Authors:
Àngela Nebot
1
;
Francisco Mugica
1
and
Félix Castro
2
Affiliations:
1
Technical University of Catalonia, Spain
;
2
Universidad Autónoma del Estado de Hidalgo, Mexico
Keyword(s):
Data Mining, E-Learning, Fuzzy Inductive Reasoning (FIR), Fuzzy Logic.
Related
Ontology
Subjects/Areas/Topics:
Computer-Supported Education
;
Education and Training
;
e-Learning
;
e-Learning Platforms
;
Simulation and Modeling
;
Simulation Tools and Platforms
Abstract:
This research presents a framework that provides valuable knowledge to teachers and students, mainly based on fuzzy logic methodologies. The framework offers the following knowledge: 1) gives a sets of rules describing the students’ learning behaviour; 2) provides a relative assessment of the features involved in the students’ evaluation performance, i.e. detects and assess the most important topics involved in the course evaluation process; 3) groups the learning behaviour of the students involved in online courses, in an incremental and dynamical way, with the ultimate goal to timely detect failing students, and properly provide them with a suitable and actionable feedback. In this paper the proposed framework is applied to the Didactic Planning course of Centre of Studies in Communication and Educational Technologies virtual campus. The application shows it usefulness, improving the course understanding and providing valuable knowledge to teachers about the course performance.