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1
Reflections on emerging language in adult learners of Nuwä Abigip an Indigenous language of California
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2
Dictogloss steals the show? Productive use of formulaic sequences by advanced learners
In: Lexis: Journal in English Lexicology, Vol 18 (2021) (2021)
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3
Developmental sequences in Austrian lower secondary learners' acquisition of English negation
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4
Sensibilidade precoce às combinações ortográficas entre crianças falantes do português europeu
Sucena, Ana. - : Centro Interdisciplinar de Estudos Educacionais, Escola Superior de Educação de Lisboa, 2017
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5
Vorfeldbesetzungen in deutschen Verb-Zweit-Sätzen als Lerngegenstand mit einer Untersuchung von Texten japanischer A1-LernerInnen
Ulmer, Carolin. - : Humboldt-Universität zu Berlin, 2017
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6
Vorfeldbesetzungen in deutschen Verb-Zweit-Sätzen als Lerngegenstand mit einer Untersuchung von Texten japanischer A1-LernerInnen ...
Ulmer, Carolin. - : Humboldt-Universität zu Berlin, 2017
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7
Aprendizaje y procesamiento de secuencias formulaicas con distintos grados de variabilidad
In: Electronic Thesis and Dissertation Repository (2016)
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8
The Development of Formulaic Sequences: A Longitudinal Learner Corpus Investigation
Elturki, Eman. - 2015
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9
The Acquisition of Formulaic Sequences in High-Intermediate ESL Learners
In: Publicly Accessible Penn Dissertations (2014)
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10
Long-Term Symbolic Learning
In: DTIC (2007)
Abstract: What are the characteristics of long-term learning? We investigated the characteristics of long-term, symbolic learning using the Soar and ACT-R cognitive architectures running cognitive models of two simple tasks. Long sequences of problems were run collecting data to answer fundamental questions about long-term, symbolic learning. We examined whether symbolic learning continues indefinitely, how the learned knowledge is used and whether computational performance degrades over the long term. We report three findings. First, in both systems, symbolic learning eventually stopped. Second, learned knowledge was used differently in different stages but the resulting production knowledge was used uniformly. Finally, both Soar and ACT-R do eventually suffer from degraded computational performance with long-term continuous learning. We also discuss ACT-R implementation and theoretic causes of ACT-R's computational performance problems and settings that appear to avoid the performance problems in ACT-R.
Keyword: *CONDITIONING(LEARNING); *LONG TERM LEARNING; *SYMBOLS; *WORD RECOGNITION; ACT-R; COMPUTATIONAL COGNITIVE MODELING; COMPUTATIONAL PERFORMANCE; COMPUTATIONS; DATA ACQUISITION; LEARNING; Linguistics; PATTERN RECOGNITION; Psychology; REPORTS; SEQUENCES; SYMBOLIC LEARNING; UTILITY PROBLEM
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA479991
http://www.dtic.mil/docs/citations/ADA479991
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11
Spoken Language Digital Libraries: The Million Hour Speech
In: http://www.ulib.org/conference/2006/1.pdf (2006)
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12
Emergence in second language writing: a methodological inroad
In: Revista Brasileira de Linguística Aplicada, Vol 13, Iss 2, Pp 493-515
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