Diagnostic d'erreurs dans le projet FreeText

L'haire, Sébastien; Vandeventer-Faltin, Anne

doi:10.4000/alsic.2219

Cited by 6 publications

(2 citation statements)

References 6 publications

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“…This is the main reason why we are interested in more sophisticated processes, such as those of correct answers freely drafted by the learner to open questions. The bibliography in this area indicates several diagnosis techniques which are used either separately or combined in a single system: definition of plans for each possible solution 18,19 , use of bases of rules 20,21,22 , and construction of grammars 23,24,25 .…”

Section: Knowledge Evaluationmentioning

confidence: 99%

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

Bouarab-Dahmani¹,

Si-Mohammed²,

Comparot³

et al. 2010

International Journal of Computational Intelligence Systems

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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.

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Section: Knowledge Evaluationmentioning

confidence: 99%

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

Bouarab-Dahmani¹,

Si-Mohammed²,

Comparot³

et al. 2010

International Journal of Computational Intelligence Systems

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“…This role is achieved through NLP tools dedicated to micro-tasks [13], and capable of solving issues of lexicon or morphology; the NLP tools provide a framework for analyzing the production of relatively predefined content. The language processing can be used to show grammatical errors directly to students in the system FreeText [14] or German Tutor [15]. The problems with these systems are the level of responses that we must give to the learner on his mistakes, especially in the case of multiple errors in a reply, the question being to know what mistakes we must resolve first.…”

Section: Level Of Nlp Integration In Salamentioning

confidence: 99%

Use of NLP Tools in CALL System for Arabic

Zrigui

Antoniadis

2012

Int. J. Comp. Proc. Lang.

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This article focuses on the development of Natural Language Processing (NLP) tools for Computer Assisted Language Learning (CALL). First, we have developed some NLP tools: a labelled dictionary of Arabic (as complete as possible), a generator for morphological derivatives, a Conjugator and a morphological analyzer for Arabic. Second, we used these tools to create a number of educational applications for learning the Arabic language by using the proposed system SALA (an NLP-based authoring system, organized into three distinct layers: functions, scripts and activities).

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