DocumentCode :
3018003
Title :
A method for Development of collaborative learning by using a neural network and a genetic algorithm
Author :
Shin-Ike, Kazuhiro ; Iima, Hitoshi
Author_Institution :
Electr. & Inf. Eng., Maizuru Nat. Coll. of Technol., Kyoto, Japan
fYear :
2009
fDate :
23-25 March 2009
Firstpage :
1
Lastpage :
6
Abstract :
In school education, there are many kinds of learning styles, and it is known that group learning (collaborative learning) is more effective than individual learning. In collaborative learning, it is very important how to determine the optimal combination of students in order to improve the learning effect. In this paper, we propose a method to improve the learning effect of collaborative learning. A neural network model is first applied for predicting learning results of pairs of students in collaborative learning. Then, in order to determine the optimal pairs of students, a genetic algorithm is applied with the prediction results obtained from the neural network. Based on this combination of students, we carried out an experiment of collaborative learning at a college in Japan. It was confirmed from the experimental results that the proposed method was effective.
Keywords :
computer aided instruction; genetic algorithms; groupware; neural nets; collaborative learning; genetic algorithm; group learning; neural network; Collaboration; Collaborative work; Educational institutions; Educational technology; Genetic algorithms; Genetic engineering; Information science; Neural networks; Predictive models; Testing; Academic Background; Collaborative Learning; Genetic Algorithm; Neural Network; Personality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Autonomous Decentralized Systems, 2009. ISADS '09. International Symposium on
Conference_Location :
Athens
Print_ISBN :
978-1-4244-4327-7
Type :
conf
DOI :
10.1109/ISADS.2009.5207353
Filename :
5207353
Link To Document :
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