DocumentCode :
615455
Title :
Visual exploration for time series data using multivariate analysis method
Author :
Wang Xiaohuan ; Yuan Guodong ; Wang Huan ; Hu Wei
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
fYear :
2013
fDate :
26-28 April 2013
Firstpage :
1189
Lastpage :
1193
Abstract :
In the online teaching activities, there are various teaching data accumulated as time series and many methods to analyze the quality of teaching. But there are no such methods which can emphasize the status perception of the teaching-learning and the interaction between the teachers and students. In this paper, we adopt multivariate analysis method to help teachers improve their teaching and to promote the students´ mastery of knowledge. We add the analysis of student learning status to reflect the students´ learning ability clearly. Through statistical analysis, clustering algorithm and visualization, users can distinguish the students of different abilities and use different educational strategies. Our system named as AVOJ, including multivariate visual analysis and data mining methods, is proved usefully both in teaching and learning instruction.
Keywords :
data mining; data visualisation; educational administrative data processing; pattern clustering; statistical analysis; teaching; time series; AVOJ; clustering algorithm; data mining method; educational strategy; learning instruction; multivariate analysis method; multivariate visual analysis; online teaching activity; statistical analysis; student learning status analysis; teaching quality analysis; time series data; visual exploration; visualization; Computers; Feature extraction; Visualization; Clustering; Information Visualization; Visual Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Education (ICCSE), 2013 8th International Conference on
Conference_Location :
Colombo
Print_ISBN :
978-1-4673-4464-7
Type :
conf
DOI :
10.1109/ICCSE.2013.6554098
Filename :
6554098
Link To Document :
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