Intelligent and Affective Tutoring Systems - emerging trends and future possibilities [Keynote speech]

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Authors
Sarrafzadeh, Hossein
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Date
2013
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Type
Conference Contribution - Oral Presentation
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
elearning
intelligent tutoring systems
affective tutoring systems
computer-user interaction
Citation
Sarrafzadeh, A. (2013). Intelligent and Affective Tutoring Systems - emerging trends and future possibilities [Keynote speech]. Paper presented at The 3rd International eConference on Computer and Knowledge Engineering (ICCKE 2013), Ferdowsi University, Mashhad, Iran.
Abstract
Many software systems would significantly improve performance if they could adapt to the emotional state of the user, for example if e-learning systems, Automatic Teller Machines, ticketing machines and robotic systems could recognise when users were happy, confused, frustrated or angry they could interact and guide the user accordingly and improve the service. We believe that e-learning systems and especially intelligent tutoring systems (ITS) would be significantly enhanced if these systems could adapt to the emotions of learners. This idea has led to the development of Affective Tutoring Systems (ATSs): ATSs are ITSs that are able to adapt to the affective state of learners. This keynote address presents research leading to the development of an Affective Tutoring System which is the first of its kind and holds great promise for e-learning systems. The system utilises a computer systems, using a camera to detect learner's emotion through facial expressions and gestures and other significant bio-signals. The system is able to adapt to students and displays emotion via a lifelike agent called Eve. Eve’s tutoring adaptations are guided by a case-based reasoning method for adapting to student states; this method uses data that was generated by an observational study of human tutors. This talk presents the observational study, the case-based method, the ATS itself and the implementation of its emotion detection technology on a computer system for real-time performance, and finally the implications of the findings for Human Computer Interaction in general and e-learning in particular. Other applications of the technology especially in health developed in this research are discussed and future directions are presented.
Publisher
International eConference on Computer and Knowledge Engineering
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International eConference on Computer and Knowledge Engineering
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