A GCSE maths tutoring game using neural networks

William Lawrence, Jenny Carter, Samad Ahmadi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageEnglish
Title of host publication2010 2nd International IEEE Consumer Electronic Society's Games Innovation Conference, ICE-GIC
Number of pages7
ISBN (Print)9781424471782
Publication statusPublished - 22 Feb 2011
Externally publishedYes
Event2nd International IEEE Consumer Electronic Society Games Innovation Conference - Hong Kong, China
Duration: 21 Dec 201023 Dec 2010
Conference number: 2


Conference2nd International IEEE Consumer Electronic Society Games Innovation Conference
Abbreviated titleICE-GIC 2010
CityHong Kong


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