Skip to main content

MathRun: An Adaptive Mental Arithmetic Game Using A Quantitative Performance Model.

Chen, L. and Tang, W., 2016. MathRun: An Adaptive Mental Arithmetic Game Using A Quantitative Performance Model. In: Ubiquitous Gaming Interaction Design Workshop, British HCI 2016 Conference, 12 July 2016, Bournemouth University.

Full text available as:

[img]
Preview
PDF
BHCI_GameWorkshop_MathRun.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

1MB

Abstract

Pedagogy and the way children learn are changing rapidly with the introduction of widely accessible computer technologies, from mobile apps to interactive educational games. Digital games have the capacity to embed many learning supports using the widely accredited VARK (visual, auditory, reading, and kinaesthetic) learning style. In this paper, we present a mathematics educational game MathRun for children age between 7-11 years old to practice mental arithmetic. We build the game as an interactive learning environment that fuses game mechanics with learning and uses the popular game genre “infinite runner” as the game mode. The game consists of an automatically generated infinite game map and mathematical questions also procedurally generated with varied levels of difficulty and complexity. A novel real-time performance evaluation method is developed for quantitative modeling the performance of the player. The model evaluates the performance in each primitive map block of the game map and level progression is automatically carried out based on the result of the evaluation. Therefore, the proposed game-based learning environment is adaptive to players with dynamic level progressions based on the combination of not only mathematics ability, but also gameplay skills of the player to facilitate learning processes through gameplay and appropriate adaptive progression of maths ability.

Item Type:Conference or Workshop Item (Paper)
Group:Faculty of Science & Technology
ID Code:24476
Deposited By: Symplectic RT2
Deposited On:08 Aug 2016 10:03
Last Modified:14 Mar 2022 13:57

Downloads

Downloads per month over past year

More statistics for this item...
Repository Staff Only -