An Ontology for Personalization in Serious Games for Assessment

Serious Games have been widely used in learning, more specifically and more recently for stealth assessment of competencies. To guarantee a reliable assessment outcome, it is essential to keep on an engaging flow in the game, with the right balance between challenge and entertainment. This requires the adaptation of the game content, scenarios and difficulty level to the various profiles, portfolios, learning styles and gameplay style of the assessed players. In this paper, we propose an ontology to model player experience and its association with in-game personalization. On one hand, we use segmentation to define groups of players and we map them to various game changes and adaptations. On the other hand, we link games to academic programs objectives by expressing which competencies required by a given program are assessed by which set of game scenarios. Using our proposed ontology, we define a set of reasoning rules to propose to each player only those games that are tailored for her/his assessment path and player experience.