A Multi-Expert Fuzzy TOPSIS-based Model for the Evaluation of e-Learning Paths
نویسندگان
چکیده
In e-learning settings, the evaluation of different alternatives regarding learning paths’ proposals is nowadays crucial, due to the great attention devoted to the construction of learning objects (LO) available through Learning Management Systems (LMS). In this paper, we present a model aiming to support this evaluation process, in presence of multiple attributes and of a panel of experts involved in educational processes. The evaluation of alternatives of e-learning paths, is carried out by each expert using the TOPSIS method under the assumption that the scores are linguistically assessed and represented by positive triangular fuzzy numbers. Given the individual rankings of alternatives, a consensus modelling mechanism is introduced where the disagreement between the rankings of single experts and the group ranking is measured with a Spearman foot rule distance. A compromise solution (consensual group ranking) is determined through a constrained optimization model where the objective function is represented by a OWA-based aggregation of individual distances and constraints are imposed on individual disagreements.
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