Oscar: an intelligent adaptive conversational agent tutoring system

Authors:
Annabel Latham;Keeley Crockett;David McLean;Bruce Edmonds
Affiliations:
Intelligent Systems Group, School of Computing, Mathematics & Digital Technology, Manchester Metropolitan University, Manchester, UK;Intelligent Systems Group, School of Computing, Mathematics & Digital Technology, Manchester Metropolitan University, Manchester, UK;Intelligent Systems Group, School of Computing, Mathematics & Digital Technology, Manchester Metropolitan University, Manchester, UK;Centre for Policy Modelling, Manchester Metropolitan University, Manchester, UK
Venue:
KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
Year:
2011

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Abstract

This paper presents an adaptive online intelligent tutoring system called Oscar which leads a tutoring conversation and dynamically predicts and adapts to a student's learning style. Oscar aims to mimic a human tutor by using knowledge of learning styles to adapt its tutoring style and improve the effectiveness of the learning experience. Learners can intuitively explore and discuss topics in natural language, helping to establish a deeper understanding of the topic and boost confidence. An initial study into the adaptation to learning styles is reported which produced encouraging results and positive test score improvements.