The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIV-4/W3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-4/W3-2020, 227–232, 2020
https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-227-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-4/W3-2020, 227–232, 2020
https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-227-2020

  23 Nov 2020

23 Nov 2020

COLLABORATIVE TUTORING: A MULTI-TUTOR APPROACH

M. Ennaji1, H. Boukachour2, M. Machkour1, and Y. Kabbadj1 M. Ennaji et al.
  • 1Computer Systems and Vision Laboratory, Faculty of Sciences Ibn Zohr University, Agadir, Morocco
  • 2Computer Science, Information Processing and Systems Laboratory, Le Havre University, France

Keywords: Collaborative Learning, Multi-agent, Multi-Level System Tracks, Cases Based Dynamic Reasoning

Abstract. An Intelligent Tutorial System (ITS) is a learning computer environment. Many ITSs do not integrate human tutor since they are designed to use in autonomy by the learner. One of the reasons to increase the rate of desertion in a distance training framework compared to that of a face-to-face course is the absence of the human killer. Besides, the existing ITSs are dedicated to a single learning object based on domain-dependent modelling. Our contribution consists in proposing an ITS, independent of the learning domain, capable of initiating learning, of managing an articulation between machine tutoring and human tutoring (teaching and peers) to offer an individualized and personalized follow-up, and ensure certification of the learner’s assessment.