Learner’s Profile Hierarchization in an Interoperable Education System

Ghorbel, Leila; Zayani, Corinne Amel; Amous, Ikram; Sèdes, Florence

doi:10.1007/978-3-319-53480-0_54

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Overview Of the Proposed Mechanism For Mapping Generation1

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2018

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“…These parameters are detailed in Section 5.1. The mechanism for mapping generation generates the mapping rules which serve to merge the exchanged data from LP to GP and vice versa based on a mechanism of data fusion (Ghorbel et al, 2016). This mechanism allows mainly the resolution of conflicts which may occur in the exchanged data .…”

Section: Overview Of the Proposed Mechanism For Mapping Generationmentioning

confidence: 99%

Semi-supervised algorithm with knowledge-based features for learner's profiles interoperability

Ghorbel

Zayani

Amous

et al. 2018

IJTEL

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Nowadays, the user can have several profiles found in different adaptive systems relative to various fields. In particular, adaptive e-learning systems respond to a strong need to adapt to each learner their proposed activities based on the data stored in his/her profile (learning-style, interest, etc.). However, each system can have incomplete data as far as the learner is concerned. Hence, the exchange of the learner's profile data is extremely important in order to enhance his/her learning experience. The exchange requires a matching process so as to resolve the large number of a learner's profiles differences whether in syntax, structure or semantics. In this context, we propose a matching process to automatically detect the similarity between the profile elements. The originality of this process resides in the fact that it rests on a new semi-supervised Tri-Training algorithm which significantly improves the state of the art approaches.

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Section: Overview Of the Proposed Mechanism For Mapping Generationmentioning

confidence: 99%