A model for learning objects adaptation in light of mobile and context-aware computing

Abstract

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The use of Ontologies in the Development of a Mobile E-Learning Application in the Process of Staff Adaptation

“…TheT mostT strikingT solutionsT andT researchT resultsT withT positiveT resultsT areT presentedT byT theT authorsT inT [6,T 7],T whoT proposedT theT OntoAdaptT ontologyT andT theT EduAdaptT architecturalT modelT forT adaptingT learningT objectsT takingT intoT accountT theT characteristicsT ofT aT mobileT device,T learningT styleT andT otherT contextualT information:T «WeT evaluateT thisT proposalT inT twoT ways.T Firstly,T weT usedT scenariosT andT metricsT toT assessT theT ontology.T Secondly,T weT developedT aT prototypeT ofT EduAdaptT modelT andT submittedT toT aT classT ofT 20T studentsT withT theT intentionT ofT evaluatingT theT usabilityT andT adherenceT toT adaptedT objects,T resultingT inT aT 78T %T ofT acceptance.T InT brief,T theT evaluationT presentedT encouragingT results,T indicatingT thatT theT proposedT modelT wouldT beT usefulT inT theT learningT process»T [6].T «WeT believeT thatT theT strengthsT ofT virtualT learningT systems,T targetedT atT mobileT devices,T canT beT improvedT byT minglingT contextT awarenessT withT contentT adaptation.T TheT contextT awarenessT isT formedT byT dataT regardingT usersT andT theirT surroundings,T suchT asT locationT data,T learningT objective,T knowledgeT historyT andT preferences,T amongT others.T ContentT adaptation,T accordingly,T canT personalizeT theT learningT objectT toT meetT thisT context.T ForT example,T considerT theT followingT scenario:T aT learner,T drivingT herT carT toT theT University,T mayT needT informationT regardingT theT courseT inT whichT sheT willT haveT anT examinationT inT aT fewT minutes.T AnT applicationT inT herT mobileT phone,T usingT contextT awareness,T canT suggestT aT learningT objectT relatedT toT theT examination»T [7].T TheT processT ofT studentT adaptationT isT alsoT ofT greatT importance:T «TheT adaptationT processT startsT inT theT client,T byT gatheringT theT currentT learningT context.T ThisT informationT consistsT ofT theT deviceT characteristics,T includingT theT deviceT model,T theT batteryT level,T availableT storageT capacity,T screenT sizeT andT operatingT systemT version.T ThisT informationT isT usefulT toT chooseT deT appropriateT LOT accordingT toT devicesT limitations,T suchT asT screenT sizeT andT multimediaT capabilities.T BesidesT theseT characteristics,T theT clientT sendsT informationT regardingT theT connection:T networkT signalT strengthT andT typeT ofT connectionT (3G,T 4G,T WiFi,T etc. ).T Finally,T thereT isT aT groupT ofT dataT relatedT toT theT user,T includingT whetherT theT userT isT stationaryT orT inT movementT andT theT currentT location»T [7].…”

The State of the Art in Methodologies of Course Recommender Systems—A Review of Recent Research

“…In the selected list, we found only one course RS on pure KBRS. This research proposed ontology-based learning objects adaptation by considering students learning style, preference, profile and background [136].…”

A Proposed Ontology-Based Generic Context Model for Ubiquitous Learning

“…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.…”