Pedagogical Scenarization for Virtual Environments for Training: Towards Genericity, Coherence and Adaptivity

Mohamed, Fahim; Jakimi, Abdeslam; Bermi, Lahcen El

doi:10.22161/ijaers/3.12.20

Cited by 9 publications

(7 citation statements)

References 6 publications

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“…However, a number of further data, in particular, learner's feedback information is required to promote the functionality of the system. The ongoing work aims at including this proposed approach in our previous work [3], in order to generate adaptable and effective pedagogical scenarios for VET.…”

Section: Resultsmentioning

confidence: 99%

Personalization of learning activities within a virtual environment for training based on fuzzy logic theory

Mohamed¹,

Abdeslam²,

Lahcen³

2019

Math. Nat. Sci.

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The development of computers and multimedia technology has opened up new possibilities for training based on virtual reality. Virtual reality is the most powerful extension of simulation based systems. In virtual reality there is a move to three dimensional, multi-sensory interfaces. A virtual environment for training (VET) can be defined as a computer-generated environment based on virtual reality, to simulate the real world. Learning through a VET can personalize learning needs for learners to promote the quality of learning. However, learners can't be provided with appropriate learning activities because often there is no personalized service to respond to each learner's particular needs. The obvious solution is to generate learning activities based on each learner's profile. Yet it is a complex process, especially with the inaccuracy of data that may contains a learner's profile. The main goal of this paper is to associate suitable learning activities to each learner based on his profile, to do so, we propose to employ fuzzy logic technique, and the fuzzy inference system to handle reasoning under uncertainty and inaccuracy which is one major issue of great concern in learner model design.

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Section: Resultsmentioning

confidence: 99%

Personalization of learning activities within a virtual environment for training based on fuzzy logic theory

Mohamed¹,

Abdeslam²,

Lahcen³

2019

Math. Nat. Sci.

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show abstract

“…However, a number of further data, in particular, learners feedback information is required to promote the functionality of the system. The ongoing work aims at including this proposed approach in our previous work [28], in order to generate adaptable and effective pedagogical scenarios for VET.…”

Section: Resultsmentioning

confidence: 99%

Personalization of learning situations within a virtual environment for training based on fuzzy clustering

Mohamed¹,

Jakimi²,

Bermi³

2017

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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Advances in networks, computers and multimedia technology have changed traditional methods for learning and skills training. Nowadays, Virtual Environments for Training (VET) have been popular, they can provide an environment where virtual reality can be used to create interactive interfaces and real-time software that can control every response and action made by the user. VET have proven to be advantageous to put learners into varied training situations to acquire knowledge and competencies, especially when these situations are taking place in uncontrolled circumstances, or when they are dangerous, unrealizable, or expensive to establish in reality. However individual learners find it difficult to select suitable learning situations for their particular situation because often, there is no personalized service to response to the user needs. Personalization of learning in a VET is a very important way of improving the effectiveness and the quality of the training, yet it also a complex process that requires consideration of several factors such as learners profiles. The goal is to associate suitable learning situations to each learner based on his profile. However, personalization of learning becomes an issue with the uncertainty and imprecision of data that may contains a learner profile. To address this issue, this study is an attempt to integrate a fuzzy clustering into the process of the personalization of learning.

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“…The authors use a meta-model that provides an abstract representation of virtual environments both generic and machine readable. Fahim & al [16] ensured that the generic side of the POSVET pedagogical scenario model using the MASCARET meta-model, allows to reuse pedagogical scenarios on different platforms. We note that, MASCARET is a meta-model describing virtual environments and agents that evolve in this environment.…”

Section: Vrles Learning Scenario Modelsmentioning

confidence: 99%

A Process of Design and Production of Virtual Reality Learning Environments

Oubahssi

Mahdi

Piau-Toffolon

et al. 2019

The Challenges of the Digital Transformation in Education

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Facilitating human learning is one of the uses of virtual reality (VR). Users interact within original and dynamic situations of learning in an integrated learning environment called Virtual Reality Learning Environment (VRLE). Nevertheless, the design of these environments is still considered as a complex task. We intend to study and propose technical and methodological solutions to help teachers to design (adapt or reuse) their pedagogical situation with a scenario-based approach and to operationalize it in a VR learning environment. In this work, we defined a design process allowing teachers to generate their VRLE. Then, we instantiated the proposed design process with a pedagogical situation as an illustrated example.

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Pedagogical Scenarization for Virtual Environments for Training: Towards Genericity, Coherence and Adaptivity

Abstract: Abstract-

Cited by 9 publications

References 6 publications

Personalization of learning activities within a virtual environment for training based on fuzzy logic theory

Personalization of learning activities within a virtual environment for training based on fuzzy logic theory

Personalization of learning situations within a virtual environment for training based on fuzzy clustering

A Process of Design and Production of Virtual Reality Learning Environments

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