Employing Textual and Facial Emotion Recognition to Design an Affective Tutoring System

Autor/inn/en	Lin, Hao-Chiang Koong; Wang, Cheng-Hung; Chao, Ching-Ju; Chien, Ming-Kuan
Titel	Employing Textual and Facial Emotion Recognition to Design an Affective Tutoring System
Quelle	In: Turkish Online Journal of Educational Technology - TOJET, 11 (2012) 4, S.418-426 (9 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1303-6521
Schlagwörter	Foreign Countries; Intelligent Tutoring Systems; Artificial Intelligence; Focus Groups; Teaching Methods; Feedback (Response); Grounded Theory; Psychological Patterns; Nonverbal Communication; Computer Assisted Instruction; Computer Software Evaluation; Programming; Animation; Natural Language Processing; Computer System Design; Educational Technology; Multimedia Instruction; Usability; Use Studies; Mixed Methods Research; Rating Scales; Man Machine Systems; Affective Behavior; Taiwan; Motivated Strategies for Learning Questionnaire + Suchen Sie Ihr Suchwort? Ausland; Intelligentes Tutorsystem; Künstliche Intelligenz; Teaching method; Lehrmethode; Unterrichtsmethode; Non-verbal communication; Nonverbale Kommunikation; Computer based training; Computerunterstützter Unterricht; Softwareanalyse; Programmierung; Natürliche Sprache; Unterrichtsmedien; Multimediales Lernen; Benutzerschulung; Rating-Skala; Mensch-Maschine-System; Affective disturbance; Active behaviour; Affektive Störung
Abstract	Emotional expression in Artificial Intelligence has gained lots of attention in recent years, people applied its affective computing not only in enhancing and realizing the interaction between computers and human, it also makes computer more humane. In this study, emotional expressions were applied into intelligent tutoring system, where learners' emotional expression in learning process was observed in order to give an appropriate feedback. Emotional intelligent not only gives high flexibility to the interaction of tutoring system, it also to deepen its level of human interaction. This study uses dual-mode operation: facial expression recognition, and text semantics as the main elements in affective computing to understand users' emotions. Text semantics are used to understand learners' learning status, and the results would contribute to course management agents in order to choose the most appropriate teaching strategies and feedback to the users. Facial expression recognition allows interactive agents to provide users a complete sound and animation feedback. (Contains 5 tables and 3 figures.) (As Provided).
Anmerkungen	Sakarya University. Esentepe Campus, Adapazari 54000, Turkey. Tel: +90-505-2431868; Fax: +90-264-6141034; e-mail: tojet@sakarya.edu.tr; Web site: http://www.tojet.net
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10