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Analysis of institutional authors

Badenes-Olmedo, CarlosCorresponding AuthorEyzaguirre-Barreda, PaulAuthorGayoso-Cabada, JoaquinAuthor

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January 28, 2026
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ESQAD: A curriculum-aligned dataset for question answer generation in Spanish

Publicated to: KNOWLEDGE-BASED SYSTEMS. 335 115255- - 2026-02-28 335(), DOI: 10.1016/j.knosys.2025.115255

Authors:

Badenes-Olmedo, Carlos; Eyzaguirre-Barreda, Paul; Chu-Artzt, Noa; Gayoso-Cabada, Joaquin
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Affiliations

Univ Politecn Madrid, Dept Sistemas Informat, Madrid 28031, Spain - Author

Abstract

This paper presents ESQAD (Educational Spanish Question-Answer Dataset), an open-access resource for question-answer generation (QAG) in Spanish aligned with national curricula. ESQAD comprises 6980 expertcurated exam questions, 340 literary comprehension items, 47 legal FAQs, and 913 LLM-generated pairs validated in academic settings. The dataset covers diverse linguistic and cognitive features, including subject classification, question typologies, and Bloom-level complexity. We analyze lexical diversity, cognitive intent, and structure across subsets. The automatically generated portion was created with Bloom-guided prompts and large language models (LLMs), and evaluated through both computational metrics and classroom validation. Results show that cognitive-level control is reliable for factual recall but only partial for higher-order reasoning. All resources, including dataset, code, and validation tool, are publicly available. ESQAD provides a structured benchmark for curriculum-aware QAG in under-resourced languages, with applications in educational NLP, question generation, and adaptive learning.
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Keywords

Adaptive learningBloom's taxonomyEducational technologyExpert systemsQuestion answer generation

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal KNOWLEDGE-BASED SYSTEMS due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2026, it was in position 26/204, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Artificial Intelligence.

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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-09:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 4 (PlumX).
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (BADENES OLMEDO, CARLOS) and Last Author (GAYOSO CABADA, JOAQUIN).

the author responsible for correspondence tasks has been BADENES OLMEDO, CARLOS.

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Awards linked to the item

The authors would like to thank the Servicio de Innovacion Educativa of Universidad Politecnica de Madrid (UPM) for their support in facilitating the pilot evaluations conducted in real academic settings. This research was partially supported by the Universidad Politecnica de Madrid through the 2023-2024 Educational Innovation Project "Automatizacion de Evaluaciones: Desarrollo de Cuestionarios a traves de Procesamiento de Lenguaje Natural y Aprendizaje Automatico" (IE24.6109) . Additional support was provided by a Spanish Ministry of Education collaboration grant awarded to Noa Chu Artzt for contributions to dataset construction and validation (2023/2024 academic year) .
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