Learning process: Multi-Agent Tutoring System

Manuel PÉREZ-MORÍÑIGO, Víctor MERCHÁN-MONTERO, José Luis MARTÍN-PÉREZ

Abstract


A multi-agent architecture has been developed for tutorial assignation scheduling. It has two main types of agents: the students and the teachers. These two are coordinated by an algorithm which assigns the classes in order of arrival. The architecture will provide the necessary tools to the students, so they get the maximum profit from the tutorials. Students and Lecturers can coordinate their tutorial meeting in an efficient way with the help of the multi-agent system.


Keywords


Multiagent systems; education; tutorship; scheduling

Full Text:

PDF

References


Capuano, N., De Santo, M., Marsella, M., Molinara, M., and Salerno. S., 2001. A Multi-Agent Architecture for Intelligent Tutoring.

Capuano, N., Mangione, G.R., Pierri, A., and Salerno. S., 2012. Learning Goals Recommendation for Self-Regulated Learning.

Capuano, N., Marsella, M., and Salerno. S., 2000. ABITS: An Agent Based Intelli-gent Tutoring System for Distance Learning.

Gascueña, J. M., and Fernández-Caballero, A., 2005. An Agent-Based In-telligent Tutoring System for Enhancing E-Learning / E-Teaching.

Greer, J., McCalla, G., Vassileva, J., Deters, R., Bull, S., and Kettel, L., 2001. Lessons Learned in Deploying a Multi-Agent Learning Support System: The I-Help Experience.

Sencer, S., 2008. Query Based Learning in Multi-Agent Systems.

Turgay, S., 2005. A multi-agent system approach for distance learning architecture. 1303-6521 volume 4 Issue 4 Article 3.

Webber, C., Bergia, L., Pesty, S., and Balachef, N., 2000. The Baghera project: A multi-agent architecture for human learning. http://julita.usask.ca/mable/webber.pdf

Webber, C., Pesty, S. 2002. A two-level multi-agent architecture for a distance learning environment.

Zapata-Rivera, J.D., and Greer, J., 2001. SMODEL Server: Student Modelling in Distributed Multi-Agent Tutoring Systems. International Conference on Artificial Intelligence in Education AIED 2001. 446-455.

Nabeth, Thierry & Angehrn, Albert & Razmerita, Liana & Roda, Claudia, 2005. InCA: a Cognitive Multi-Agents Architecture for Designing Intelligent & Adaptive Learning Systems. Comput. Sci. Inf. Syst.. 2. 99-114. 10.2298/CSIS0502099N.

Alonso Rincón, Ricardo S.; Prieto Tejedor, Javier; García Pérez, Óscar and Corchado Rodríguez, Juan M., 2013. Collaborative learning via social computing. Frontiers of Information Technology & Electronic Engineering. 2019, Florentino. E-learning Platforms and E-learning Students: Building the Bridge to Success. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, Salamanca, v. 1, n. 2, p. 21-34, jul.. ISSN 2255-2863.

Becerra-Bonache, Leonor and Jiménez López, M. Dolores, 2014. Linguistic Models at the Crossroads of Agents, Learning and Formal Languages. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, Salamanca, v. 3, n. 4, p. 67-87, dec.. ISSN 2255-2863.

Ricardo Silveira, Guilherme Klein da Silva Bitencourt, Thiago Ângelo Gelaim, Jerusa Marchi, and Fernando de La Prieta, 2016. Towards a Model of Open and Reliable Cognitive Multiagent Systems: Dealing with Trust and Emotions. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, Salamanca, v. 4, n. 3, p. 57-86, jun.. ISSN 2255-2863.




DOI: http://dx.doi.org/10.14201/ADCAIJ201981512





Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

Clarivate Analytics