Multi-parameter dynamic difficulty game´s scenario using Box-Muller of Gaussian distribution

Scenario is an important aspect in a game. It controls players experience according to the scenario that has been composed. Diversity design of scenario and unpredicted event make the game more challenging. This paper investigates the usage of multi-parameter Box-Muller method of Gaussian distribution in adjusting dynamically game scenario. Those parameters are mean (μ) and standard deviation (σ). Scenario is designed at cave stage of pedagogical game Reog Ponorogo using mathematics problems as game´s challenge. Challenges are defined as six categories cognitive domain of Bloom taxonomy. Those categories are: knowledge, comprehension, application, analysis, synthesis, and evaluation. Problem domain includes the following: sequences and series, probability and mathematical logic. Box-Muller method is used to select five of ten available problems at random, and Gaussian distribution was used to dynamically adjusting difficulty level of problems in order to match player´s skill.