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Record W2495538722 · doi:10.1075/aals.9.07ch4

Chapter 4. Skill Acquisition Theory and the role of practice in L2 development

2013· book-chapter· en· W2495538722 on OpenAlexaff
Roy Lyster, Masatoshi Sato

Bibliographic record

VenueAILA applied linguistics series · 2013
Typebook-chapter
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsMcGill University
Fundersnot available
KeywordsDreyfus model of skill acquisitionSecond-language acquisitionConjunction (astronomy)Differential effectsContext (archaeology)Knowledge acquisitionComputer scienceProcedural knowledgePsychologyKnowledge managementCognitive psychologyLinguisticsKnowledge-based systems

Abstract

fetched live from OpenAlex

This chapter presents an overview of research in support of Skill Acquisition Theory and the claim that contextualized oral practice in conjunction with feedback promotes continued second language growth. Skill acquisition is explained as a gradual transition from effortful use to more automatic use of the target language, with the ultimate goal of achieving faster and more accurate processing. By reviewing different yet compatible theoretical orientations of knowledge representations (e.g., implicit/explicit knowledge, exemplar-based/rule-based representations), the interplay between declarative and procedural knowledge is explained as bidirectional and relative to the context of instruction. The differential effects of guided practice and communicative practice are addressed and their benefits in conjunction with feedback are highlighted through reference to classroom-based second language acquisition (SLA) research. Finally, future directions regarding research on practice effects and types of practice are suggested.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.196
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations84
Published2013
Admission routes1
Has abstractyes

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