Learners automated evaluation with the ODALA approach

Bouarab-Dahmani, Farida; Si-Mohammed, Malik; Comparot, Catherine; Charrel, Pierre‐Jean

doi:10.1145/1529282.1529303

Cited by 8 publications

(5 citation statements)

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“…In this paper, we propose an instructional design and a platform for MOOC based on ODALA approach. This last was proposed in (Bouarab-Dahmani, Si-Mohammed, Comparot, & Charrel, 2009) for Computer-Based Human Learning Environment (CBHL) in general. This method supports both a domain knowledge representation and an automated evaluation of learners.…”

Section: Figure 1 Framework Of the Design And Evaluation Of Moocsmentioning

confidence: 99%

Collaborative MOOC Content Design and Automatic Assessment Based on ODALA Approach

Hammid

Haddadi

Bouarab-Dahmani

2017

Journal of Information Technology Research

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Since the fall of 2011, the Massive Open Online Course (MOOC) phenomenon is still being qualified as the most attractive and discussed subject by educational communities and public. In the literature, there are many researches about this recent e-learning generation that vary as the goals vary from raising pedagogical issues to economics ones. Several case studies state that MOOCs are challenging the use of technologies to enhance learning; others think that MOOCs can induce to disruptive in education and educational institutions. In this paper, we propose an instructional design for a kind of MOOC platforms where mainly the use of disciplines specifications and automated evaluation of MOOC learners are possible to settle the source of these problems. Our proposition is based on ODALA (Ontology-Driven Auto-evaluation Learning Approach) principles and on the disciplines' knowledge capitalization using a meta-model represented as domain ontology for disciplines modeling inspired by this approach.

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Section: Figure 1 Framework Of the Design And Evaluation Of Moocsmentioning

confidence: 99%

Collaborative MOOC Content Design and Automatic Assessment Based on ODALA Approach

Hammid

Haddadi

Bouarab-Dahmani

2017

Journal of Information Technology Research

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“…The ODALA approach proposes a methodology and techniques for developing an evaluation system based on teaching domain ontology Onto-TDM 4 . This approach provides designers of automated learning by doing systems a way of addressing the development problem of the evaluation system from two view points: the developer's and the user's [14].…”

Section: The Odala+ Approachmentioning

confidence: 99%

“…The main concepts used in Onto-TDM for teaching domain representation in the case of learning by doing are [1]: the evaluation units (a generic class concept where we find exercises, questions, …), the Notions which are structural components of the teaching domain, including in particular the knowledge items (KI) that are designated as the granular or smallest notions of the domain, and the potential errors of the learner when solving the domain's evaluation units. We also defined taxonomy for errors classification to facilitate their management in the evaluation system and the teaching domain model [2] where different types are proposed: form errors, semantic errors, specific semantic errors, syntactic errors … For an automated evaluation system development, the ODALA approach proposes five stages [3]: knowledge base construction by Onto-TDM instantiation, form ana- 4 ODALA+ process for designer, as shown by Fig. 2 adds two other steps to ODALA related to learner's profile calculation and automated generation of appropriate exercises.…”

Section: The Odala+ Approachmentioning

confidence: 99%

“…Our previous work about ontological teaching domain modelling [1] [2] and automated evaluation of learners' knowledge [3] [4] proposed the ODALA approach. This last, over the learning sessions outcomes assessment of the learner in terms of marks and indicators that allow a quantitative estimate of the learner's state of knowledge even when solving open questions.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Exercises Generation Using an Automated Evaluation and a Domain Ontology: The ODALA+ Approach

Bouarab-Dahmani¹,

Si-Mohammed²,

Comparot

et al. 2011

Int. J. Emerg. Technol. Learn.

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Generating adapted learning contents is one of the most important activity that can give the best progression of a learner. This is why research on personalization of learning is growing to get learning environments able to adapt the learning activities and contents to the learner’s profile. This last contains information about knowledge, skills, behavior, of the learner, at a given time of the learning process and for given domains. This information, to be effective, must be collected directly from an evaluation module that the learning system will systematically integrate in particular with the learning by doing mode. After the satisfactory results of our research on teaching domain modeling and automated evaluation of learner’s in the case of learning by doing exercises, we propose in this paper the ODALA+ approach which is an extension of the already proposed approach called ODALA (Ontology Driven Auto-evaluation Learning Approach) by adding two steps for learner’s profile calculation using the evaluation results and for generating adapted exercises

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“…In our preceding works on modeling disciplines and on learners automated evaluation [4] [5], we proposed the ODALA (Ontology Driven Auto-Evaluation Learning Approach) approach that describes an automated evaluation process based on a domain ontology a priori valuable for leaning by doing disciplines and tested with some computer sciences domains. After one or more training sessions, this process gives different evaluation results (marks, understanding indicators, errors …) which allow a quantitative estimate of learner"s knowledge state even under open questions.…”

Section: Introductionmentioning

confidence: 99%

Automated Evaluation of Learner‟s Solutions Expressed in a Graphical Language: Application to the Relational Databases Domain

Bouarab-Dahmani¹,

Mammeri²

2015

IJMECS

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This paper deals with one of our research directions on software tools enhancing self-learning in computer science disciplines. In this study, we discuss an experiment on relational data bases learning using a tool for the edition and automated evaluation of learners" solutions given as relational algebra trees. Indeed, in addition to the interest of the graphic languages for any training, the evaluation of our precedent works on modeling and evaluating solutions as algebraic expressions showed us some problems: first, there are various languages for the algebraic expressions. Second, among the detected errors by the prototype, developed in our precedent works for algebraic expressions, the form errors about the algebraic language have to be corrected before starting the semantic analysis. Third, in some cases, errors in the form have led to other non-committed errors which can cause inconsistencies in the errors" diagnosis process. Starting from these problems, the two principal objectives of the work presented in this article concern the algebraic trees construction and the evaluation assisted by a graphic tool which essentially consists in a semantic analysis as recommended in ODALA (ontology driven auto-evaluation learning approach) that we have already proposed. The tool was evaluated by a set of tests and experimented with second year LMD license students. These experiments results were interesting and showed that the tool is particularly helpful for novice students and their teachers.

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Learners automated evaluation with the ODALA approach

Cited by 8 publications

References 8 publications

Collaborative MOOC Content Design and Automatic Assessment Based on ODALA Approach

Collaborative MOOC Content Design and Automatic Assessment Based on ODALA Approach

Adaptive Exercises Generation Using an Automated Evaluation and a Domain Ontology: The ODALA+ Approach

Automated Evaluation of Learner‟s Solutions Expressed in a Graphical Language: Application to the Relational Databases Domain

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