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

I. Nyoman Sukajaya*, Anik Vega Vitianingsih, S. N.Supeno Mardi, Ketut Eddy Purnama, Mochamad Hariadi, Mauridhi H. Purnomo

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationICCSE 2012 - Proceedings of 2012 7th International Conference on Computer Science and Education
Pages1666-1671
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 7th International Conference on Computer Science and Education, ICCSE 2012 - Melbourne, VIC, Australia
Duration: 14 Jul 201217 Jul 2012

Publication series

NameICCSE 2012 - Proceedings of 2012 7th International Conference on Computer Science and Education

Conference

Conference2012 7th International Conference on Computer Science and Education, ICCSE 2012
Country/TerritoryAustralia
CityMelbourne, VIC
Period14/07/1217/07/12

Keywords

  • Box-Muller
  • Game Scenario
  • Gaussian Distribution
  • Learning Mathematics

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