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Inferring a Learner's Cognitive, Motivational and Emotional State in a Digital Educational Game

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Electronic Journal of e-Learning Volume 10, Number 2, ISSN 1479-4403


Digital educational games (DEGs) possess the potential of providing an appealing and intrinsically motivating learning context. Usually this potential is either taken for granted or examined through questionnaires or interviews in the course of evaluation studies. However, an "adaptive" game would increase the probability of a DEG being actually motivating and emotionally appealing. In order to adapt the game to the learner's motivational and emotional state "while" engaged with a particular game scenario, an ongoing assessment of these states is required. An explicit assessment, e.g. by questionnaires occurring repeatedly in short time intervals on the screen would probably destroy the learner's flow experience. Thus, it is necessary to apply an approach that assesses the learner's current states in a non-invasive way. In the course of this paper we describe such a non-invasive, implicit assessment procedure which is based on the interpretation of "behavioral indicators". A set of behavioral indicators has been elaborated whereby some of them are derived from the theory of "information foraging" (Pirolli and Card, 1999). Values for each behavioral indicator (e.g. amount, frequency, seconds, etc.) are gathered after equally long lasting "time slices". After each time slice, these values serve as weighted predictors to multiple regression equations for the dimensions of a motivation model, an emotion model and a construct called clearness. The motivation model is based on the two dimensions of "approach" and "avoidance motivation". The emotion model encompasses the dimensions "valence" and "activation". Clearness is defined as appropriate problem representation. A comparison of the resulting values on these dimensions between the current and previous time slices cove rs fluctuations of the learner's states over time. The assessment of such changes forms the prerequisite for providing in-game adaptations which aim to enhance the learner's state, targeting towards a full exploitation of DEGs' pedagogical potential. (Contains 2 tables and 2 figures.)


Bedek, M., Seitlinger, P., Kopeinik, S. & Albert, D. (2012). Inferring a Learner's Cognitive, Motivational and Emotional State in a Digital Educational Game. Electronic Journal of e-Learning, 10(2), 172-184. Retrieved December 16, 2019 from .

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