DocumentCode :
1862234
Title :
Improving Conceptual Learning through Customized Knowledge Visualization
Author :
Gu, Qianyi ; Ahmad, Faisal ; Sumner, Tamara
Author_Institution :
Dept. of Comput. Sci., Sichuan Normal Univ., Chengdu, China
fYear :
2010
fDate :
9-10 Jan. 2010
Firstpage :
407
Lastpage :
410
Abstract :
This paper describes a customized scaffolding approach to improve learner´s conceptual understandings through knowledge visualization. We propose a framework to use natural language processing and graph based algorithms to automatic visualize individual learner´s prior knowledge states, domain knowledge, new encountered concepts and to reveal the semantic relationships between them. Thus, we are able to help learners to solve their uncertainties of new merging ideas and concepts in their learning process in order to integrate new knowledge with their preconceptions.
Keywords :
data visualisation; graph theory; knowledge representation; natural language processing; conceptual learning; customized knowledge visualization; customized scaffolding approach; graph based algorithm; natural language processing; Computer science; Data mining; Data visualization; Information resources; Knowledge representation; Merging; Natural language processing; Software libraries; Uncertainty; User interfaces; knowledge representation; user interfaces; visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on
Conference_Location :
Phuket
Print_ISBN :
978-1-4244-5397-9
Electronic_ISBN :
978-1-4244-5398-6
Type :
conf
DOI :
10.1109/WKDD.2010.68
Filename :
5432564
Link To Document :
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