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Leveraging Explainable AI Methods and Tools for Educational Data

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Higher Education Learning Methodologies and Technologies Online (HELMeTO 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2076))

Abstract

Artificial Intelligence (AI) has become an integral part of our lives, and Explainable Artificial Intelligence (XAI) is becoming more essential to ensure trustworthiness and comply with regulations. XAI methodologies help to explain the automatic processing behind data analysis. This paper provides an overview of the use of XAI in the educational domain. Specifically, it analyzes some of the most commonly used XAI tools, emphasizing their characteristics to help users choose the most suitable one. Additionally, two case studies have been analyzed to demonstrate how to use XAI tools in the educational domain by exploiting a subset of the Open University dataset.

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Notes

  1. 1.

    EU AI ACT: https://www.europarl.europa.eu/news/en/headlines/society/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence.

  2. 2.

    General Data Protection Regulation (GDPR): https://gdpr-info.eu/.

  3. 3.

    https://demos.citius.usc.es/ExpliClas/.

  4. 4.

    https://www.cs.waikato.ac.nz/ml/weka/.

  5. 5.

    https://orangedatamining.com/.

  6. 6.

    https://github.com/oegedijk/explainerdashboard.

  7. 7.

    https://eli5.readthedocs.io/en/latest/.

  8. 8.

    https://github.com/GionatanG/skmoefs.

  9. 9.

    https://bitbucket.org/mbarsacchi/fuzzyml/src/master/.

  10. 10.

    https://github.com/Fisdet/FISDeT.

  11. 11.

    Student oriented subset of the Open University Learning Analytics dataset: https://zenodo.org/records/4264397.

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Acknowledgment

Gabriella Casalino acknowledges funding from the European Union PON project Ricerca e Innovazione 2014–2020, DM 1062/2021. Gianluca Zaza and Giovanna Castellano acknowledge the support of the PNRR project FAIR - Future AI Research (PE00000013), Spoke 6 - Symbiotic AI (CUP H97G22000210007) under the NRRP MUR program funded by the NextGenerationEU. Gabriella Casalino, Giovanna Castellano, Riccardo Pecori and Gianluca Zaza are members of the INdAM GNCS research group. G. Casalino, G. Castellano, R. Pecori and G. Zaza acknowledge funds from “INdAM-GNCS Project” (CUP E53C22001930001). P. Ducange thanks the PNRR - M4C2 - Investimento 1.3, Partenariato Esteso PE00000013 - “FAIR - Future Artificial Intelligence Research” - Spoke 1 “Human-centered AI” and the Italian Ministry of University and Research (MUR) in the framework of the FoReLab and CrossLab projects (Departments of Excellence). M. Fazzolari acknowledges SERICS project (PE14), funded by NextGenerationEU program.

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Bari, Via Orabona 4, Bari, Italy

    Gabriella Casalino, Giovanna Castellano & Gianluca Zaza

  2. Department of Information Engineering, University of Pisa, Largo Lazzarino 1, Pisa, Italy

    Pietro Ducange

  3. IIT-CNR, Via Moruzzi 1, Pisa, Italy

    Michela Fazzolari

  4. SMARTEST Research Centre, eCampus University, Via Isimbardi 10, 22060, Novedrate, CO, Italy

    Riccardo Pecori

  5. IMEM-CNR, Parco Area delle Scienze 37/A, 43124, Parma, Italy

    Riccardo Pecori

Authors
  1. Gabriella Casalino
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  2. Giovanna Castellano
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  3. Pietro Ducange
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  4. Michela Fazzolari
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  5. Riccardo Pecori
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  6. Gianluca Zaza
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Corresponding author

Correspondence to Riccardo Pecori .

Editor information

Editors and Affiliations

  1. University of Bari, Bari, Italy

    Gabriella Casalino

  2. Pegaso University, Naples, Italy

    Raffaele Di Fuccio

  3. National Research Council of Italy, Institute for Educational Technology, Palermo, Italy

    Giovanni Fulantelli

  4. eCampus University, Novedrate, Como, Italy

    Paolo Raviolo

  5. Alma Mater Studiorum University of Bologna, Bologna, Italy

    Pier Cesare Rivoltella

  6. National Research Council of Italy, Institute for Educational Technology, Palermo, Palermo, Italy

    Davide Taibi

  7. University of Foggia, Foggia, Italy

    Giusi Antonia Toto

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Casalino, G., Castellano, G., Ducange, P., Fazzolari, M., Pecori, R., Zaza, G. (2024). Leveraging Explainable AI Methods and Tools for Educational Data. In: Casalino, G., et al. Higher Education Learning Methodologies and Technologies Online. HELMeTO 2023. Communications in Computer and Information Science, vol 2076. Springer, Cham. https://doi.org/10.1007/978-3-031-67351-1_7

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  • DOI: https://doi.org/10.1007/978-3-031-67351-1_7

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