Multi-agent system model for tutor recommendation in ubiquitous learning environments
Resumo
Ubiquitous learning environments allow to learn anywhere at anytime, enabling people to have better learning experiences in their daily lives. In order to detect learning problems and offer help, a tutor needs to observe the actions of students and to evaluate them, which is not easy to accomplish in a ubiquitous environment. Therefore, this work presents a multi-agent model to generate recommendations of tutors in the topic that a student needs help with, based on the experiences of these tutors with other students, their availability and their physical proximity. The proposed model allows to monitor the student interaction within the learning environment, detect learning problems and offer personalized help.
Palavras-chave:
Multi-agent model, Recommendation, Ubiquitous learning environments
Referências
Ayoola, O. L. and Mangina, E. (2014). Personalisation of a u-learning environment for third level education. Yükseköğretim Dergisi, 4(1):54–60.
Bokhari, M. U. and Ahmad, S. (2014). Multi-Agent Based E-Learning Systems: A Comparative Study. In International Conference on Information and Communication Technology for Competitive Strategies. ICTCS ’14, pages 1–6.
Boudabous, S., Kazar, O., and Laouar, M. R. (2017). Towards a hospital ubiquitous learning system based agents. In Proceedings of the International Conference on Computing for Engineering and Sciences, ICCES ’17, pages 56–62, New York, NY, USA. ACM.
de M. Neves, A. R., Alvaro Marcos G. Carvalho, and Ralha, C. G. (2014). Agent-based architecture for context-aware and personalized event recommendation. Expert Systems with Applications, 41(2):563 – 573.
Duran, E. B. and Alvarez, M. (2017). Method for Generating Expert Recommendations to advise students on ubiquitous learning experiences. In Conferencia Internacional de la Sociedad Chilena de Ciencia de la Computación (SCCC 2017).
Garcia-Cabot, A., Garcia-Lopez, E., De-Marcos, L., Fernandez, L., and Gutierrez-Martinez, J.-M. (2014). Adapting learning content to user competences, context and mobile device using a multi-agent system: case studies. International Journal of Engineering Education, 30(4):937–949.
Graf, S. and Kinshuk (2008). Adaptivity and Personalization in Ubiquitous Learning Systems. In 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering - USAB 2008, pages 331–338, Graz, Austria. Springer 2008.
Nwana, H. (1996). Software Agents: An Overview. Knowledge Engineering Review, 11(3):205–244.
Sajja, P. S. and Akerkar, R. (2012). Intelligent Technologies for Web Applications. Chapman & Hall/CRC, 1st edition.
Salazar, O. M., Ovalle, D. A., and Duque, N. D. (2015). Adaptive and personalized educational ubiquitous multi-agent system using context-awareness services and mobile devices. In Zaphiris, P. and Ioannou, A., editors, Learning and Collaboration Technologies, pages 301–312, Cham. Springer International Publishing.
Tan, Q., Kinshuk, Kuo, Y. H., Jeng, Y. L., Wu, P. H., Huang, Y. M., Liu, T. C., and Chang, M. (2009). Location-based adaptive mobile learning research framework and topics. In 2009 International Conference on Computational Science and Engineering, volume 1, pages 140–147.
Wooldridge, M. (2002). Introduction to MultiAgent Systems. Wiley & Sons, second edi edition.
Bokhari, M. U. and Ahmad, S. (2014). Multi-Agent Based E-Learning Systems: A Comparative Study. In International Conference on Information and Communication Technology for Competitive Strategies. ICTCS ’14, pages 1–6.
Boudabous, S., Kazar, O., and Laouar, M. R. (2017). Towards a hospital ubiquitous learning system based agents. In Proceedings of the International Conference on Computing for Engineering and Sciences, ICCES ’17, pages 56–62, New York, NY, USA. ACM.
de M. Neves, A. R., Alvaro Marcos G. Carvalho, and Ralha, C. G. (2014). Agent-based architecture for context-aware and personalized event recommendation. Expert Systems with Applications, 41(2):563 – 573.
Duran, E. B. and Alvarez, M. (2017). Method for Generating Expert Recommendations to advise students on ubiquitous learning experiences. In Conferencia Internacional de la Sociedad Chilena de Ciencia de la Computación (SCCC 2017).
Garcia-Cabot, A., Garcia-Lopez, E., De-Marcos, L., Fernandez, L., and Gutierrez-Martinez, J.-M. (2014). Adapting learning content to user competences, context and mobile device using a multi-agent system: case studies. International Journal of Engineering Education, 30(4):937–949.
Graf, S. and Kinshuk (2008). Adaptivity and Personalization in Ubiquitous Learning Systems. In 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering - USAB 2008, pages 331–338, Graz, Austria. Springer 2008.
Nwana, H. (1996). Software Agents: An Overview. Knowledge Engineering Review, 11(3):205–244.
Sajja, P. S. and Akerkar, R. (2012). Intelligent Technologies for Web Applications. Chapman & Hall/CRC, 1st edition.
Salazar, O. M., Ovalle, D. A., and Duque, N. D. (2015). Adaptive and personalized educational ubiquitous multi-agent system using context-awareness services and mobile devices. In Zaphiris, P. and Ioannou, A., editors, Learning and Collaboration Technologies, pages 301–312, Cham. Springer International Publishing.
Tan, Q., Kinshuk, Kuo, Y. H., Jeng, Y. L., Wu, P. H., Huang, Y. M., Liu, T. C., and Chang, M. (2009). Location-based adaptive mobile learning research framework and topics. In 2009 International Conference on Computational Science and Engineering, volume 1, pages 140–147.
Wooldridge, M. (2002). Introduction to MultiAgent Systems. Wiley & Sons, second edi edition.
Publicado
04/10/2018
Como Citar
REUTER, Beatriz Fernandez; ALVAREZ, Margarita M.; GONZALEZ, Gabriela; DURÁN, Elena B..
Multi-agent system model for tutor recommendation in ubiquitous learning environments. In: WORKSHOP ON ADVANCED VIRTUAL ENVIRONMENTS AND EDUCATION (WAVE), 1. , 2018, Florianópolis-SC.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 10-17.
DOI: https://doi.org/10.5753/wave.2018.10.
