DocumentCode
481962
Title
An inspection of a system for improving learning abilities 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
fYear
2008
fDate
10-13 Nov. 2008
Firstpage
3479
Lastpage
3484
Abstract
In this paper we propose a method to determine the optimal combination to improve learning effect through approaches of system engineering. A neural network model is applied for predicting the learning results of learners. This model has input values which are potential abilities and personalities of learners and has one output value which is the correctness rate for learning problems. In order to determine the optimal combination of learners, a genetic algorithm is applied by using the prediction results. An average value of scores in collaborative learning in an optimal combination of pairs of learners obtained through the use of a genetic algorithm is higher than that of scores in pairs based on a voluntary basis of learners. This proposed method can realize the combination of learners by a simple process.
Keywords
computer aided instruction; genetic algorithms; neural nets; collaborative learning ability; genetic algorithm; learner personality; neural network model; system engineering; system inspection; Collaborative work; Educational institutions; Genetic algorithms; Genetic engineering; Information science; Inspection; Neural networks; Predictive models; Systems engineering and theory; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, 2008. IECON 2008. 34th Annual Conference of IEEE
Conference_Location
Orlando, FL
ISSN
1553-572X
Print_ISBN
978-1-4244-1767-4
Electronic_ISBN
1553-572X
Type
conf
DOI
10.1109/IECON.2008.4758521
Filename
4758521
Link To Document