Enriching adaptation in e‐learning systems through a situation‐aware ontology network

Abstract

Purpose -The broader adoption of the internet along with web-based systems has defined a new way of exchanging information. That advance added by the multiplication of mobile devices has required systems to be even more flexible and personalized. Maybe because of that, the traditional teaching-controlled learning style has given up space to a new way of learning, which is more flexible and adequate to the learners needs. The purpose of this research is to go further into the semantic modeling of adaptive web based learning systems. Particularly, the paper focuses on those learning systems that consider in their definition the awareness of student's context in order to properly react to the student needs. Design/methodology/approach -In this paper the authors introduce a semantic model of the student context in terms of an ontology network. This semantic model is explored in order to detect the "current situation" of students when they are navigating into e-learning environments. The final objective is to enrich the adaptation functionality of e-learning environments, being able to evaluate context data from personal profile, learning domain and technological situation. Findings -In order to evaluate the semantic model defined, examples of detected situations are shown in accordance to specific e-learning scenarios. Originality/value -The paper covers definition of a flexible and modularized model by using ontology networks, which can be easily modified to incorporate new knowledge data, aiding the modeling of concepts from different learning environments.

A Proposed Ontology-Based Generic Context Model for Ubiquitous Learning

“…After that, these two metrics were used to estimate the Ontology Richness (oR) (Bouiadjra & Benslimane, 2011). Table 4 summarizes the metrics in concordance with the FOEval model (Bouiadjra & Benslimane, 2011), comparing the metrics of the proposed Ontology and the ontologies described in (Pernas et al, 2012;Abech et al, 2016).…”

“…As a golden standard, we used two ontologies described in (Pernas et al, 2012) and(abech et al, 2016). Our choice is based on two reasons: The first one is that, both works have many similarities with our ontology in conceptual terms; they aim to propose an ontology-based context model to be used within an adaptive and personalized learning system.…”

“…The second reason and the most important is that Abech (abech et al, 2016) has integrated in his work, an evaluation section of his ontology, and she has used the same metrics described in Foeval (Bouiadjra & Benslimane, 2011). Abech chose the work presented in (Pernas et al, 2012) as Golden standard because it allows access to his OWL files. This will allow us to exploit directly the data of the two works that are presented in Abech Evaluation section (abech et al, 2016) The metrics in Table 3 are extracted from the software Protégé, and they are used to calculate the Attribute Richness (aR) and the Relation Richness (rR) as proposed in FOEval (Bouiadjra & Benslimane, 2011).…”

Um modelo ubíquo para retriagem de pacientes baseado na Internet das coisas

“…Explorar essa trocaé o objetivo da ciência de contexto [Schilit et al 1994]. Ampliando esse conceito, [Marilza Pernas et al 2012] define que, através de ciência de situação,é possível proporcionar que aplicativos tenham a capacidade de perceber e compreender a situação atual, com a finalidade de antecipar ou prever sua demanda em um futuro próximo.…”

“…A Computação ubíqua (ou computação pervasiva)é usada para descrever a onipresença dos computadores no cotidiano das pessoas [Weiser 1991]. Assim, tem se desenvolvido aplicações cada vez mais adaptáveis, capazes de interpretar um contexto e antecipar futuras ações que devem ser efetuadas [Schilit et al 1994, Marilza Pernas et al 2012. Em função disso, esse trabalho se propõe a estudar a computação ubíqua com o objetivo de propor um modelo computacional para auxiliar os enfermeiros na retriagem de pacientes em emergências de hospitais usando também a Internet das coisas afim de detectar o melhor momento para efetuar a retriagem.…”