DocumentCode :
2812208
Title :
An affective recognition-based architecture for intelligent learning environments
Author :
Yin, Gui-Mei ; Guo, Guang-Xingce
Author_Institution :
Comput. Sci. Dept., Tai Yuan Normal Univ., Taiyuan, China
Volume :
5
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
It is now widely accepted that intelligent learning environments are expected to care about both learners and tutors, and to have a good understanding of the variety of learning contexts. The key research question now is how to tackle the complex issues related to building learning systems that care, ranging from representing knowledge and context to modeling social, cognitive, metacognitive, and affective dimensions. In allusion to the absence of affective dimensions in traditional Intelligent Learning Environment (ILE), an improved architecture based on affective recognition is proposed in this paper. we add two components as emotion model and learning assessment model in the classical architecture proposed by Adriana da Silva (2008), which can get, recognize and analyse affective information of students´ learning performance, then affective stimulation and affective tutoring is implementation according to different students´ learning emotion, and then pass this information to affective information processing model. Pedagogical strategies can change accordingly to learners emotion, appropriately conduction of emotional motivation can help to achieve the best quality of learning.
Keywords :
computer aided instruction; learning (artificial intelligence); ontologies (artificial intelligence); affective dimension; affective recognition; affective stimulation; affective tutoring; cognitive dimension; emotion model; intelligent learning environment; learning assessment model; metacognitive dimension; pedagogical strategy; social dimension; Adaptation model; affective recognition; intelligent learning environments(ILE); ontology; semantic web;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5619187
Filename :
5619187
Link To Document :
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