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

نویسندگان

  • Long Chen
  • Wen Tang
چکیده

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.

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تاریخ انتشار 2016