Game interaction state graphs for evaluation of user engagement in explorative and experience-based training games

There is an increasing interest to use computer games for non-traditional education, such as for training purposes. For training education, simulators are considered as offering more realistic learning environments to experience situations that are similar to real world. This type of learning is more beneficial for practicing critical situations which are difficult or impossible in real world training, for instance experience the consequences of unsafe driving. However, the effectiveness of simulation-based learning of this nature is dependent upon the learner's engagement and explorative behaviour. Most current learner evaluation systems are unable to capture this type of learning. Therefore, in this paper we introduce the concept of game interaction state graphs (GISGs) to capture the engagement in explorative and experience-based training tasks. These graphs are constructed based on rules which capture psychologically significant learner behaviours and situations. Simple variables reflecting game state and learner's controller actions provide the ingredients to the rules. This approach eliminates the complexity involved with other similar approaches, such as constructing a full-fledged cognitive model for the learner. GISGs, at minimum, can be used to evaluate the explorative behaviour, the training performance and personal preferences of a learner.