Title: A new recommendation method for pertinent collaborative learners based on their intelligence and a fuzzy measure

Authors: Saida Hank; Azeddine Chikh

Addresses: Algiers University 3, Rue Ahmed Oukade, B.P. 19, Dely Ibrahim, Algiers, Algeria; Higher National School of Computer Science, ESI, Oued Smar, Algiers, Algeria ' Laboratory of Research in Informatics of Tlemcen, Department of Computer Sciences, University of Tlemcen, Tlemcen, Algeria

Abstract: This paper considers learners' intelligence as an influencing factor for collaborative learning. We propose a novel recommendation approach for pertinent collaborative learners. This approach is based on the learners' collaboration according to the multiple and triarchic intelligence theories. Our contribution is mainly a two-fold proposition: (1) We adopt the conceptual model of learners' intelligence, that we have proposed in other paper, and which we enhance by adding multiple intelligence and triarchic intelligence as sub-classes of the 'intelligence' class. (2) We adopt a process that aims at (a) acquiring knowledge of an individual learner's intelligence according to the multiple and triarchic intelligence theories, (b) recommending pertinent collaborators using a mathematical aggregation operator that relies on a fuzzy measure that facilitates consideration of the importance of each criterion as well as its interaction with others. An illustrative example shows the effect of this interaction.

Keywords: e-learning; bloom's objectives; intelligence; collaborative learning; learners' recommendation; fuzzy measure.

DOI: 10.1504/IJTEL.2019.100483

International Journal of Technology Enhanced Learning, 2019 Vol.11 No.3, pp.279 - 303

Accepted: 23 May 2018
Published online: 29 Jun 2019 *

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