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Learning Path Recommendation from an Inferred Learning Space

Madjid Sadallah
Grégory Smits
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Abstract

Defining a learning space of reference may be a challenging task for the concerned tutor(s). However, once formalized, such a representation of possible learning sequences may serve as a norm to evaluate the current state of a learner and to potentially derive recommendations about the next learning state to target. A pragmatic strategy is introduced in this article to ease the definition of a subjective learning space from a few tutor(s)-provided examples of representative learning paths. A measure is then also inferred from these representative paths that can then be used to evaluate an ongoing learning path. The learning space and the evaluation measure, combined together, are then used to suggest the learning activity the learner should address next.
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Dates and versions

hal-04108625 , version 1 (27-05-2023)

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  • HAL Id : hal-04108625 , version 1

Cite

Madjid Sadallah, Grégory Smits. Learning Path Recommendation from an Inferred Learning Space. 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Sep 2023, Aveiro, Portugal. ⟨hal-04108625⟩
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