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

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 Environ...

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Bibliographic Details
Main Authors: Farida Bouarab-Dahmani, Malik Si-Mohammed, Catherine Comparot, Pierre-Jean Charrel
Format: Article
Language:English
Published: Springer 2010-09-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Online Access:https://www.atlantis-press.com/article/1971.pdf
Description
Summary: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.
ISSN:1875-6883