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Record W3081132945

Post-French Immersion Student Perceptions of Parallel Concordancing: A Mixed Methods Study

2019· dissertation· en· W3081132945 on OpenAlexaboutno aff
Noah Jason Ward Bradley

Bibliographic record

VenueYork University Digital Library (York University) · 2019
Typedissertation
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsFrench immersionPerceptionCorpus linguisticsMathematics educationComputer scienceQualitative propertyMultimethodologyThe InternetQualitative researchPsychologyImmersion (mathematics)MultimediaWorld Wide WebNatural language processingSociology
DOInot available

Abstract

fetched live from OpenAlex

I examine the perceptions of students who have graduated from the Ontario French immersion program toward an online corpus at a university in Ontario. No corpus research has yet been conducted on post-French immersion students studying in a French Studies department at university. This study further researches the effectiveness of bilingual corpus use for writing. It presents students with a tool for overcoming language learning plateaus and provides teachers with a model for teaching corpus usage. Through a sequential mixed methods approach, I use a quantitative questionnaire and then qualitative interviews to answer the research questions. Students generally perceive corpus use positively, but not as an answer to every language learning problem, instead viewing corpus use as one of many available tools. Furthermore, students prefer using several websites to verify their word usage. In our information-driven world, students use every internet resource at their disposal to learn a language efficiently.

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)0.000
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 score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.001

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 head0.012
GPT teacher head0.282
Teacher spread0.269 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueYork University Digital Library (York University)Same topicSecond Language Acquisition and LearningFrench-language works237,207