Authors:
Hanane Elbasri
1
;
Adil Haddi
2
;
Hakim Allali
2
and
Othmane El Meslouhi
2
Affiliations:
1
LAVETE Laboratory, FST, Hassan 1st University, Settat, Morocco, North Africa, Ibn Zohr University, Agadir, Morocco, North Africa, Morocco
;
2
Ibn Zohr University, Agadir, Morocco, North Africa, Morocco
Keyword(s):
Technology Enhanced Learning (TEL), metacognition, metacognitive agent, multi-agent system
Abstract:
Online learning is the field of action of the article. We are, therefore, in full "Technology Enhanced Learning” (TEL). In the absence of the teacher in the TEL and faced with the difficulties encountered, learners have a high probability of being demotivated and can, therefore, give up learning very early.
To remedy these drawbacks, the article proposes an intelligent agent that helps the learner to build a reading plan for the course, to choose a learning strategy and readjust it according to his progress towards his objectives. This agent is the metacognitive agent that, by design, is precisely there to encourage the learner to self-evaluate his learning.
The article shows the interactions between the proposed agent and the learner through a number of criteria that allow the agent to determine when and how to react.
These criteria take into account the progression and speed of learning, the performance of the learner as well as the result of the formative evaluation throughout the
learning process.
The agent is modeled by distributing the different stages of metacognition and designing the interaction between the learner and the metacognitive agent.
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