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Multi-agent Systems that Learn to Monitor Students’ Activity

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Advances in Artificial Intelligence - IBERAMIA 2018 (IBERAMIA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11238))

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Abstract

Learning activities make use today of a variety of software tools, like Learning Management Systems (LMSs), online social networks, and forums. They enhance the experience by facilitating interactions among participants and with resources. These interactions can be used as a source of information on how the process is working for individual students or groups, and therefore to provide them a tailored support. However, lecturers can only do this monitoring in very simple ways, as their time is limited, tools generate large amounts of data, and students have very different profiles. In order to improve this situation, this work proposes the use of semi-automated assistants to analyse these data, able to learn from the lecturers’ expertise on what situations are relevant. The Assistant for Learning Activities (ALA) is an Adaptive Multi-Agent System (AMAS) that raises alerts when some events appear in data. Its architecture includes two groups of agents. The core are the agents that learn and classify the data to generate the alerts. There can be multiple groups of these agents to identify different types of alert. A second group of agents wraps and transforms data from sources to feed the first group. The ALA setup uses a prototypical training based on information from previous courses. Then, it learns and adjusts for a specific course using the lecturers’ feedback on the alerts it generates. The paper reports the currently undergoing validation of the ALA knowledge based on the information from the institutional LMS of a Spanish university.

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Notes

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Acknowledgment

This work has been done in the context of the individual grant “Subprograma de Movilidad del Programa Estatal de Promoción del Talento y su Empleabilidad, en el marco del Plan Estatal de Investigación Científica y Técnica y de Innovación” (grant PRX17/00613) supported by the Spanish Ministry for Education, Culture, and Sports, the projects “RISE Women with disabilities In Social Engagement (RISEWISE)” (grant 690874) supported by the European Commission in the Horizon 2020 programme, “Collaborative Design for the Promotion of the Well-Being in Inclusive Smart Cities (DColbici3)” (grant TIN2017-88327-R) supported by the Spanish Ministry for Economy and Competitiveness, MOSI-AGIL-CM (grant S2013/ICE-3019) supported by the Autonomous Region of Madrid and co-funded by EU Structural Funds FSE and FEDER, “Manage Your Time - Learning Method of Time Management and Organizational Autonomy in Multiple Projects (GesTie)” (grant 258 - 2018-19) supported by the Universidad Complutense de Madrid, and the “Programa de Creación y Consolidación de Grupos de Investigación” (UCM-BSCH GR35/10-A).

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Authors and Affiliations

  1. Research Group on Agent-based, Social and Interdisciplinary Applications (GRASIA), Universidad Complutense de Madrid, Madrid, Spain

    Rubén Fuentes-Fernández

  2. Institut de Recherche en Informatique de Toulouse (IRIT), Toulouse, France

    Frédéric Migeon

Authors
  1. Rubén Fuentes-Fernández
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  2. Frédéric Migeon
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Corresponding author

Correspondence to Rubén Fuentes-Fernández .

Editor information

Editors and Affiliations

  1. Universidad Nacional del Sur, Bahía Blanca, Buenos Aires, Argentina

    Guillermo R. Simari

  2. University of Madeira, Funchal, Portugal

    Eduardo Fermé

  3. Universidad Nacional de Piura, Castilla-Piura, Peru

    Flabio Gutiérrez Segura

  4. Universidad Nacional de Trujillo, Trujillo, Peru

    José Antonio Rodríguez Melquiades

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Fuentes-Fernández, R., Migeon, F. (2018). Multi-agent Systems that Learn to Monitor Students’ Activity. In: Simari, G., Fermé, E., Gutiérrez Segura, F., Rodríguez Melquiades, J. (eds) Advances in Artificial Intelligence - IBERAMIA 2018. IBERAMIA 2018. Lecture Notes in Computer Science(), vol 11238. Springer, Cham. https://doi.org/10.1007/978-3-030-03928-8_9

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  • DOI: https://doi.org/10.1007/978-3-030-03928-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03927-1

  • Online ISBN: 978-3-030-03928-8

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