Technical Note: \cal Q-Learning
Machine Learning
PAC model-free reinforcement learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Automatic question generation for vocabulary assessment
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Realizing Adaptive Questions and Answers for ICALL Systems
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
COGALEX '08 Proceedings of the workshop on Cognitive Aspects of the Lexicon
Measuring and predicting orthographic associations: modelling the similarity of Japanese kanji
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
EdAppsNLP 05 Proceedings of the second workshop on Building Educational Applications Using NLP
Vocabulary navigation made easier
Proceedings of the 15th international conference on Intelligent user interfaces
Kansuke: a kanji look-up system based on a few stroke prototypes
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
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Learning a foreign language is a long, error-prone process, and much of a learner's time is effectively spent studying vocabulary. Many errors occur because words are only partly known, and this makes their mental storage and retrieval problematic. This paper describes how an intelligent interface may take advantage of the access structure of the mental lexicon to help predict the types of mistakes that learners make, and thus compensate for them. We give two examples, firstly a dictionary interface which circumvents the tip-of-the-tongue problem through search-by-similarity, and secondly an adaptive test generator which leverages user errors to generate plausible multiple-choice distractors.