Using AI for developing personalized learning paths

Leon Ramona-Diana (), Ortiz Ángel (), Díaz Mª del Mar Alemany () and Alvarez Ana Esteso ()
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Leon Ramona-Diana: Research Center on Production Management and Engineering, Universitat Politècnica de València, Spain
Ortiz Ángel: Research Center on Production Management and Engineering, Universitat Politècnica de València, Spain
Díaz Mª del Mar Alemany: Research Center on Production Management and Engineering, Universitat Politècnica de València, Spain
Alvarez Ana Esteso: Research Center on Production Management and Engineering, Universitat Politècnica de València, Spain

International Journal of Advanced Statistics and IT&C for Economics and Life Sciences, 2024, vol. 14, issue 1, 13-19

Abstract: This research aims to examine how artificial intelligence (AI) can be used within the educational framework for developing personalized learning paths. In order to achieve this goal, an etic approach is employed, and a qualitative-quantitative perspective is adopted. Thus, following the PRISMA guidelines, 71 articles published on Web od Science, during January 2014 – June 2024, are selected and analysed using cluster and density analysis. The results bring forward that the peak of the scientific production was reached in 2022 and that the topic is more appealing to the scholars from the information technology field than to the ones from the educational area. Furthermore, two lines of research can be identified; one that is technology-driven and another one that is learner/human-driven. Further research is required in providing a nexus between the two of them since, in the context of Industry 5.0 and Society 5.0, AI could act as a bridge. This research has several implications. On the one hand, it emphasizes the topics that captured scholars’ attention and also various research gaps that should be addressed. On the other hand, it extends the research from the educational management area by highlighting how AI could facilitate the transition towards the implementation of the connectivism learning theories.

Keywords: Artificial intelligence; Personalized learning path; Industry 5.0 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:ijsiel:v:14:y:2024:i:1:p:13-19:n:1001

DOI: 10.2478/ijasitels-2024-0001

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