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In the collaborative serious game, adaptation is one of the main factors could be considered in the phase of conception since they can contribute to improve learning performance. Learning styles present one of the most factors that affect learning outcomes. Game-based learning (GBL) that takes into account learning styles in the process of adaptation, it furnishes to learners a greater benefit owing in the personalization of learning and contents materials according to their proper learning styles. In this paper, Adaptive system that personalize a collaborative serious game based on learning style proposed by Felder and Silverman is described. This system used trace and agent technology. A model of trace and group model are developed to extract adaptation knowledge in order to form plan that will be executed by Npc player. To evaluate a system, an experiment has been conducted on group of students. From the experimental results, it is concluded that the adaptive collaborative serious game based on learning style improve learning outcomes and effectiveness, and promote learning motivation. Subject Categories and Descriptors K.3.1 Computer Uses in Education] Collaborative learning I.2.6 [Learning] Knowledge acquisition General Terms: Collaborative Learning, Game Based Learning, Learning Style

Development of an Adaptive Collaborative Serious Game Based on Learning Style, Using Trace and Agent Technology