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The Application of Artificial Intelligence in Recommendation Systems Reinforced Through Assurance of Learning in Personalized Environments of e-Learning

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Information Systems and Technologies (WorldCIST 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 800))

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Abstract

Learning environments unquestionably enable learners to develop their pedagogical and scientific processes efficiently and effectively. Thus, considering the impossibility of not having conditions of autonomy over the routine underlying the studies and, consequently, not having guarantees of the learning carried out makes the learners experience gaps in the domain of materials adequate to their actual needs. The paper's objective is to present the relevance of the applicability of Artificial Intelligence in Recommendation Systems, reinforced through the Assurance of Learning, oriented towards adaptive-personalized practice in corporate e-learning contexts. The research methodology underlying the work fell on Design Science Research, as it is considered adequate to support the research, given the need to carry out the design phases, development, construction, evaluation, validation of the artefact and, finally, communication of the results. The main results instigate the development of an Adaptive-Personalized Learning framework for corporate e-learning, provided with models of Artificial Intelligence and guided using the Assurance of Learning process. It becomes central that learners can enjoy adequate academic development. In this sense, the framework has an implicit structure that promotes the definition of personalized attributes, which involves recommendations and customizations of content per profile, including training content that will be suggested and learning activity content that will be continuously monitored, given the specific needs of learners.

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Author information

Authors and Affiliations

  1. University of Tras-os-Montes and Alto Douro, Vila Real, Portugal

    Fernando Fresneda-Bottaro & Paulo Martins

  2. Universidade Aberta, Lisbon, Portugal

    Arnaldo Santos

  3. Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal

    Paulo Martins

  4. Polytechnic Institute of Setubal, Setubal, Portugal

    Leonilde Reis

Authors
  1. Fernando Fresneda-Bottaro
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  2. Arnaldo Santos
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  3. Paulo Martins
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  4. Leonilde Reis
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Corresponding author

Correspondence to Fernando Fresneda-Bottaro .

Editor information

Editors and Affiliations

  1. ISEG, Universidade de Lisboa, Lisbon, Cávado, Portugal

    Alvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, Porto, Portugal

    Fernando Moreira

  5. TeCIP Institute, Scuola Superiore Sant’Anna, Pisa, Italy

    Valentina Colla

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Fresneda-Bottaro, F., Santos, A., Martins, P., Reis, L. (2024). The Application of Artificial Intelligence in Recommendation Systems Reinforced Through Assurance of Learning in Personalized Environments of e-Learning. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F., Colla, V. (eds) Information Systems and Technologies. WorldCIST 2023. Lecture Notes in Networks and Systems, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-031-45645-9_50

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