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Bayesian Modelling of Confusability of Phoneme-Grapheme Connections

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICALT.2007.83

Seventh IEEE International Conference ...

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	ASCII Text	x
	Mikko Vilenius, Janne V. Kujala, Ulla Richardson, Heikki Lyytinen, Toshio Okamoto, "Bayesian Modelling of Confusability of Phoneme-Grapheme Connections," Advanced Learning Technologies, IEEE International Conference on, vol. 0, no. 0, pp. 285-287, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007), 2007.

	BibTex	x
	@article{ 10.1109/ICALT.2007.83, author = {Mikko Vilenius and Janne V. Kujala and Ulla Richardson and Heikki Lyytinen and Toshio Okamoto}, title = {Bayesian Modelling of Confusability of Phoneme-Grapheme Connections}, journal ={Advanced Learning Technologies, IEEE International Conference on}, volume = {0}, year = {2007}, isbn = {}, pages = {285-287}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICALT.2007.83}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Advanced Learning Technologies, IEEE International Conference on TI - Bayesian Modelling of Confusability of Phoneme-Grapheme Connections SN - SP285 EP287 A1 - Mikko Vilenius, A1 - Janne V. Kujala, A1 - Ulla Richardson, A1 - Heikki Lyytinen, A1 - Toshio Okamoto, PY - 2007 KW - null VL - 0 JA - Advanced Learning Technologies, IEEE International Conference on ER -

Mikko Vilenius, University of Electro-Communications, Japan

Janne V. Kujala, University of Jyvaskyla, Finland

Ulla Richardson, University of Jyvaskyla, Finland

Heikki Lyytinen, University of Jyvaskyla, Finland

Toshio Okamoto, University of Electro-Communications, Japan

Deficiencies in the ability to map letters to sounds are currently considered to be the most likely early signs of dyslexia [4]. This has motivated the use of Literate, a computer game for training this skill, in several Finnish schools and households as a tool in the early prevention of reading disability.

In this paper, we present a Bayesian model that uses a student?s performance in a game like Literate to infer which phoneme-grapheme connections student currently confuses with each other. This information can be used to adapt the game to a particular student?s skills as well as to provide information about the student?s learning progress to their parents and teachers.

We apply our model to empirical data collected using Literate. Based on these data, we evaluate and compare using Bayesian methodology three different submodels with different restrictions on the possible confusability relations.

Citation:

Mikko Vilenius, Janne V. Kujala, Ulla Richardson, Heikki Lyytinen, Toshio Okamoto, "Bayesian Modelling of Confusability of Phoneme-Grapheme Connections," icalt,pp.285-287, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007), 2007

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