Sciweavers

AIED
2009
Springer

A Phoneme-Based Student Model for Adaptive Spelling Training

13 years 10 months ago
A Phoneme-Based Student Model for Adaptive Spelling Training
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. Keywords. spelling, student model, phoneme, adaptivity, error classification
Gian-Marco Baschera, Markus Gross
Added 25 May 2010
Updated 25 May 2010
Type Conference
Year 2009
Where AIED
Authors Gian-Marco Baschera, Markus Gross
Comments (0)