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
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;
Conference_Titel :
Industrial Electronics, 2008. IECON 2008. 34th Annual Conference of IEEE
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1767-4
Electronic_ISBN :
1553-572X
DOI :
10.1109/IECON.2008.4758521