filename : Bas11b.pdf entry : article conference : AIED 2011, Auckland, New Zealand, 28. June - 2. July, 2011 pages : 31-38 year : 2011 month : title : Modeling Engagement Dynamics in Spelling Learning subtitle : author : G.M. Baschera, A.G. Busetto, S. Klingler, J.M. Buhmann and M. Gross booktitle : Frontiers in Artificial Intelligence and Application ISSN/ISBN : editor : publisher : IOS Press publ.place : volume : 6738/2011 issue : language : English keywords : engagement modeling, feature processing, domain knowledge, dynamic Bayesian network, learning, spelling abstract : In this paper, we introduce a model of engagement dynamics in spelling learning. The model relates input behavior to learning, and explains the dynamics of engagement states. By systematically incorporating domain knowledge in the preprocessing of the extracted input behavior, the predictive power of the features is significantly increased. The model structure is the dynamic Bayesian network inferred from student input data: an extensive dataset with more than 150 000 complete inputs recorded through a training software for spelling. By quantitatively relating input behavior and learning, our model enables a prediction of focused and receptive states, as well as of forgetting.