An Application of GOMS Model to Analyse and Predict Gamer Behaviours in MMORPG

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Author(s)
Song, Seungkeun
Jo, Jun Hyung
Eboueya, Michel
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N E Gough and Q H Mehdi

Date
2008
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Abstract

The main objective of this research is to build a behavior prediction model of Massively Multiplayer Online Role-playing Game (MMORPG) gameplay using the GOMS analysis method. GOMS analysis (Card et al. 1983) is an observational approach to Human Computer Interaction (HCI) to model and predict behaviors of a human operator in a highly interactive task. This method has been employed by many researchers in order to model and predict the behaviors of gamers (or computer game players). However, it is rare to find its application in the MMORPG game genre. In this research, a pilot experiment was previously conducted with three skilled gamers. The gamers were provided with the goals and operators through the user's guide book, and they found methods and selection rules while being observed (Song et al., 2006). Based on the results obtained from the pilot study, this research was expanded and the model was further tested with 30 subjects (gamers). The new outcomes revealed that the relevance of GOMS analysis for predicting selection rules is 96.25% according to the degree of abstraction and 77.35% based on the degree of complexity. This research will provide game designers with a new testing mechanism in the early development stages, in order to improve the quality of the game product.

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The International Journal for Intelligent Games and Simulation (IJIGS)

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5

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1

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Computer-Human Interaction

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