000147073 001__ 147073
000147073 005__ 20241205091044.0
000147073 0247_ $$2doi$$a10.1057/s41599-024-04040-y
000147073 0248_ $$2sideral$$a140881
000147073 037__ $$aART-2024-140881
000147073 041__ $$aeng
000147073 100__ $$0(orcid)0000-0001-8471-9415$$aEscolano-Perez, Elena$$uUniversidad de Zaragoza
000147073 245__ $$aUsing artificial intelligence in education: decision tree learning results in secondary school students based on cold and hot executive functions
000147073 260__ $$c2024
000147073 5060_ $$aAccess copy available to the general public$$fUnrestricted
000147073 5203_ $$aImproving educational quality is a universal concern. Despite efforts made in this regard, learning outcomes have not improved sufficiently. Therefore, further investigation is needed on this issue, adopting new perspectives (conceptual and analytical) to facilitate the understanding and design of effective actions. The objective of this study was to determine the influence of executive functions (considering both cognitive and affective processes) and their interactions on learning outcomes in Language and Literature and Mathematics in Spanish students, through the use of artificial intelligence, based on the machine learning approach, and more specifically, the decision tree technique. A total of 173 students in compulsory secondary education (12–17 years old) from the same educational institution participated. The school’s educational counsellor provided information on student executive function levels by completing the BRIEF2 questionnaire for each participant. She also reported on the learning outcomes achieved by students in the subjects of interest for this research (Language and Literature and Mathematics). R software was used to model the regression trees. The results revealed groups of students characterised by different profiles, i.e., by different combinations of difficulties in various executive functions and varying levels of learning outcomes in each academic area. However, regardless of the academic area considered (Language and Literature or Mathematics), working memory was identified as the most relevant executive function in all of the students’ learning outcomes. Understanding the combination of executive functions that predict learning outcomes in each group of students is important since it enables teachers and other educational professionals, policymakers and researchers to provide individualised educational resources according to the diverse student profiles and needs. It constitutes an effective mechanism to improve students’ learning results and, ultimately, to enhance an equitable and more effective educational system.
000147073 536__ $$9info:eu-repo/grantAgreement/ES/DGA/S49-23R$$9info:eu-repo/grantAgreement/ES/MCIU-AEI-FEDER/PGC2018-098742-B-C31
000147073 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000147073 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000147073 700__ $$aLosada, José Luis
000147073 7102_ $$14009$$2735$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Psicolog.Evolut.Educac
000147073 773__ $$g11 (2024), 1563 [13 pp.]$$pHumanit. soc. sci. commun.$$tHumanities & social sciences communications$$x2662-9992
000147073 8564_ $$s968972$$uhttps://zaguan.unizar.es/record/147073/files/texto_completo.pdf$$yVersión publicada
000147073 8564_ $$s1771742$$uhttps://zaguan.unizar.es/record/147073/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000147073 909CO $$ooai:zaguan.unizar.es:147073$$particulos$$pdriver
000147073 951__ $$a2024-12-05-08:47:41
000147073 980__ $$aARTICLE