Ontology-Driven Adaptive and Pervasive Learning Environments – APLEs: An Interdisciplinary Approach

Soylu, Ahmet; Vandewaetere, Mieke; Wauters, Kelly; Jacques, Igor; Causmaecker, Patrick De; Desmet, Piet; Clarebout, Geraldine; Noortgate, Wim Van den

doi:10.1007/978-3-642-20074-8_9

Cited by 3 publications

(2 citation statements)

References 42 publications

(53 reference statements)

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“…We have presented a broad literature to set the given discussion into a concrete context, to put forward available work required to realise the discussed approach, and to identify current weaknesses in the related literature. Our future work includes the application of this approach for automated development of adaptive and pervasive learning environments (APLEs (Soylu et al, 2010c)) to provide a personalised, any-time and any-where learning experience.…”

Section: Discussionmentioning

confidence: 99%

Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review

Soylu

Causmaecker

Preuveneers

et al. 2011

IJMSO

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Abstract:Increasing demand for large scale and highly complex systems and applications, particularly with the emergence of pervasive computing and the impact of adaptive systems, introduces significant challenges for software development, as well as for user-machine interaction. Therefore, a perspective shift on software development and user-machine interaction is required. An amalgamation of model driven development and ontologies has been envisaged as a promising direction in recent literature. In this paper, we investigate this merged approach and conclude that a merger of both approaches, from formal modelling and knowledge representation perspective, on the one hand enables use of ontologies at run-time together with rules, prominently in terms of run-time reasoning, dynamic adaptations, software intelligibility, self-expressiveness, user involvement, and user situation awareness; and on the other hand at development time, prominently in terms of automated and incremental code generation, requirement adaptability, preservation of application knowledge, and validation and verification of structural and behavioural properties of the software. The core contribution of this paper lies in providing an elaborate and exploratory discussion of the problem and solution spaces along with a multidisciplinary meta-review and identification of complementary efforts in literature required to realise a merged approach.

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Section: Discussionmentioning

confidence: 99%

Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review

Soylu

Causmaecker

Preuveneers

et al. 2011

IJMSO

Self Cite

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“…Domain ontologies are widely used in educational and language processing solutions (Dahab et al , 2008; Wu and Hsu, 2002; Missikoff et al , 2002) and address a variety of domains with different characteristics in their structure and granularity depending on the aim of the solution and the modeling strategy of the ontology engineer (Gavrilova and Leshcheva, 2015). If the aim of the ontology is to support the task of learning, the ontology must express whether a concept requires the knowledge of another one or how a concept provides the details for other concepts (Soylu et al , 2011; Vas, 2007). These ontologies focus on explicitly answering the questions of “How do learners learn?” and “What do learners learn?” to be able to express all the knowledge requirements of the domain and the composition of the required knowledge.…”

Section: Connection-aware Semantic Learning Servicesmentioning

confidence: 99%

Implementing connectivism by semantic technologies for self-directed learning

Vas

Weber²,

Gkoumas³

2018

IJM

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Purpose Connectivism has been proposed to explain the impact of new technologies on learning. According to this approach, learning may occur even outside the individual within an organization or a system. Learning objectives are not defined in advance and learning requires the ability to form connections and use networks to find the required knowledge. The connections by which individuals can learn are more important than what they currently know. The purpose of this paper is to investigate if a measure, rating the importance of concepts, can be derived from a network representation of the learning domain and if highly connected concepts – with high importance value – can describe whether information is explored in such ways as assumed by connectivism. Design/methodology/approach The authors empirically examined if the proposed measure can provide insight on the role of connections in learning and explain the reasons behind passing certain parts of a test using a linear regression model. Findings The results are twofold. First, an implementation of the information exploration principle of connectivism has been introduced, applying semantic technologies and the importance measure. Second, although no significant effects could be isolated, trends in performance improvement concerning highly important concepts were identified. Originality/value However, connectivism has been known since 2005, it is still lacking for successful implementations. The presented approach of a concept importance measure is a promising starting point by providing means of connected learning, enabling individuals to effectively improve their personal abilities to better fit job demand.

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Extending Computerized Adaptive Testing to Multiple Objectives: Envisioned on a Case from the Health Care

Weber

Vas

2014

Electronic Government and the Information Systems Perspective

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Ontology-Driven Adaptive and Pervasive Learning Environments – APLEs: An Interdisciplinary Approach

Cited by 3 publications

References 42 publications

Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review

Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review

Implementing connectivism by semantic technologies for self-directed learning

Extending Computerized Adaptive Testing to Multiple Objectives: Envisioned on a Case from the Health Care

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