Towards Advanced Learner Modeling: Discussions on Quasi Real-time Adaptation with Physiological Data

Blanchard, Emmanuel; Chalfoun, Pierre; Frasson, Claude

doi:10.1109/icalt.2007.264

Cited by 9 publications

(8 citation statements)

References 12 publications

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“…That data is then used to model the learner's emotional and physiological profile in order to better adjust and adapt learning accordingly [3]. Learning in virtual worlds has taken a very important part in the HCI community for recent evidence has shown the relevance of using such virtual ITS for affective feedback and adaptation [3,4]. Nevertheless, the current learning strategies have a limitation when it comes to processing complex information.…”

Section: Introductionmentioning

confidence: 99%

“…The availability, ease of use and affordability of physiological devices helped in their integration into the tutoring systems. That data is then used to model the learner's emotional and physiological profile in order to better adjust and adapt learning accordingly [3]. Learning in virtual worlds has taken a very important part in the HCI community for recent evidence has shown the relevance of using such virtual ITS for affective feedback and adaptation [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Affective Conditions for Subconscious Learning in a 3D Intelligent Tutoring System

Chalfoun

Frasson

2009

Lecture Notes in Computer Science

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Abstract. In this paper we take a closer and in-depth look at initial results obtained from a previous novel experiment conducted with a 3D subliminal teaching Intelligent Tutoring System. Subliminal priming is a technique used to project information to a learner outside of his perceptual field. Initial results showed great promise by illustrating the positive impact of the subliminal module on the overall emotional state of the learners as well as their learning performances. Indeed, since emotion monitoring is critical in any learning context, we monitored the physiological reactions of the user while they learned and while they answered questions. We present a detailed and precise look at the optimal affective conditions that set the best learners apart. We will also explain a most surprising finding: the positive long term impact of subliminal priming on the entire learning process.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Affective Conditions for Subconscious Learning in a 3D Intelligent Tutoring System

Chalfoun

Frasson

2009

Lecture Notes in Computer Science

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“…This is not surprising since emotions, especially motivation and engagement, are widely related in various cognitive tasks as described earlier in this chapter. Learning in virtual worlds has taken a very important part in the HCI community for recent evidence has shown the relevance of using such virtual ITS for affective feedback and adaptation (Blanchard et al 2007;McQuiggan and Lester 2006). Nevertheless, cognitive learning theories base mostly their intervention on attention to the specified task at hand.…”

Section: Subliminal Learningmentioning

confidence: 99%

Managing Learner’s Affective States in Intelligent Tutoring Systems

Frasson

Chalfoun

2010

Studies in Computational Intelligence

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Abstract. Recent works in Computer Science, Neurosciences, Education, and Psychology have shown that emotions play an important role in learning. Learner's cognitive ability depends on his emotions. We will point out the role of emotions in learning, distinguishing the different types and models of emotions which have been considered until now. We will address an important issue concerning the different means to detect emotions and introduce recent approaches to measure brain activity using Electroencephalograms (EEG). Knowing the influence of emotional events on learning it becomes important to induce specific emotions so that the learner can be in a more adequate state for better learning or memorization. To this end, we will introduce the main components of an emotionally intelligent tutoring system able to recognize, interpret and influence learner's emotions. We will talk about specific virtual agents that can influence learner's emotions to motivate and encourage him and involve a more cooperative work, particularly in narrative learning environments. Pushing further this paradigm, we will present the advantages and perspectives of subliminal learning which intervenes without conscious perception. Finally, we conclude with new directions to emotional learning. Emotions and LearningLearning involves mainly two processes: reasoning and memorizing. Reasoning is developed during cognitive tasks in which a learner tries to solve a problem using deductions or inductions. If a new knowledge (fact, rule) is obtained then the knowledge will be memorized in long term memory. Memorizing is also triggered when a learner tries to remember a previously acquired element using several means such as similarity, imagery, case-based analysis, etc. The two processes work alternatively and can be considered as a "Cartesian" approach of brain functions. Recent researches in neurosciences, education, and psychology have shown that emotions play an important role in learning. People often separate emotions and reason, believing that emotions are an obstacle in rational decision making or

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“…Des solutions ont déjà été proposées pour permettre une telle analyse (Qu et al, 2004). De notre côté, nous étudions la prise en compte des données physiologiques des apprenants en vue d'atteindre cet objectif (Blanchard et al, 2007).…”

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“…Son rôle est d'une part de transmettre à l'agent de modélisation des apprenants, les informations permettant la mise à jour du profil de l'apprenant. Ces informations sont obtenues en scrutant les interactions de l'apprenant dans l'interface graphique (clics de souris, activité de l'avatar, réponses à des questionnaires...) ou par l'intermédiaire de modules extérieurs permettant, par exemple, la prise en compte de données provenant de capteurs physiologiques (Blanchard et al, 2007). D'autre part, le rôle de notre agent de scrutation est de répercuter les ordres provenant notamment des agents pédagogiques et visant à afficher des données d'apprentissage.…”

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Un système tutoriel intelligent inspiré des jeux vidéo pour améliorer la motivation de l’apprenant

Blanchard¹,

Frasson²

2007

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Dans cet article, nous discutons de recommandations dont l'objectif est de faciliter la conception et le développement de Systèmes Tutoriels Intelligents (STI) pouvant améliorer ou, tout du moins, maintenir à un niveau satisfaisant la motivation de leurs apprenants durant une activité d'apprentissage. Ces recommandations s'inspirent des recherches liées à la théorie de l'autodétermination. Cette dernière identifie trois besoins psychologiques innés dont la satisfaction conditionne la qualité de la motivation d'un individu. Ces besoins concernent les niveaux d'autonomie, de compétence et de relationnel ressentis par cet individu. Le prototype d'un STI développé en fonction de ces recommandations est ensuite décrit et les résultats d'une étude exploratoire portant sur l'appréciation de ce système par des élèves de CM2 sont présentés de manière à soutenir la pertinence de nos recommandations. MOTS CLÉS : système tutoriel intelligent, motivation, soutien à l'autonomie, système multi-agents, environnement ludo-éducatif.

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Towards Advanced Learner Modeling: Discussions on Quasi Real-time Adaptation with Physiological Data

Abstract: Abstract

Cited by 9 publications

References 12 publications

Optimal Affective Conditions for Subconscious Learning in a 3D Intelligent Tutoring System

Optimal Affective Conditions for Subconscious Learning in a 3D Intelligent Tutoring System

Managing Learner’s Affective States in Intelligent Tutoring Systems

Un système tutoriel intelligent inspiré des jeux vidéo pour améliorer la motivation de l’apprenant

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