filename     : Bas09.pdf
entry        : inproceedings
conference   : AIED 2009, Brighton, UK, 6-10 July, 2009
pages        : 614-616
year         : 2009
month        : July
title        : A Phoneme-Based Student Model for Adaptive Spelling Training
subtitle     : Phoneme-Based Student Model
author       : Gian-Marco Baschera and Markus Gross
booktitle    : Frontiers in Artificial Intelligence and Applications
ISSN/ISBN    : 978-1-60750-028-5
editor       : Vania Dimitrova, Riichiro Mizoguchi, Benedict du Boulay and Art Graesser
publisher    : IOS Press
publ.place   : Amsterdam
volume       : 200
issue        : 1
language     : English
keywords     : spelling, student model, phoneme, adaptivity, error classification
abstract     : We present a novel phoneme-based student model for spelling training. Our model is data driven, adapts to the user and provides information for, e.g., optimal word selection. We describe spelling errors using a set of features accounting for phonemic, capitalization, typo, and other error categories. We compute the influence of individual features on the error expectation values based on previous input data using Poisson regression. This enables us to predict error expectation values and to classify errors probabilistically. Our model is generic and can be utilized within any intelligent language learning environment.