Serveur d'exploration sur la recherche en informatique en Lorraine

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Tell Me What You See, I Will Tell You What You Remember

Identifieur interne : 000004 ( Main/Exploration ); précédent : 000003; suivant : 000005

Tell Me What You See, I Will Tell You What You Remember

Auteurs : Florian Marchal [France] ; Sylvain Castagnos [France] ; Anne Boyer [France]

Source :

RBID : Hal:hal-01305030

English descriptors

Abstract

Recommender systems usually rely on users’ preferences. Nevertheless, there are many situations, such as in intelligent tutoring systems, where recommendations of pedagogical resources should rather be based on their memory.So as to infer in real time and with low involvement what has been memorized by users, we propose in this paper toestablish a link between gaze features and visual memory. We designed a user experiment where 24 subjects had toremember 72 images. In the meantime, we collected 18,643 fixation points. Among other metrics, our results show astrong correlation between the relative path angles and the memorized items. It is thus possible to predict the users’memory status by analyzing their gaze data while interacting with the system, so as to provide recommendations thatfits their learning curve.

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Links toward previous steps (curation, corpus...)


Le document en format XML

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<term> Gaze data</term>
<term> Visual memory</term>
<term> recall</term>
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<div type="abstract" xml:lang="en">Recommender systems usually rely on users’ preferences. Nevertheless, there are many situations, such as in intelligent tutoring systems, where recommendations of pedagogical resources should rather be based on their memory.So as to infer in real time and with low involvement what has been memorized by users, we propose in this paper toestablish a link between gaze features and visual memory. We designed a user experiment where 24 subjects had toremember 72 images. In the meantime, we collected 18,643 fixation points. Among other metrics, our results show astrong correlation between the relative path angles and the memorized items. It is thus possible to predict the users’memory status by analyzing their gaze data while interacting with the system, so as to provide recommendations thatfits their learning curve.</div>
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