Automated Evaluation of Learners with ODALA: Application to Relational Databases E-learning

DOI

10.2991/ijcis.2010.3.3.11How to use a DOI?

Keywords

Self-learning, Error diagnosis, Learner's evaluation, Learner's marking, Learner's model, E-learning.

Abstract

This paper deals with an approach for an automated evaluation of the learners' state of knowledge when learning by doing. This approach is called ODALA for "Ontology-Driven Auto-evaluation for e-Learning Approach". It takes place in the context of Computer Based Human Learning Environment (CBHLE) in a self-learning by doing mode. ODALA is based on the teaching domain ontology and on errors classification and detection. The evaluation process is composed of four stages: (1) form analysis of learner's solutions, (2) semantic analysis, (3) marking, and (4) updating of the learner's model. We bring the approach into play in the context of relational databases teaching: we present the results of the relational databases self-learning system (RDB-E-LEARN) development, where the main stages of our evaluation approach are implemented.

Copyright

© 2010, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Farida Bouarab-Dahmani
AU  - Malik Si-Mohammed
AU  - Catherine Comparot
AU  - Pierre-Jean Charrel
PY  - 2010
DA  - 2010/09/01
TI  - Automated Evaluation of Learners with ODALA: Application to Relational Databases E-learning
JO  - International Journal of Computational Intelligence Systems
SP  - 357
EP  - 369
VL  - 3
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2010.3.3.11
DO  - 10.2991/ijcis.2010.3.3.11
ID  - Bouarab-Dahmani2010
ER  -