinet of the Regional Minister of Education and General Deputy Director of Research at the Regional Ministry of Education of the Community of Madrid. In the Ministry of Education, Culture and Sport he has been General Director of University Policy and General Secretary of Universities.


Ismael Sanz is Associate Professor in the Department of Applied Economics I at the Universidad Rey Juan Carlos. He holds a PhD in Applied Economics from the Faculty of Economics and Business Studies at the Universidad Complutense de Madrid (UCM). He has been General Director of Innovation, Scholarships and Grants of the Ministry of Education of the Community of Madrid, Director of the Na­tional Institute for Educational Evaluation (INEE) of the Ministry of Education, Cul­ture and Sport (2012-2015) and Chair of the Strategic Development Group of PISA of the OECD. He is currently Vice-Rector for Quality at the URJC. Author of articles in high impact research journals.


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Creative Commons Attribution-NonCommercial 4.0 International License

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Palabras clave | Keywords

educationalefficiency, Publicpolicyanalysis