DocumentCode
1571388
Title
Optimal grouping by using Genetic Algorithm and Support Vector Machines
Author
Lin, Kuan-Cheng ; Shiau, Mei-Lian ; Lin, Shu-Ying ; Tai, Jui
Author_Institution
Dept. of Manage. Inf. Syst., Nat. Chung Hsing Univ., Taichung, Taiwan
fYear
2009
Firstpage
777
Lastpage
782
Abstract
Nowadays with bloom of Internet technology, students can do their learning by digital learning platform even they are not in class. To diversify teaching and to improve effects in learning, many researchers strongly advocate cooperative learning and come out many essays in the field. When it comes to grouping, making group members help others, learning each other, and making students progressed in cooperative learning are prospective subjects. This investigation features collecting on-line learning processes and personal thinking styles of learners to select main characteristics influenced grouping by genetic algorithm. We also predict optimal grouping way which decided by support vector machine, one of machine learning. Finding best grouping model from varied characteristics helps teacher group easily and further the whole learning results in cooperative learning.
Keywords
Internet; computer aided instruction; genetic algorithms; learning (artificial intelligence); support vector machines; Internet technology; cooperative learning; digital learning platform; genetic algorithm; machine learning; on-line learning processes; support vector machines; teaching; Artificial intelligence; Biological cells; Education; Electronic learning; Genetic algorithms; Information systems; Internet; Machine learning; Support vector machine classification; Support vector machines; Cooperative Learning; Genetic Algorithm; Support Vector Machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Pervasive Computing (JCPC), 2009 Joint Conferences on
Conference_Location
Tamsui, Taipei
Print_ISBN
978-1-4244-5227-9
Electronic_ISBN
978-1-4244-5228-6
Type
conf
DOI
10.1109/JCPC.2009.5420079
Filename
5420079
Link To Document