We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Animated Pedagogical Agents to Assist Learners and to keep them motivated on Online Learning Environments (LMS or MOOC)

by K. Bendou, El. Megder, C. Cherkaoui
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 168 - Number 6
Year of Publication: 2017
Authors: K. Bendou, El. Megder, C. Cherkaoui
10.5120/ijca2017914477

K. Bendou, El. Megder, C. Cherkaoui . Animated Pedagogical Agents to Assist Learners and to keep them motivated on Online Learning Environments (LMS or MOOC). International Journal of Computer Applications. 168, 6 ( Jun 2017), 46-53. DOI=10.5120/ijca2017914477

@article{ 10.5120/ijca2017914477,
author = { K. Bendou, El. Megder, C. Cherkaoui },
title = { Animated Pedagogical Agents to Assist Learners and to keep them motivated on Online Learning Environments (LMS or MOOC) },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 168 },
number = { 6 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 46-53 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume168/number6/27882-2017914477/ },
doi = { 10.5120/ijca2017914477 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:15:27.394201+05:30
%A K. Bendou
%A El. Megder
%A C. Cherkaoui
%T Animated Pedagogical Agents to Assist Learners and to keep them motivated on Online Learning Environments (LMS or MOOC)
%J International Journal of Computer Applications
%@ 0975-8887
%V 168
%N 6
%P 46-53
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper gives an overview of the first specifications of current research on an animated pedagogical agent to assist learners and to keep them motivate on an online learning environment (LMS or MOOC). 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. 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. We therefore propose to show, through this paper which is a summary of our recent work, the interest and importance of the analysis of the limitations of the online learning environments, in particular the causes of the drop-out problem in order to define adapted pedagogical interventions strategies.

References
  1. Wilen-Daugenti, T., (2009). Technology and learning environments in higher education. Peter Lang.
  2. Qazdar, A., Cherkaoui, C., Er-Raha, B. et Mammass, D. (2015). AeLF: Mixing Adaptive Learning System avec système de gestion de l'apprentissage. International Journal of Computer Applications , 119 (15).
  3. Cherkaoui, C., et al. (2015). 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.
  4. Bonk, CJ, Lee, MM, Reeves, TC et Reynolds, TH eds., (2015). MOOCs and Open Education. Routledge.
  5. Daradoumis, T., Bassi, R., Xhafa, F. and Caballé, S., 2013, October. A review on massive e-learning (MOOC) design, delivery and assessment. In P2P, Parallel, Grid, Cloud and Internet Computing Conference (3PGCIC), IEEE.
  6. Baylor, A. & Kim, Y. (2003). Validating pedagogical agent roles: Expert, Motivator, and Mentor. In D. Lassner & C. McNaught (Eds.), Proceedings of EdMedia: World Conference on Educational Media and Technology 2003 (pp. 463-466). (AACE).
  7. Yuan, L., Powell, S. and CETIS, J., (2013). MOOCs and open education: Implications for higher education.
  8. Bakki, A., Oubahssi, L., Cherkaoui, C. et George, S. (2015), 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 (p. 556-559). Springer International Publishing.
  9. Hill, P. (2013). The most thorough summary (to date) of MOOC completion rates, e-Literate, February 26th..
  10. Chang, S.H. (2008). Effectiveness of personal interaction in learner - centered paradigm distance education class based on student satisfaction. Journal of Research on Technology in Education . 40 (4).
  11. Zaiane, O. R. (2002, December). Building a recommender agent for e-learning systems. In Computers in Education, 2002. Proceedings. International Conference on (pp. 55-59). IEEE.
  12. Galan J-P., Sabadie W. (2001). Evaluation du site Web: une approche par l'expérience de service, 17ème Congrès International de l'Association Française de Marketing, Deauville, 1-26.
  13. Gulz, Agneta. (2004). Benefits of virtual characters in computer based learning environments: Claims and evidence." International Journal of Artificial Intelligence in Education 14.3, 4): 313-334.
  14. Douglas E. Hersh, 2016 - The Human Element – https://www.insidehighered.com/news/2010/03/29/lms
  15. McCluskey, F., Kupczynski, L., Ice, P., Wiesenmayer, R. (2010). Student Perceptions of the Relationship between Indicators of Teaching Presence and Success in Online Courses. Journal of Interactive Online Learning, 9, 23–43.
  16. Belanger, Y., & Thornton, J. (2013). Bioelectricity: A quantitative approach Duke University’s first MOOC.
  17. El Mhouti, A., Nasseh, A., & Erradi, M. (2016). Stimulate Engagement and Motivation in MOOCs Using an Ontologies Based Multi-Agents System. International Journal of Intelligent Systems & Applications, 8(4).
  18. Stoilescu, D. (2009). Modalities of using learning objects for intelligent agents in learning. International Journal of Doctoral Studies, 4, 49-64.
  19. Nawrot, I. and Doucet, A., (2014). 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.
  20. Frasson, C., Mengelle, T., & Aimeur, E. (1997, August). Using pedagogical agents in a multi-strategic intelligent tutoring system. In Workshop on Pedagogical agents in AI-ED (Vol. 97, pp. 40-47).
  21. Johnson, W. L., Rickel, J. W., & Lester, J. C. (2000). Animated pedagogical agents: Face-to-face interaction in interactive learning environments. International Journal of Artificial intelligence in education, 11(1), 47-78.
  22. Rickel, J. and Johnson, W.L., (1999). Animated agents for procedural training in virtual reality: Perception, cognition, and motor control. Applied artificial intelligence, 13(4-5), pp.343-382.
  23. Pesty, S., Webber, C. and Balacheff, N., (2001). Baghera: une architecture multi-agents pour l'apprentissage humain. Agents Logiciels, Cooperation, Apprentissage et Activité Humaine ALCAA, pp.204-214.
  24. Graesser, A. C., Lu, S., Jackson, G. T., Mitchell, H. H., Ventura, M., Olney, A., & Louwerse, M. M. (2004). AutoTutor: A tutor with dialogue in natural language. Behavior Research Methods, 36(2), 180-192.
  25. Clarebout, G., Elen, J., Johnson, W. L., & Shaw, E. (2002). Animated pedagogical agents: An opportunity to be grasped?. Journal of Educational multimedia and hypermedia, 11(3), 267-286.
  26. Baylor, A. L., & Chang, S. (2002). Pedagogical agents as scaffolds: The role of feedback timing, number of agents, and adaptive feedback. In International Conference of the Learning Sciences, Seattle, WA.
  27. Craig, S.D., Driscoll, D.M. and Gholson, B., (2004). Constructing knowledge from dialog in an intelligent tutoring system: Interactive learning, vicarious learning, and pedagogical agents. Journal of Educational Multimedia and Hypermedia, 13(2), p.163.
  28. Capuano, N., Marsella, M. and Salerno, S., (2000). 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.
  29. Suh, H. and Lee, S., (2006). Collaborative learning agent for promoting group interaction. ETRI journal, 28(4), pp.461-474.
  30. Lin, F.O., (2010). Integrating JADE agents into MOODLE.
  31. Veletsianos, G. and Russell, G.S., (2013). What do learners and pedagogical agents discuss when given opportunities for open-ended dialogue?. Journal of Educational Computing Research, 48(3), pp.381-401.
  32. Garg, V., Tiwari, R. and Gwalior, A.I.(). Hybrid Massive Open Online Course (MOOC) Recommendation System using Machine Learning (2016), In International conference on soft computing techniques in engineering and technology, http://asctet.co.in/papers/OR0033.pdf
  33. Lenoir, Y., (1991). Relations entre interdisciplinarité et intégration des apprentissages dans l'enseignement des programmes d'études du primaire au Québec (Doctoral dissertation, Paris 7).
  34. Bovo, A., (2014). Apprentissage automatique pour l'assistance au suivi d'étudiants en ligne: approche classique et bio-inspirée (Doctoral dissertation).
Index Terms

Computer Science
Information Sciences

Keywords

Online Learning Environment Adaptivity Recommendation Feedback Pedagogical Intervention Pedagogical agent.

Powered by PhDFocusTM