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Contribution of Pedagogical Agents to Motivate Learners in Online Learning Environments: The Case of the PAOLE Agent

  • Abdelkrim Bendou
  • Mohamed-Amine Abrache
  • Chihab Cherkaoui
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 37)

Abstract

The work we present in this paper is a part of the general problem of drop-out in online learning environments (LMSs and MOOCs). It deals in particular with the motivation issue of learners to finish their courses. In this sense, we defend the idea of the interest of animated pedagogical agents to motivate learners and to adapt content, presentation and navigation to their profile. We therefore propose the first specifications of the PAOLE agent. The design of this agent is based on a new concept which we have called the Pedagogical Intervention. An intervention may be of different kinds, but it is more precisely used to overcome the current problem of abandonment of learners. It combines characteristics of intelligent agents like: autonomy, ability to perceive, to interact, to reason and to act; and some other characteristics of pedagogical agents as: observing, evaluating, adapting content, recommending, engaging, motivating, etc.

Keywords

Online learning Environment Adaptivity Recommendation Feedback Pedagogical intervention Pedagogical agent 

References

  1. 1.
    Wilen-Daugenti, T.: Technology and learning environments in higher education. Peter Lang, New York (2009)Google Scholar
  2. 2.
    Qazdar, A., Cherkaoui, C., Er-Raha, B., Mammass, D.: AeLF: Mixing Adaptive Learning System avec système de gestion de l’apprentissage. Int. J. Comput. Appl. 119(15) (2015)Google Scholar
  3. 3.
    Cherkaoui, C., et al.: Un modèle d’adaptation dans les environnements d’apprentissage en ligne (LMS et MOOC). (SITA’2015), 10ème Conférence internationale sur les systèmes Intelligents. IEEE, 2015 (2015)Google Scholar
  4. 4.
    Bonk, C.J., Lee, M.M., Reeves, T.C., Reynolds, T.H. (eds.): MOOCs and Open Education. Routledge, New York (2015)Google Scholar
  5. 5.
    Daradoumis, T., Bassi, R., Xhafa, F., Caballé, S.: A review on massive e-learning (MOOC) design, delivery and assessment. In: P2P, Parallel, Grid, Cloud and Internet Computing Conference (3PGCIC). IEEE, October 2013Google Scholar
  6. 6.
    Baylor, A., Kim, Y.: Validating pedagogical agent roles: expert, motivator, and mentor. In: Lassner, D., McNaught, C. (eds.) Proceedings of EdMedia: World Conference on Educational Media and Technology 2003, pp. 463–466. AACE (2003)Google Scholar
  7. 7.
    Yuan, L., Powell, S., Cetis, J.: MOOCs and Open Education: Implications for Higher Education (2013)Google Scholar
  8. 8.
    Bakki, A., Oubahssi, L., Cherkaoui, C., George, S.: Motivation et engagement dans les MOOC: comment accroître la motivation de l’apprentissage en adaptant les scénarios pédagogiques? Dans Design for Teaching and Learning in a Networked World, pp. 556–559. Springer International Publishing (2015)Google Scholar
  9. 9.
    Hill, P.: The most thorough summary (to date) of MOOC completion rates, e-Literate, 26 February 2013Google Scholar
  10. 10.
    Zaíane, O.R.: Building a recommender agent for e-learning systems. In: Proceedings of International Conference on Computers in Education 2002, pp. 55–59. IEEE, December 2002Google Scholar
  11. 11.
    Galan, J.-P., Sabadie, W.: Evaluation du site Web: une approche par l’expérience de service, 17ème Congrès International de l’Association Française de Marketing, Deauville, pp. 1–26 (2001)Google Scholar
  12. 12.
    Gulz, A.: Benefits of virtual characters in computer based learning environments: claims and evidence. Int. J. Artif. Intell. Edu. 14(3, 4), 313–334 (2004)Google Scholar
  13. 13.
    Hersh, D.E.: The Human Element (2016). https://www.insidehighered.com/news/2010/03/29/lms
  14. 14.
    McCluskey, F., Kupczynski, L., Ice, P., Wiesenmayer, R.: Student perceptions of the relationship between indicators of teaching presence and success in online courses. J. Interact. Online Learn. 9, 23–43 (2010)Google Scholar
  15. 15.
    El Mhouti, A., Nasseh, A., Erradi, M.: Stimulate engagement and motivation in moocs using an ontologies based multi-agents system. Int. J. Intell. Syst. Appl. 8(4) (2016)Google Scholar
  16. 16.
    Stoilescu, D.: Modalities of using learning objects for intelligent agents in learning. Int. J. Doctoral Stud. 4, 49–64 (2009)Google Scholar
  17. 17.
    Nawrot, I., Doucet, A.: Building engagement for MOOC students: introducing support for time management on online learning platforms. In: Proceedings of the 23rd International Conference on World Wide Web, pp. 1077–1082. ACM (2014)Google Scholar
  18. 18.
    Frasson, C., Mengelle, T., Aimeur, E.: Using pedagogical agents in a multi-strategic intelligent tutoring system. In: Workshop on Pedagogical agents in AI-ED, vol. 97, pp. 40–47, August 1997Google Scholar
  19. 19.
    Johnson, W.L., Rickel, J.W., Lester, J.C.: Animated pedagogical agents: face-to-face interaction in interactive learning environments. Int. J. Artif. Intell. Edu. 11(1), 47–78 (2000)Google Scholar
  20. 20.
    Rickel, J., Johnson, W.L.: Animated agents for procedural training in virtual reality: perception, cognition, and motor control. Appl. Artif. Intell. 13(4–5), 343–382 (1999)CrossRefGoogle Scholar
  21. 21.
    Pesty, S., Webber, C., Balacheff, N.: Baghera: une architecture multi-agents pour l’apprentissage humain. Agents Logiciels, Cooperation, Apprentissage et Activité Humaine ALCAA, pp. 204–214 (2001)Google Scholar
  22. 22.
    Graesser, A.C., Lu, S., Jackson, G.T., Mitchell, H.H., Ventura, M., Olney, A., Louwerse, M.M.: AutoTutor: a tutor with dialogue in natural language. Behav. Res. Methods 36(2), 180–192 (2004)CrossRefGoogle Scholar
  23. 23.
    Clarebout, G., Elen, J., Johnson, W.L., Shaw, E.: Animated pedagogical agents: an opportunity to be grasped? J. Edu. Multimedia Hypermedia 11(3), 267–286 (2002)Google Scholar
  24. 24.
    Baylor, A.L., Chang, S.: Pedagogical agents as scaffolds: the role of feedback timing, number of agents, and adaptive feedback. In: International Conference of the Learning Sciences, Seattle, WA (2002)Google Scholar
  25. 25.
    Craig, S.D., Driscoll, D.M., Gholson, B.: Constructing knowledge from dialog in an intelligent tutoring system: interactive learning, vicarious learning, and pedagogical agents. J. Educ. Multimedia Hypermedia 13(2), 163 (2004)Google Scholar
  26. 26.
    Capuano, N., Marsella, M., Salerno, S.: ABITS: an agent based Intelligent Tutoring System for distance learning. In: Proceedings of the International Workshop on Adaptive and Intelligent Web-Based Education Systems, ITS (2000)Google Scholar
  27. 27.
    Suh, H., Lee, S.: Collaborative learning agent for promoting group interaction. ETRI J. 28(4), 461–474 (2006)CrossRefGoogle Scholar
  28. 28.
    Lin, F.O.: Integrating JADE Agents into MOODLE (2010)Google Scholar
  29. 29.
    Veletsianos, G., Russell, G.S.: What do learners and pedagogical agents discuss when given opportunities for open-ended dialogue? J. Edu. Comput. Res. 48(3), 381–401 (2013)CrossRefGoogle Scholar
  30. 30.
    Garg, V., Tiwari, R., Gwalior, A.I.: Hybrid Massive Open Online Course (MOOC) recommendation system using machine learning. In: International Conference on Soft Computing Techniques in Engineering and Technology (2016). http://asctet.co.in/papers/OR0033.pdf
  31. 31.
    Lenoir, Y.: Relations entre interdisciplinarité et intégration des apprentissages dans l’enseignement des programmes d’études du primaire au Québec (Doctoral dissertation, Paris 7) (1991)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.IRF-SIC LaboratoryFSA - Ibn Zohr University AgadirAgadirMorocco

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