Search results for "Intelligent Tutoring Systems"

showing 4 items of 4 documents

Semantics driven interaction using natural language in students tutoring

2007

The aim of this work is to introduce a semantic integration between an ontology and a chatbot in an Intelligent Tutoring Systems (ITS) to interact with students using natural language. The interaction process is driven by the use of a purposely defined ontology. In the ontology two types of conceptual relations are defined. Besides the usual relations, which are used to define the domain's structure, another type of relation is used to define the navigation schema inside the ontology according to the need of managing uncertainty. Uncertainty level is related to student knowledge level about the involved concepts. In this work we propose an ITS for the Java programming language called TutorJ…

Ontology Inference LayerComputer sciencecomputer.internet_protocolOntology (information science)Semanticscomputer.software_genreOWL-SIntelligent tutoring systemsLatent semantic analysisNatural language dialogueSemantic driven interactionSemantic navigationSemantic similaritySemantic computingSchema (psychology)Upper ontologySemantic integrationSemantic compressionSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionisemantic navigationLatent semantic analysisbusiness.industryOntology-based data integrationKnowledge levelIntelligent Tutoring SystemsOntologylatent semantic analysisArtificial intelligencesemantic driven interactionbusinesscomputernatural language dialogueNatural language processing
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The potential of temporal analysis: Combining log data and lag sequential analysis to investigate temporal differences between scaffolded and non-sca…

2020

This paper contributes to the ongoing discussion about analysing the temporal aspects of learning processes in the educational technology research field. Our main aim was to advance methods for analysing temporal aspects of technology-enhanced learning (TEL) processes by introducing the temporal lag sequential analysis (TLSA) technique and by combining TLSA with temporal log data analysis (TLDA). Our secondary aim was to illustrate the potential of these two analysis techniques to reveal the differences between the face-to-face technology-enhanced collaborative inquiry-based learning (CIBL) processes of three different conditions (non-scaffolded, writing scaffolded and script scaffolded gro…

General Computer ScienceComputer sciencescaffoldingcomputer.software_genre050105 experimental psychologyField (computer science)Computer-Supported Collaborative LearningEducationMoodleLog datatietokoneavusteinen oppiminentechnology-enhanced inquiry0501 psychology and cognitive sciencesyhteisöllinen oppiminenlag sequential analysisbusiness.industryGroup (mathematics)05 social sciencesEducational technology050301 educationIntelligent Tutoring SystemsLag sequential analysisAsynchronous communicationpostsecondary educationkorkeakouluopiskeluInquiry-based learningScreen captureArtificial intelligencebusinesscooperative/collaborative learning0503 educationcomputeroppimisprosessiNatural language processingComputers & Education
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Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow

2020

An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner and difficulty of the tasks such that the learner experiences a state of flow during the learning. Flow is a mental state that psychologists refer to when someone is completely immersed in an activity. Flow state is a multidisciplinary field of research and has been studied not only in psychology, but also neuroscience, education, sport, and games. The idea behind this paper is to try to achieve a flow state in a similar way as Elo’s chess skill rating (Glickman in Am Ches…

Stochastic point locationComputer scienceCognitive NeuroscienceGame ranking systemsAnalogyIntelligent tutoring system02 engineering and technologyField (computer science)Intelligent tutoring systemAdjusting delayed matching-to-sampleTask (project management)03 medical and health sciences0302 clinical medicineHuman–computer interaction0202 electrical engineering electronic engineering information engineeringStochastic point locationsVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550State of flowTrueSkillSpaced retrievalComputerized adaptive testingComputingMilieux_PERSONALCOMPUTINGIntelligent tutoring systemsOnline learning020201 artificial intelligence & image processingComputerized adaptive testingState (computer science)Adaptive task difficulties030217 neurology & neurosurgeryResearch ArticleAdaptive task difficultyCognitive Neurodynamics
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Improving Assessment of Students through Semantic Space Construction

2009

Assessment is one of the hardest tasks an Intelligent Tutoring System has to perform. It involves different and sometimes uncorrelated sub-tasks: building a student model to define her needs, defining tools and procedures to perform tests, understanding students' replies to system prompts, defining suitable procedures to evaluate the correctness of students' replies, and strategies to improve students' abilities after the assessment session.In this work we  present an improvement of our system, TutorJ, with particular attention to the assessment phase. Many tutoring systems offer only a limited set of assessment options like multiple-choice questions,fill-in-the-blanks tests or other types …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCorrectnessComputer sciencebusiness.industryProcess (engineering)Natural language understandingCognitive architecturecomputer.software_genreIntelligent tutoring systemKnowledge-based systemsKnowledge baseHuman–computer interactionIntelligent Tutoring Systems Semantic Space Construction Natural Language InteractionArtificial intelligencebusinesscomputerNatural languageNatural language processing
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