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Record W2895444437 · doi:10.1017/s0267190518000077

Learning Chinese through Contextualized Language Practices in Study Abroad Residence Halls: Two Case Studies

2018· article· en· W2895444437 on OpenAlexaff
Celeste Kinginger, Qian Wu

Bibliographic record

VenueAnnual Review of Applied Linguistics · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsResidenceSocializationPsychologyMandarin ChineseSecond languageStudy abroadPedagogyNarrativeQuality (philosophy)LinguisticsSociologySocial psychologyEpistemology

Abstract

fetched live from OpenAlex

ABSTRACT A key question about study abroad concerns the relative benefits and qualities of various living arrangements as sites for learning language and culture. A widely shared assumption seems to be that students choosing homestays enjoy more opportunities for engagement in high-quality interactive settings than do those who opt for residence halls. However, research on outcomes has to date produced only weak evidence for a homestay advantage, suggesting a need to understand the nature of language socialization practices in various living situations. While a number of studies have examined the nature of homestay interaction, only a few have focused on language use in residence halls or other settings where students may interact with peers who are expert second language users. Informed by a Vygotskian approach to the study of development, this article examines the specific qualities of contextualized language practices through two case studies of U.S.-based learners of Mandarin in Shanghai and their Chinese roommates. In the first case, a friendly relationship emerged from routine participation in emotionally charged conversational narrative. In the second, both participants’ interest in verbal play and humor led to enjoyment as well as profoundly intercultural dialogue. In each case, there is evidence to show that all parties enjoyed opportunities to learn. These findings suggest that residence halls can be very significant contexts for learning in study abroad settings.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.006
Scholarly communication0.0030.002
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.063
GPT teacher head0.443
Teacher spread0.380 · 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 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

Citations39
Published2018
Admission routes1
Has abstractyes

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