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Intelligent Agents supporting user interactions within self regulated learning processes
ARTICLE

, , Università di Macerata, Italy ; , Università di Palermo, Italy ; , Università di Macerata, Italy ; , , Università di Palermo, Italy ; , Università di Macerata, Italy ; , Università di Palermo, Italy

Journal of e-Learning and Knowledge Society Volume 6, Number 2, ISSN 1826-6223 e-ISSN 1826-6223 Publisher: Italian e-Learning Association

Abstract

The paper focuses on the main advantages in the defnition and utilization of an open and modular e-learning software platform to support highly cognitive tasks performed by the main actors of the learning process. We present in detail the integration inside the platform of two intelligent agents devoted to talking with the student and to retrieving new information sources on the Web. The process is triggered as a reply to the system’s perception that the student feels discontented with the presented contents. The architecture is detailed, and some conclusions about the growth of the platform’s overall performance are expressed.

Citation

Bentivoglio, C., Bonura, D., Cannella, V., Carletti, S., Pipitone, A., Pirrone, R., Rossi, P. & Russo, G. (2010). Intelligent Agents supporting user interactions within self regulated learning processes. Journal of e-Learning and Knowledge Society, 6(2), 27-36. Italian e-Learning Association. Retrieved January 17, 2019 from .

Keywords

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References

  1. Azevedo, R. (2008), The role of self-regulation in learning about science with hypermedia. In D. Robinson& G. Schraw (Eds.), Recent innovations in educational technology that facilitate student learning, 127-156. Charlotte, NC: Information Age Publishing.
  2. Bentivoglio C.A. (2009), Recognizing Community Interaction States in Discussion Forum Evolution. In Cognitive and Metacognitive Educational Systems AAAI Fall Symposium, 20-25.
  3. Pilato G., Pirrone R., Rizzo R. (2008), A KST-Based System for Student Tutoring. Applied Artificial Intelligence, 22(4), 283-308, ISSN: 0883-9514.
  4. Pintrich, P.R. (2000), The role of goal orientation in selfregulated learning. In Boekaerts, M.; Pintrich, P.R.; and Zeinder, M., eds., Handbook of self-regulation. San Diego, CA: Academic Press. 451–502.
  5. Pirrone R., Cannella V., and Russo G. (2008), Awareness Mechanisms for an Intelligent Tutoring System. Biological ly Inspired Cognitive Architectures. AAAI Fall Symposium (FS-08-01) ISBN 978-1-57735-396-6, 146-151.
  6. Prensky, M. (2008), The Role of Technology in teaching and the classroom, Educational Technology, Vol. 48(6), 1-3.
  7. Rossi, P.G. (2006), Design and ongoing monitoring systems for online education. In Proceedings of OnLine Educa, Berlin.
  8. Rossi, P.G. (2009), Ambiente di apprendimento con elementi di artificial intelligence. JE-LKS. Journal of E-Learning and Knowledge Society, vol. 5(1), 65-75.
  9. Russo G., Pipitone A., and Pirrone R. (2009), Acquisition Of New Knowledge In TutorJ. Cognitive and Metacognitive Educational Systems. AAAI Fall Symposium (FS-0902) ISBN 978-1-57735-436-9, 81-86.
  10. Landauer, T., and Laham, P.F.D. (1998), An Introduction to Latent Semantic Analysis. Discours Processes 25, 259–284.
  11. Zimmermann, B.J. (2001), Theories of Self-Regulated Learning and Academic Achievement: An Overview and Analysis. Lawrence Erlbaum Associates. Chapter 1, 1–37.

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