Emotion Detection in E-learning Using Expectation-Maximization Deep Spatial-Temporal Inference Network

2017 ◽  
pp. 245-252 ◽  
Author(s):  
Jiangqin Xu ◽  
Zhongqiang Huang ◽  
Minghui Shi ◽  
Min Jiang
Keyword(s):  
Expectation Maximization ◽  
Emotion Detection ◽  
Inference Network ◽  
E Learning ◽  
Temporal Inference

scholarly journals E-Learner's Academic Emotions Based on Facial Expressions : A Survey

2020 ◽  
pp. 265-273
Author(s):  
Snehal Rathi ◽  
Arnav Sakhariya ◽  
Jeet Shah ◽  
Mohit Sanghvi
Keyword(s):  
Facial Expressions ◽  
Affective Domain ◽  
Vital Role ◽  
Emotion Detection ◽  
Academic Emotions ◽  
Face To Face ◽  
E Learning ◽  
Face To Face Learning ◽  
Academic Emotion ◽  
Day By Day

This paper presents different technologies and framework used for academic emotion detection using facial recognition in E-Learning. E-Learning is growing day by day for various reasons like distance learning and user is able to do it at anytime and anywhere. But E-Learning lacks in real time feedback from the students to teachers and vice-versa. Academic Emotion plays an important role on detecting whether the students have understood the topic or not. In face to face learning, a skilled teacher achieves affective domain goals by interacting with the students and asking them questions. But in online learning student and teacher are apart so if system itself finds the emotion and take the action accordingly, is really very helpful to teacher and student both. There are various ways like sensors, facial expressions, log usage are used by many scientists to achieve this. We have researched and read many papers about various frameworks used and found that academic emotions play a vital role and also makes big difference in learning if it is properly analyzed and suitable action is taken. A model for the same purpose has been proposed here which will detect emotion and generate feedback accordingly.

Studying the Suitability of Discourse Analysis Methods for Emotion Detection and Interpretation in Computer-Mediated Educational Discourse

2013 ◽  
pp. 119-143
Author(s):  
Thanasis Daradoumis ◽  
Marta María Arguedas Lafuente
Keyword(s):  
Discourse Analysis ◽  
Classroom Interaction ◽  
Emotion Detection ◽  
Learning Contexts ◽  
Analysis Methods ◽  
Educational Environments ◽  
Computer Mediated ◽  
Depth Study ◽  
E Learning ◽  
Regulation Of Emotion

Conversation analysis (CA) and discourse analysis (DA) methods have been widely used to analyse classroom interaction in conventional educational environments and to some extent in e-learning environments, paying more attention to the ’quality’ and purposes the discourse serves to accomplish in its specific context. However, CA and DA methods seem to ignore emotion detection and interpretation when analysing learners’ interaction in online environments. Effective regulation of emotion, motivation and cognition in social interaction has been shown to be crucial in achieving problem-solving goals. The aim of this chapter is to provide an in-depth study on the possibility of applying discourse analysis methods in e-learning contexts with implications for emotion detection, interpretation and regulation. The result of this study shows whether a comprehensive approach that includes DA methodological solutions and constructivist strategies (e.g., cognitive dissonance) for emotion detection and interpretation can be elaborated and applied.

Studying the Suitability of Discourse Analysis Methods for Emotion Detection and Interpretation in Computer-Mediated Educational Discourse

2016 ◽  
pp. 1774-1799
Author(s):  
Thanasis Daradoumis ◽  
Marta María Arguedas Lafuente
Keyword(s):  
Discourse Analysis ◽  
Classroom Interaction ◽  
Emotion Detection ◽  
Learning Contexts ◽  
Analysis Methods ◽  
Educational Environments ◽  
Computer Mediated ◽  
Depth Study ◽  
E Learning ◽  
Regulation Of Emotion

Conversation analysis (CA) and discourse analysis (DA) methods have been widely used to analyse classroom interaction in conventional educational environments and to some extent in e-learning environments, paying more attention to the 'quality' and purposes the discourse serves to accomplish in its specific context. However, CA and DA methods seem to ignore emotion detection and interpretation when analysing learners' interaction in online environments. Effective regulation of emotion, motivation and cognition in social interaction has been shown to be crucial in achieving problem-solving goals. The aim of this chapter is to provide an in-depth study on the possibility of applying discourse analysis methods in e-learning contexts with implications for emotion detection, interpretation and regulation. The result of this study shows whether a comprehensive approach that includes DA methodological solutions and constructivist strategies (e.g., cognitive dissonance) for emotion detection and interpretation can be elaborated and applied.

E-Learning: Educating the 21st Century Speech-Language Pathologist

ASHA Leader ◽  
2007 ◽  
Vol 12 (14) ◽  
pp. 24-25 ◽  
Author(s):  
Gloria D. Kellum ◽  
Sue T. Hale
Keyword(s):  
21St Century ◽  
Speech Language Pathologist ◽  
E Learning

Auswirkungen eines E-Learning zum gesundheitsschädigenden Alkohol-konsum auf Wissen, Einstellung und Kompetenzen von Pflegefachpersonen im Akutspital – Eine Prätest-Posttest-Studie

Pflege ◽  
2018 ◽  
Vol 31 (4) ◽  
pp. 213-222
Author(s):  
Eva Evers ◽  
Sabine Hahn ◽  
Petra Metzenthin
Keyword(s):  
Präventive Maßnahmen ◽  
E Learning

Zusammenfassung. Hintergrund: Gesundheitsschädigender Alkoholkonsum ist weltweit der drittgrößte Risikofaktor für verschiedene Krankheiten und führt in der Schweiz zu 1.600 Todesfällen pro Jahr. Durch frühzeitiges Erkennen und präventive Maßnahmen können alkoholbezogene Krankheiten und Todesfälle verringert werden. Pflegefachpersonen nehmen dabei eine entscheidende Rolle ein. Jedoch stellen sich mangelndes Fachwissen, persönliche Einstellungen und Unsicherheiten als hindernde Faktoren dar. Schulungen helfen, diese Hindernisse zu überwinden. Ziel: Das Ziel der Studie war, die Auswirkungen eines E-Learning zum gesundheitsschädigenden Alkoholkonsum auf das Fachwissen, die Einstellung und die Selbsteinschätzung der Kompetenzen von Pflegefachpersonen eines Akutspitals zu untersuchen. Methode: Es wurde eine Prätest-Posttest-Studie durchgeführt. Im Zeitraum von Dezember 2013 bis März 2014 wurden insgesamt 33 diplomierte Pflegefachpersonen vor und nach der Durchführung des E-Learning befragt. Die Befragung erfolgte mithilfe eines literaturbasiert entwickelten Fragebogens. Ergebnisse: Das Fachwissen und die Selbsteinschätzung der Kompetenzen zeigten signifikante Verbesserungen. Eine Veränderung der Einstellung konnte nicht nachgewiesen werden. Schlussfolgerungen: Durch den Wissenszuwachs und die höher eingeschätzten Kompetenzen konnten Unsicherheiten abgebaut und das Vertrauen in die eigenen Fähigkeiten gestärkt werden. Um auch die Entwicklung wertneutraler Einstellungen gegenüber den Betroffenen zu fördern, wird empfohlen, neben dem E-Learning und der Einführung von Richtlinien, Präsenzveranstaltungen mit Möglichkeiten zum Austausch untereinander anzubieten.

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