A new recommendation method for pertinent collaborative learners based on their intelligence and a fuzzy measure Online publication date: Sat, 29-Jun-2019
by Saida Hank; Azeddine Chikh
International Journal of Technology Enhanced Learning (IJTEL), Vol. 11, No. 3, 2019
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.
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