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Record W885494521 · doi:10.34577/0000000212

留学環境における日本人の英語学習者 -成果,言語接触,習熟進度-

2015· article· ja· W885494521 on OpenAlexaboutno aff
千裕 田島

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2015
Typearticle
Languageja
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This study examined the outcomes of study abroad, and further investigated why some learners make more language contact and/or proficiency gain during their study abroad than others. The research participants were 25 second-year Japanese university students in a private university in Tokyo, learning English in a 15-week study abroad program in Canada. This study generated three research questions. Research question one sought to find both linguistic and non-linguistic outcomes of a study abroad. Research question two had two parts: investigating variables associated with postreturn English proficiency test results, and exploring variables associated with while-abroad language contact. Finally, in research question three, qualitative data were used to find interpretations and explanations into the variables identified by quantitative data, especially focusing on the amount of while-abroad language contact. The variables used in the study include affective factors e.g., motivation, willingness to communicate, language anxiety, self-perceived English skills, and homesickness. In addition, learner profiles, e.g., previous study abroad experience, the number of English courses taken prior to study abroad, the amount of language contact prior to study abroad, and English proficiency, were considered. This research employed mixed methods, and the following sections summarize a number of findings from both the quantitative and qualitative analysis.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.027
GPT teacher head0.247
Teacher spread0.220 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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