Design and Implementation of Technology Enabled Affective Learning Using Fusion of Bio-Physical and Facial Expression

Autor/inn/en	Ray, Arindam; Chakrabarti, Amlan
Titel	Design and Implementation of Technology Enabled Affective Learning Using Fusion of Bio-Physical and Facial Expression
Quelle	In: Educational Technology & Society, 19 (2016) 4, S.112-125 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1436-4522
Schlagwörter	Program Implementation; Technology Uses in Education; Affective Objectives; Affective Behavior; Affective Measures; Biofeedback; Emotional Response; Electronic Learning; Nonverbal Communication; Courseware; Pretesting; Computer System Design; College Students; Foreign Countries; India + Suchen Sie Ihr Suchwort? Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Affective disturbance; Active behaviour; Affektive Störung; Emotionales Verhalten; Non-verbal communication; Nonverbale Kommunikation; Lernsoftware; Vortest; Collegestudent; Ausland; Indien
Abstract	Technology Enabled Learning is a cognitive, constructive, systematic, collaborative learning procedure, which transforms teaching-learning pedagogy where role of emotion is very often neglected. Emotion plays significant role in the cognitive process of human being, so the transformation is incomplete without capturing the learner's emotional state. This paper, proposes a new Affective Computing Module in E-Learning system that focuses on capturing of emotional aspects, managing learning activities, timing and their reflection on the overall learning process. Human Computer Interaction aims at recognizing the learner's emotional state in order to provide a horizontal interface between human and computer. We have adopted bio-physical (Heart Rate, Skin Conductance and Blood Volume Pressure) and facial expression methods, as these can be made both in-obtrusive and robust against number of environmental conditions, to extract affective state of the learner. This study explores how emotion evolves during the learning process and how emotion feedback is used to improve learning experiences. We propose a learner emotion detection and automated lesson selection model, where two emotion attributes have been fused and achieved an efficient model for "Affective E-Learning System," which obtained the sound classification rate. The system can select the learning pedagogy of the learner from detected emotion through neuro-fuzzy logic. Our research shows reasonable results in comparison with the existing systems. The result proves that the recognizer system is efficient. (As Provided).
Anmerkungen	International Forum of Educational Technology & Society. Athabasca University, School of Computing & Information Systems, 1 University Drive, Athabasca, AB T9S 3A3, Canada. Tel: 780-675-6812; Fax: 780-675-6973; Web site: http://www.ifets.info
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01