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Record W1905125945 · doi:10.18806/tesl.v31i0.1186

The Quantity and Quality of Language Practice in Typical Interactive Pair/Group Tasks

2015· article· en· W1905125945 on OpenAlexfundvenueno aff
Laura Collins, Joanna White

Bibliographic record

VenueTESL Canada Journal · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersConcordia UniversityMinistère de l'Éducation, du Loisir et du Sport Québec
KeywordsHumanitiesPossessivePsychologyLinguisticsSociologyArtPhilosophy

Abstract

fetched live from OpenAlex

This article reports on a study examining the language practice opportunities that occurred during a range of paired and small group interactive tasks in an intensive English as a Second Language (ESL) class of francophone Grade 6 students. The analysis focussed on the opportunities the tasks provided for the use of two complex and challenging forms (the simple past and the possessive determiners his/her) by these learners. We examined both the quantity and the quality of the contexts for the two target forms within the tasks, and whether particular task types or task features were associated with more or richer practice for the forms.Cet article fait rapport d’une étude qui examine les occasions de pratiquer la langue qui se sont présentées pendant diverses tâches interactives accomplies en petits groupes dans un cours intensif d’anglais langue seconde avec des étudiants francophones en 6e année. L’analyse a porté sur les occasions présentées aux apprenant pendant les tâches pour employer deux formes complexes et difficiles (le passé simple et les déterminants possessifs « his » et « hers »). Nous avons examiné tant la quantité que la qualité des contextes pour les deux formes ciblées, ainsi que les différentes sortes de tâches pour déterminer si elles étaient liées à un emploi plus riche ou fréquent des formes.

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 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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.326
Teacher spread0.263 · 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 teacher head, not a consensus.

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

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

Citations8
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueTESL Canada JournalSame topicEFL/ESL Teaching and LearningFrench-language works237,207