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Record W2234278633 · doi:10.3138/cmlr.2494

L2 Academic Discourse Socialization through Oral Presentations: An Undergraduate Student’s Learning Trajectory in Study Abroad

2015· article· en· W2234278633 on OpenAlexfundvenueaboutno aff
Masaki Kobayashi

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersForeign Affairs and International Trade Canada
KeywordsSocializationAppropriationSophisticationContext (archaeology)PsychologyPresentation (obstetrics)Citizen journalismPedagogyQualitative researchMathematics educationSociologySocial psychologyPolitical scienceSocial scienceLinguistics

Abstract

fetched live from OpenAlex

The present study provides an in-depth, longitudinal account of an undergraduate student’s L2 discourse socialization in an academic exchange program in Canada. By invoking Rogoff’s (1995) notion of participatory appropriation, this qualitative case study examined an L2 student’s task-related strategies and performance as they evolved over time in a study-abroad context. Thus, it revealed the cumulative effects of her participation in the development of knowledge and skills required to accomplish her academic presentation tasks at an appropriate level of sophistication. Data, collected over an entire academic year, included audio-recorded observations, in-depth interviews, and relevant written products. The findings indicate that the focal student’s academic discourse socialization was a dynamic, intertextual process of acting continuously on the challenges and opportunities that her previous experiences afforded her. Her participation was both guided by different co-participants and contingent upon the series of agentive choices that she made about her tasks.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.354
Teacher spread0.289 · 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.

Study designQualitative
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

Citations36
Published2015
Admission routes3
Has abstractyes

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