Proposing the Underlying Causes That Lead to the Trainee’s Erroneous Actions to the Trainer

El-Kechaï, Naïma; Després, Christophe

doi:10.1007/978-3-540-75195-3_4

Cited by 3 publications

(5 citation statements)

References 12 publications

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“…During the realization of these collaborative works, our ITS follows the learners and then apply the algorithms depicted above for detecting learner's erroneous actions. Next, for interpreting the causes of errors, we use the classification scheme of error modes proposed in [5] which were particularly adapted to VET. Table 1 and Table 2 respectively illustrate results of retrospective analysis for the phenotype Sequence and Wrong object.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…We started by defining the Common Performance Conditions, then the direct and indirect relations between consequent-antecedent are modelled using a non-hierarchical data structure. Finally, the most probable cause-effect links could be found using Dempster-Shafer's theory presented in [5].…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…The objective is to determine how each factor (M,T,O) influences the training context. Here, we are inspired from the proposition presented in [5] using a predefined questionnaire which will be answered by the teacher before training session (cf. Figure 5).…”

Section: Define the Common Performance Conditions (Cpc's)mentioning

confidence: 99%

“…The "leaves" are terminal nodes (or "root" causes) whose antecedents list is empty. In order to calculate the certitude of choosing each node as a probable cause, we inherit the proposition presented in [5] using Dempster-Shafer's evidence theory:…”

Section: Algorithm 1 Retrospective Analysismentioning

confidence: 99%

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Modeling of Errors Realized by a Human Learner in Virtual Environment for Training

Trinh

Buche

Querrec

et al. 2009

INT J COMPUT COMMUN

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This study focuses on the notion of erroneous actions realized by human learners in Virtual Environments for Training. Our principal objective is to develop an Intelligent Tutoring System (ITS) suggesting pedagogical assistances to the human teacher. For that, the ITS must obviously detect and classify erroneous actions produced by learners during the realization of procedural and collaborative work. Further, in order to better support human teacher and facilitate his comprehension, it is necessary to show the teacher why learner made an error. Addressing this issue, we firstly modeling the Cognitive Reliability and Error Analysis Method (CREAM). Then, we integrate the retrospective analysis mechanism of CREAM into our existing ITS, thus enable the system to indicate the path of probable cause-effect explaining reasons why errors have occurred.

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Section: Experiments and Resultsmentioning

confidence: 99%

Section: Experiments and Resultsmentioning

confidence: 99%

Section: Define the Common Performance Conditions (Cpc's)mentioning

confidence: 99%

Section: Algorithm 1 Retrospective Analysismentioning

confidence: 99%

See 2 more Smart Citations

Modeling of Errors Realized by a Human Learner in Virtual Environment for Training

Trinh

Buche

Querrec

et al. 2009

INT J COMPUT COMMUN

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show abstract

“…Some projects aim at individualizing the simulation for each learner. This could be done for example through emotional agents (Ailiya et al, 2010) or by Hollnagel classification (El-Kechai and Desprès, 2007). At lower scale, some have highlighted the adaptability characteristic of ITS (Dos Santos and Osorio, 2004).…”

Section: Itsmentioning

confidence: 99%

A Pedagogical Scenario Language for Virtual Learning Environment based on UML Meta-model - Application to Blood Analysis Instrument

Corre

Hoareau

Ganier

et al. 2014

Proceedings of the 6th International Conference on Computer Supported Education

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Training to learn the use and maintenance of biomedical devices have various constraints. In order to complete these trainings, we proposed to use virtual reality based on pedagogical scenarios and Intelligent Tutoring Systems (ITS). In this paper, we first established the existing pedagogical scenario models and ITS. Subsequently we presented our proposal of a formal model based on the concept of learning organization by extension of UML in order to describre some pedagogical scenario and ITS. The use of this model is illustrated by an application of a virtual biomedical analyzer with the aim of learning the technical procedures of the device. Finally, we performed two experiments in order to verify the efficiency of virtual reality training.

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Educational Data Mining: A Review of the State of the Art

Romero

Ventura

2010

IEEE Trans. Syst., Man, Cybern. C

1,512

709

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Proposing the Underlying Causes That Lead to the Trainee’s Erroneous Actions to the Trainer

Cited by 3 publications

References 12 publications

Modeling of Errors Realized by a Human Learner in Virtual Environment for Training

Modeling of Errors Realized by a Human Learner in Virtual Environment for Training

A Pedagogical Scenario Language for Virtual Learning Environment based on UML Meta-model - Application to Blood Analysis Instrument

Educational Data Mining: A Review of the State of the Art

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