An Emotion-Aware Learning Analytics System Based on Semantic Task Automation

Muñoz López, Sergio and Sánchez, Enrique and Iglesias Fernández, Carlos Ángel (2020). An Emotion-Aware Learning Analytics System Based on Semantic Task Automation. "Electronics", v. 9 (n. 8); pp. 1-24. ISSN 2079-9292. https://doi.org/10.3390/electronics9081194.

Description

Title: An Emotion-Aware Learning Analytics System Based on Semantic Task Automation
Author/s:
  • Muñoz López, Sergio
  • Sánchez, Enrique
  • Iglesias Fernández, Carlos Ángel
Item Type: Article
Título de Revista/Publicación: Electronics
Date: 2020
ISSN: 2079-9292
Volume: 9
Subjects:
Freetext Keywords: e-learning; emotion aware; semantic; task automation; emotion detection; emotion regulation
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

E-learning has become a critical factor in the academic environment due to the endless number of possibilities that it opens for the learning context. However, these platforms often suppose to increase the difficulties for the communication between teachers and students. Without having real contact between teachers and students, the former finds it harder to adapt their methods and content to their students, while the students also find complications for maintaining their focus. This paper aims to address this challenge with the use of emotion and engagement recognition techniques. We propose an emotion-aware e-learning platform architecture that recognizes students' emotions and attention in order to improve their academic performance. The system integrates a semantic task automation system that allows users to easily create and configure their own automation rules to adapt the study environment. The main contributions of this paper are: (1) the design of an emotion-aware learning analytics architecture; (2) the integration of this architecture in a semantic task automation platform; and (3) the validation of the use of emotion recognition in the e-learning platform using partial least squares structural equation modeling (PLS-SEM) methodology.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2015-68284-RSEMOLACarlos A. Iglesias; Tomás RoblesTecnologías de Análisis de Sentimientos y emociones para agentes sociales empáticos en inteligencia ambiental

More information

Item ID: 67506
DC Identifier: https://oa.upm.es/67506/
OAI Identifier: oai:oa.upm.es:67506
DOI: 10.3390/electronics9081194
Official URL: https://www.mdpi.com/2079-9292/9/8/1194
Deposited by: Memoria Investigacion
Deposited on: 04 Jul 2021 09:09
Last Modified: 04 Jul 2021 09:09
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