Evaluating Web Based Instructional Models Using Association Rule Mining

Authors:
Enrique García;Cristóbal Romero;Sebastián Ventura;Carlos Castro
Affiliations:
Escuela Politécnica Superior, Universidad de Córdoba, Córdoba, Spain 14071;Escuela Politécnica Superior, Universidad de Córdoba, Córdoba, Spain 14071;Escuela Politécnica Superior, Universidad de Córdoba, Córdoba, Spain 14071;Escuela Politécnica Superior, Universidad de Córdoba, Córdoba, Spain 14071
Venue:
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Year:
2009

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Abstract

In this paper we describe an Integrated Development System for Instructional Model for E-learning (INDESIME) to create and to maintain instructional models using adaptive technologies and collaborative tools. An authoring tool has also been developed for helping to non-programming users to create Learning Management Systems (LMSs) courses that implement a specific instructional model. Data mining techniques are proposed to evaluate the e-learning courses generated from the model. We have tested the degree of effectiveness of our system using Moodle courses. The courses topics tested are based on the European Computer Driving Licence Foundation catalogue.