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AI Teaching Rounds: Orienting Graduate Medical Education Without the Hype. [PDF]
J Grad Med EducPreiksaitis C.
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Beyond comprehensible input: a neuro-ecological critique of Krashen's hypothesis in language education. [PDF]
Front PsycholNguyen QN, Doan DTH.
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Implicit artificial grammar learning in adults and children
, 2006 Poletiek, Fenna H., van den Bos, Esther
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Impaired artificial grammar learning in agrammatism
Cognition, 2010It is often assumed that language is supported by domain-specific neural mechanisms, in part based on neuropsychological data from aphasia. If, however, language relies on domain-general mechanisms, it would be expected that deficits in non-linguistic cognitive processing should co-occur with aphasia.
Morten H, Christiansen +3 more
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Abstraction Processes in Artificial Grammar Learning
The Quarterly Journal of Experimental Psychology Section A, 1997Four experiments explored the extent to which abstract knowledge may underlie subjects’ performance when asked to judge the grammaticality of letter strings generated from an artificial grammar. In Experiments 1 and 2 subjects studied grammatical strings instantiated with one set of letters and were then tested on grammatical and ungrammatical strings
D R, Shanks, T, Johnstone, L, Staggs
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2015
We consider Artificial Grammar Learning (AGL), which is a versatile methodological tool for the study of learning. AGL is fairly unique amongst learning paradigms, in that it allows an instantiation of a wide variety of theories of learning, including rules, similarity, and associative learning theories.
Eleni Ziori, Emmanuel Pothos
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We consider Artificial Grammar Learning (AGL), which is a versatile methodological tool for the study of learning. AGL is fairly unique amongst learning paradigms, in that it allows an instantiation of a wide variety of theories of learning, including rules, similarity, and associative learning theories.
Eleni Ziori, Emmanuel Pothos
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Surface features can deeply affect artificial grammar learning
Consciousness and Cognition, 2020Three experiments explored the extent to which surface features explain discrimination between grammatical and non-grammatical strings in artificial grammar learning (AGL). Experiment 1 replicated Knowlton and Squire's (1996) paradigm using either letter strings as in the original study, or an analogous set of color strings to further explore if ...
Jimenez, Luis +2 more
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