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A Web Application to Analyze Students’ Emotions and Attention

Aplicación web para el análisis de emociones y atención de estudiantes

dc.creatorPiedrahíta-Carvajal, Alejandro
dc.creatorRodríguez-Marín, Paula Andrea
dc.creatorTerraza-Arciniegas, Daniel F.
dc.creatorAmaya-Gómez, Mauricio
dc.creatorDuque-Muñoz, Leonardo
dc.creatorMartínez-Vargas, Juan David
dc.date2021-05-12
dc.date.accessioned2021-08-19T16:21:46Z
dc.date.available2021-08-19T16:21:46Z
dc.identifierhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1821
dc.identifier10.22430/22565337.1821
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/12073
dc.descriptionAnalyzing and monitoring students’ attention level in virtual environments allows teachers to take actions to improve teaching-learning processes. This study introduces the integration of two models, one for emotion recognition and one for attention analysis, both of them aimed at monitoring the interactions of students in virtual environments. Such integration was completed on a web platform employing the Flask framework, where the artificial intelligence models used to analyze the interaction can be executed. The results obtained show that teachers, as knowledge mediators, can use the platform to understand the behavior of the students in synchronous and asynchronous virtual environments and take actions to improve learning experiences. The results also highlight the advantages of employing the Model-View-Controller (MVC) pattern in web applications, using and integrating artificial intelligence techniques through the Flask framework.en-US
dc.descriptionEl análisis de emociones y el monitoreo del nivel de atención de los estudiantes en entornos virtuales permite a los docentes tomar acciones para mejorar los procesos de enseñanza-aprendizaje. Por esta razón, este trabajo presenta la integración de dos modelos: uno para el reconocimiento de emociones y otro para el análisis de atención, ambos con el objetivo de hacer monitoreo durante la interacción de un estudiante en entornos virtuales. Dicha integración se realiza en una plataforma web desarrollada en el entorno flask, en la que se pueden ejecutar los modelos de inteligencia artificial utilizados para la interacción. Los resultados obtenidos muestran que la plataforma podría ser utilizada por docentes como mediadores del conocimiento, para entender el comportamiento de los estudiantes en entornos virtuales tanto síncronos como asíncronos, y para tomar acciones que mejoren la experiencia de aprendizaje. Como ventaja adicional, los resultados aquí mostrados resaltan las ventajas que trae utilizar el Modelo Vista Controlador (MVC) en aplicaciones web, empleando e integrando técnicas de inteligencia artificial a través del framework Flask.es-ES
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dc.publisherInstituto Tecnológico Metropolitano (ITM)en-US
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dc.rightsCopyright (c) 2021 TecnoLógicasen-US
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0en-US
dc.sourceTecnoLógicas; Vol. 24 No. 51 (2021); e1821en-US
dc.sourceTecnoLógicas; Vol. 24 Núm. 51 (2021); e1821es-ES
dc.source2256-5337
dc.source0123-7799
dc.subjectWeb applicationen-US
dc.subjectAttention monitoringen-US
dc.subjectEmotion recognitionen-US
dc.subjectFacial recognitionen-US
dc.subjectAplicación webes-ES
dc.subjectmonitoreo de atenciónes-ES
dc.subjectreconocimiento de emocioneses-ES
dc.subjectreconocimiento de rostroses-ES
dc.titleA Web Application to Analyze Students’ Emotions and Attentionen-US
dc.titleAplicación web para el análisis de emociones y atención de estudianteses-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeResearch Papersen-US
dc.typeArtículos de investigaciónes-ES


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