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.