Title :
A GCSE maths tutoring game using neural networks
Author :
Lawren, William ; Carter, Jenny ; Ahmadi, Samad
Author_Institution :
Centre for Comput. Intell., De Montfort Univ., Leicester, UK
Abstract :
This paper investigates the use of neural networks to provide a challenging environment to motivate students of mathematics in further investigation of mathematical concepts. The research focuses on areas of shape, but similar methods could be used for a variety of mathematical topics. The paper presents a game in which a back-propagation neural network is trained by the player to compare areas of mathematical shapes. The original prototype in MATLAB is presented. A demonstration of the idea of a neural network as a opponent using the Python Programming Language further expands on this original work. The results show that a neural network can be used in a variety of ways to support students of differing levels of ability.
Keywords :
backpropagation; computer aided instruction; computer games; mathematics computing; neural nets; GCSE maths tutoring game; MATLAB; Python Programming Language; backpropagation neural network; mathematical concepts; mathematical shapes; mathematical topics; neural networks; Artificial neural networks; Games; MATLAB; Mathematics; Shape; Training;
Conference_Titel :
Games Innovations Conference (ICE-GIC), 2010 International IEEE Consumer Electronics Society's
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7178-2
Electronic_ISBN :
978-1-4244-7179-9
DOI :
10.1109/ICEGIC.2010.5716877