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Record W2982495138 · doi:10.5430/ijhe.v8n7p39

To the Question of the Interference and Positive Transfer When Teaching Russian to Hispanic Students

2019· article· en· W2982495138 on OpenAlexvenueno aff
Dinara R. Valeeva, Alina Ershova

Bibliographic record

VenueInternational Journal of Higher Education · 2019
Typearticle
Languageen
FieldMedicine
TopicEmergency Medicine Education and Research
Canadian institutionsnot available
FundersKazan Federal University
KeywordsLinguisticsVariety (cybernetics)Relevance (law)Process (computing)Computer scienceContrast (vision)First languageRussian languagePsychologyMathematics educationArtificial intelligencePolitical science

Abstract

fetched live from OpenAlex

The real research is devoted to problems of an interlingual interference in the process of studying of Russian by students of the Hispanic countries. The relevance of the article is caused by the fact that at all variety of the scientific works devoted to the contrast description of various languages and the analysis of their interference, it is a little work comparing the Russian and Spanish languages. The research was conducted for the purpose of comparison of the separate language phenomena of the Russian and Spanish languages and the description of those lexical and grammatical features which knowledge will allow teachers to warn and correct native speaker errors in the Russian speech, therefore, to optimize training process. According to the authors, it is advisable to use the national focused tests and tasks on classes in RKI and also governed with explanations and examples in the native language of students that will increase their intellectual activity.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.415
Teacher spread0.398 · 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 designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

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