ISCA International Workshop on Speech and Language Technology in Education (SLaTE 2011)
In this paper, we present a general method for optimizing a tutoring
system with a target application in the domain of second
language acquisition. More specifically, the optimisation process
aims at learning the best sequencing strategy for switching
between teaching and evaluation sessions so as to maximise
the increase of knowledge of the learner in an adapted manner.
The most important feature of the proposed method is that it is
able to learn an optimal strategy from a fixed set of data, collected
with a hand-crafted strategy. This way, no model (neither
cognitive nor probabilistic) of learners is required but only
observations of their behavior when interacting with a simple
(non-optimal) system. To do so, a particular batch-mode approximate
dynamic programming algorithm is used, namely the
Least Square Policy Iteration algorithm. Experiments on simulated
data provide promising results.
Index Terms. Tutoring systems, approximate dynamic programming
Bibliographic reference. Pietquin, Olivier / Daubigney, Lucie / Geist, Matthieu (2011): "Optimization of a tutoring system from a fixed set of data", In SLaTE-2011, 97-100.