NON-INVASIVE DATA TRACKING IN EDUCATIONAL GAMES: COMBINATION OF LOGFILES AND NATURAL LANGUAGE PROCESSING

Within educational games one essential problem is how to gather user information without destroying the game play. Even though, there exist several possibilities of tracking the user behaviour, most of the objective behavioural data are ambiguous and lack subjective meaning. However, the assessment of subjective data by, e.g., questionnaires either destroys the game play or could be only made when the game has finished. The proposed methodological framework illustrates how the combination of data tracking by logfiles and Natural Language Processing (NLP) could lead to a more precise interpretation of user behaviour which in turn enables an optimization of adaptive user support in the context of serious games