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Mahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
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Schuler, Kathryn D.; Kodner, Jordan; Caplan, Spencer – First Language, 2020
In 'Against Stored Abstractions,' Ambridge uses neural and computational evidence to make his case against abstract representations. He argues that storing only exemplars is more parsimonious -- why bother with abstraction when exemplar models with on-the-fly calculation can do everything abstracting models can and more -- and implies that his…
Descriptors: Language Processing, Language Acquisition, Computational Linguistics, Linguistic Theory
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Wen, Dunwei; Cuzzola, John; Brown, Lorna; Kinshuk – International Review of Research in Open and Distance Learning, 2012
Question answering systems have frequently been explored for educational use. However, their value was somewhat limited due to the quality of the answers returned to the student. Recent question answering (QA) research has started to incorporate deep natural language processing (NLP) in order to improve these answers. However, current NLP…
Descriptors: Language Processing, Natural Language Processing, Distance Education, Online Courses
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Gutl, Christian; Lankmayr, Klaus; Weinhofer, Joachim; Hofler, Margit – Electronic Journal of e-Learning, 2011
Research in automated creation of test items for assessment purposes became increasingly important during the recent years. Due to automatic question creation it is possible to support personalized and self-directed learning activities by preparing appropriate and individualized test items quite easily with relatively little effort or even fully…
Descriptors: Test Items, Semantics, Multilingualism, Language Processing
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Diziol, Dejana; Walker, Erin; Rummel, Nikol; Koedinger, Kenneth R. – Educational Psychology Review, 2010
Research on computer-supported collaborative learning has shown that students need support to benefit from collaborative activities. While classical collaboration scripts have been effective in providing such support, they have also been criticized for being coercive and not allowing students to self-regulate their learning. Adaptive collaboration…
Descriptors: Student Problems, Learning Activities, Cooperation, Language Processing
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Wagner, Joachim; Foster, Jennifer; van Genabith, Josef – CALICO Journal, 2009
A classifier which is capable of distinguishing a syntactically well formed sentence from a syntactically ill formed one has the potential to be useful in an L2 language-learning context. In this article, we describe a classifier which classifies English sentences as either well formed or ill formed using information gleaned from three different…
Descriptors: Sentences, Language Processing, Natural Language Processing, Grammar
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Ellis, Nick C.; Simpson-Vlach, Rita; Maynard, Carson – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2008
Natural language makes considerable use of recurrent formulaic patterns of words. This article triangulates the construct of "formula" from corpus linguistic, psycholinguistic, and educational perspectives. It describes the corpus linguistic extraction of pedagogically useful formulaic sequences for academic speech and writing. It determines…
Descriptors: Psycholinguistics, Second Language Learning, Language Processing, Native Speakers