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Record W2527270231 · doi:10.5539/ies.v9n10p174

Perceptions of an Anticipated Bilingual Education Program in Turkey

2016· article· en· W2527270231 on OpenAlexvenueno aff
Burhan Özfidan, Lynn M. Burlbaw, Li‐Jen Kuo

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsBilingual educationThematic analysisNeuroscience of multilingualismEthnic groupDescriptive statisticsPsychologyMultimethodologyQualitative researchNative-language instructionQualitative propertyMathematics educationPerceptionMedical educationAffect (linguistics)PedagogySociologyTeaching methodSocial scienceComputer science

Abstract

fetched live from OpenAlex

Bilingual education is globally an important aspect within the educational community in recent years. The purpose of the study is to explore perceptions towards a bilingual education program and investigate factors that may affect the development of a bilingual education program in Turkey. This study also identifies the benefits of bilingualism in Turkey. The study employed an explanatory sequential mixed method design, which consisted of a quantitative phase followed by a qualitative phase. Data were collected from 40 participants who were graduate students, faculty members, and K-12 teachers. Descriptive analysis was used in the first phase of data analysis; thematic analysis was used in the second phase. A bilingual education program in Turkey might solve the conflict between different ethnic groups. Findings from both phases of data analysis indicated that people in the research group have affirmative perspectives towards a bilingual education program in Turkey.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
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 head0.154
GPT teacher head0.601
Teacher spread0.448 · 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 designOther design
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

Citations9
Published2016
Admission routes1
Has abstractyes

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