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Record W2125400901 · doi:10.1080/09658416.2010.486439

Language awareness and second language pronunciation: a classroom study

2010· article· en· W2125400901 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLanguage Awareness · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsConcordia University
FundersConcordia University
KeywordsPronunciationPsychologyMetalinguisticsFluencyActive listeningContext (archaeology)Language assessmentLanguage acquisitionLinguisticsQualitative researchSet (abstract data type)Class (philosophy)Quality (philosophy)Language educationMathematics educationTeaching methodComputer scienceVocabulary developmentCommunicationArtificial intelligence

Abstract

fetched live from OpenAlex

We examined the relationship between the quality of second language (L2) learners’ language awareness (as shown through dialogue journal entries) and the quality of their L2 pronunciation (as assessed through listener-based ratings of accentedness, comprehensibility, and fluency). The participants were 10 students enrolled in a 13-week university-level pronunciation course focusing on the suprasegmental aspects of English. We evaluated the students’ pronunciation during week 1 and week 11 of class and examined weekly dialogue journal entries written by the students over 10 weeks for evidence of language awareness. We analysed the comments for aspects of language awareness which were quantitative (language learning as assimilating a set of discrete items) and qualitative (language learning as a meaningful context in which learning occurs). We found a relationship between the students’ pronunciation ratings and the number of qualitative (not quantitative) language awareness comments, such that higher pronunciation ratings were associated with a greater number of qualitative language awareness comments. We also found that the students who produced the most qualitative language awareness comments were those who reported the largest amount of L2 listening done outside of class. We discuss the results in light of the role of language awareness in L2 pronunciation learning.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.018
GPT teacher head0.278
Teacher spread0.261 · 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