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Dynamic e-Learning Content Selection with BDI Agents

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Book cover Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability - The PAAMS Collection (PAAMS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 524))

Abstract

This paper presents an e-learning content selection model, based on multi-agent paradigm, aiming to facilitate the learning material reuse and adaptability on Learning Management Systems. The proposed model was developed according to a BDI multi-agent architecture, as an improvement of the Intelligent Learning Objects approach, allowing the dynamic selection of Learning Objects. A prototype was implemented to validate the proposed model, using the JADEX BDI V3 platform, and allowing to build improved learning experiences.

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References

  1. Allison, C., Miller, A., Oliver, I., Michaelson, R., Tiropanis, T.: The Web in education. Comput. Netw. 56, 3811–3824 (2012). Elsevier

    Article  Google Scholar 

  2. Vesin, B., Klasnja-Milicevic, A., Ivanovic, M., Budimac, Z.: Applying recommender systems and adaptive hypermedia for e-learning personalization. Comput. Inform. 32, 629–659 (2013). Institute of Informatics

    Google Scholar 

  3. Mahkameh, Y., Bahreininejad, A.: A context-aware adaptive learning system using agents. Expert Syst. Appl. 38, 3280–3286 (2011). Elsevier

    Article  Google Scholar 

  4. Bachari, E., Abelwahed, E., Adnani, M.: E-learning personalization based on dynamic learners’ preference. Int. J. Comput. Sci. Inf. Technol. (IJCSIT) 3(3), 200–216 (2011)

    Google Scholar 

  5. Caeiro, M., Llamas, M., Anido, L.: PoEML: modeling learning units through perspectives. Comput. Standards Interfaces 36(2), 380–396 (2014). Elsevier

    Article  Google Scholar 

  6. Santos, G., Jorge, J.: Interoperable intelligent tutoring systems as open educational resources. IEEE Trans. Learn. Technol. 6(3), 271–282 (2013). IEEE CS & ES

    Article  Google Scholar 

  7. Despotovic-Zrakic, M., Markovic, A., Bogdanovic, Z., Barac, D., Krco, S.: Providing adaptivity in moodle LMS courses. Int. Forum Educ. Tech. Soc. 15(1), 326–338 (2012). International Forum of Educational Technology & Society

    Google Scholar 

  8. Komlenov, Z., Budimac, Z., Ivanovic, M.: Introducing adaptivity features to a regular learning management system to support creation of advanced eLessons. Inform. Educ. 9(1), 63–80 (2010). Institute of Mathematics and Informatics

    Google Scholar 

  9. Barak, M., Ziv, S.: Wandering: A web-based platform for the creation of location-based interactive learning objects. Comput. Educ. 62, 159–170 (2013). Elsevier

    Article  Google Scholar 

  10. Chen, C.: Intelligent web-based learning system with personalized learning path guidance. Comput. Educ. 51, 787–814 (2008). Elsevier

    Article  Google Scholar 

  11. Kurilovas, E., Zilinskiene, I., Dagiene, V.: Recommending suitable scenarios according to learners’ preferences: An improved swarm based approach. Comput. Hum. Behav. 30, 550–557 (2014). Elsevier

    Article  Google Scholar 

  12. Wooldridge, M.: An Introduction to MultiAgent Systems, 2nd edn. Wiley, New York (2009)

    Google Scholar 

  13. Weiss, G. (ed.): Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. The MIT Press, Cambridge (1999)

    Google Scholar 

  14. Pokahr, A., Braubach, L., Haubeck, C., Ladiges, J.: Programming BDI agents with pure Java. In: Müller, J.P., Weyrich, M., Bazzan, A.L. (eds.) MATES 2014. LNCS, vol. 8732, pp. 216–233. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  15. MOODLE – Modular Oriented-Object Dynamic Learning Environment. http://moodle.org

  16. Alencar, M., Netto, J.: Improving cooperation in virtual learning environments using multi-agent systems and AIML. In: 41st ASEE/IEEE Frontiers in Education Conference, Session F4C, pp. 1–6. IEEE (2011)

    Google Scholar 

  17. Giuffra, P., Silveira, R.: A multi-agent system model to integrate virtual learning environments and intelligent tutoring systems. International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI) 2(1), 51–58 (2013)

    Article  Google Scholar 

  18. Brown, E., Cristea, A., Stewart, C., Brailsford, T.: Patterns in authoring of adaptive educational hypermedia: a taxonomy of learning styles. Edu. Technol. Soc. 8(3), 77–90 (2005). International Forum of Educational Technology & Society

    Google Scholar 

  19. Silveira, R., Gomes, E., Vicari, R.: Intelligent learning objects: an agent-based approach of learning objects. In: van Weert, T., Tatnall, A. (eds.) Information and Communication Technologies and Real-Life Learning. IFIP, vol. 182, pp. 103–110. Springer, Boston (2006)

    Google Scholar 

  20. Silva, J., Silveira, R.: The development of intelligent learning objects with an ontology based on SCORM standard. In: Seventh International Conference on Intelligent Systems Design and Applications, pp. 211–216. IEEE (2007)

    Google Scholar 

  21. Bavaresco, N., Silveira, R.: Proposal of an architecture to build intelligent learning objects based on BDI agents. In: XX Informatics in Education Brazilian Symposium (2009)

    Google Scholar 

  22. Padgham, L., Winikoff, M.: Developing Intelligent Agent Systems – A practical guide. Wiley, New York (2004)

    Book  Google Scholar 

  23. Prometheus Design Tool (Eclipse Plug-in). https://code.google.com/p/pdt-plugin/

  24. Pokahr, A., Braubach, L., Jander, K.: The jadex project: programming model. In: Distributed Systems and Information Systems, Chap. 1, pp. 1–34. University of Hamburg (2012)

    Google Scholar 

  25. JADEX Active Components. http://www.activecomponents.org/

  26. Braubach, L., Pokahr, A.: Jadex Active Components Framework – BDI Agents for Disaster Rescue Coordination. University of Hamburg (2011)

    Google Scholar 

  27. Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley, New York (1995)

    Google Scholar 

  28. Braubach, L., Pokahr, A.: Developing Distributed Systems with Active Components and JADEX. University of Hamburg (2012)

    Google Scholar 

  29. SCORM 2004. Advanced Distributed Learning. http://www.adlnet.org/scorm

  30. SCORM Run-Time Reference. Rustici Software. http://scorm.com/scorm-explained/technical-scorm/run-time/run-time-reference/

  31. Vian, J., Campos, R., Palomino, C., Silveira, R.: A multiagent model for searching learning objects in heterogeneous set of repositories. In: 2011 11th IEEE International Conference on Advanced Learning Technologies (ICALT), pp. 48–52. IEEE (2011)

    Google Scholar 

  32. Campos, R.L.R., Comarella, R.L., Silveira, R.A.: Multiagent based recommendation system model for indexing and retrieving learning objects. In: Corchado, J.M., Bajo, J., Kozlak, J., Pawlewski, P., Molina, J.M., Julian, V., Silveira, R.A., Unland, R., Giroux, S. (eds.) PAAMS 2013. CCIS, vol. 365, pp. 328–339. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. PPGCC – UFSC, Florianópolis, Brazil

    João de Amorim Jr., Thiago Ângelo Gelaim & Ricardo Azambuja Silveira

Authors
  1. João de Amorim Jr.
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  2. Thiago Ângelo Gelaim
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  3. Ricardo Azambuja Silveira
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Corresponding author

Correspondence to João de Amorim Jr. .

Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain

    Javier Bajo

  2. University of Southern Denmark, Odense, Denmark

    Kasper Hallenborg

  3. Faculty of Engineering Management, Poznan University, Poznan, Poland

    Pawel Pawlewski

  4. Departamento de Sistemas Informáticos y Computación, Polytechnic University of Valencia, Valencia, Spain

    Vicente Botti

  5. Fluminense Federal University, Rio de Janeiro, Brazil

    Nayat Sánchez-Pi

  6. Universidad Nacional de Colombia, Manizales, CALDAS, Colombia

    Nestor Darío Duque Méndez

  7. Lab. Nacional de Energia e Geologia, Lisbon, Portugal

    Fernando Lopes

  8. Universidad Politécnica de Valencia, Valencia, Spain

    Vicente Julian

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de Amorim, J., Gelaim, T.Â., Silveira, R.A. (2015). Dynamic e-Learning Content Selection with BDI Agents. In: Bajo, J., et al. Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability - The PAAMS Collection. PAAMS 2015. Communications in Computer and Information Science, vol 524. Springer, Cham. https://doi.org/10.1007/978-3-319-19033-4_25

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  • DOI: https://doi.org/10.1007/978-3-319-19033-4_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19032-7

  • Online ISBN: 978-3-319-19033-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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