Research Reports

Permanent URI for this collectionhttp://dl.cerist.dz/handle/CERIST/34

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Author: search.filters.author.Bouabid, Mohamed AmineSubject: search.filters.subject.Remote Lab-Works

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    A Layered Architecture for online Lab-works: Experimentation in the Computer Science Education
    (CERIST, 2012) Bouabid, Mohamed Amine; Vidal, Phillipe; Broisin, Julien
    Practical competencies are key components of any computing education curriculum. Today, several computer experiment tools exist, however, these tools are originally intended to experts, and do not integrate very well into the existing online learning environments, in particular, they lack efficient support for teamwork, tutoring and instructional design. In this paper we introduce a model-driven engineering approach to transparently integrate remote computer experiments into distant learning curriculums. The originality of this framework stands on two key components: a middleware layer that acts as glue between existing Learning Management Systems and remote laboratories and a set of standard unifying and extensible models representing the whole system including its lab components, the versatile experiments and the actors’ actions.
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    A Generic Framework for Remote Practicals: Application to Computer Science and early feedbacks
    (CERIST, 2012) Bouabid, Mohamed Amine
    In this paper we present a model-driven based framework to guide efficiently the design and integration of remote computer experiments into distant learning curricula taking into the account the related educational considerations (especially efficient online teamwork and tutoring support). Our approach is centered on a specific pedagogical object: the lab experiment and based on a standard management meta-model to describe and interact with any concrete lab experiment during its whole lifecycle. These models are carried out by a three-tier architecture comprising: (1) The upper learning environment, (2) A middleware layer, and (3) The lower remote laboratories (2). The middleware exposes a homogeneous set of services to the learning layer to interact with the experiments’ models that are matched with the corresponding raw lab resources; giving the opportunity to develop innovative and educational end-user HCIs. A concrete application in the computer science area is developed, followed by an early usability testing which brought promoting results