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Record W993285327

Information and communication technologies in teaching and learning english as foreighn language

2014· article· en· W993285327 on OpenAlexaboutno aff
Г. О. Козлакова, Оksana Strelchenko

Bibliographic record

VenueEdukacja-Technika-Informatyka · 2014
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsFirst languageRelevance (law)CurriculumForeign languageLanguage industrySubject (documents)Language educationMedium of instructionFunction (biology)Comprehension approachPedagogyLinguisticsComputer scienceSociologyPolitical scienceWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

English is not only the mother tongue in Britain, Canada, the United States of America, New Zealandand several other countries, but it is also used as a second and a foreign language (EFL) in many other developing countries. That’s why English is generally acknowledged as a global language and it is also seen as a veritable tool for learning, business and interactional purposes, among other function. The role and status of English in Ukraine is higher than ever as evidenced by its position as a key subject of medium of instruction, curriculum. In view of its relevance, it has become imperative for English Language teachers and learners to realize the fundamental role of information and communication technology as a catalyst in the advancement of the frontiers of knowledge in language acquisition which is a prerequisite to the viability of the global economic development. At present, IC technologies have proved successful in replacing the traditional teaching and the use of authentic materials in the form of films, radio, TV has been there for a long time.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.788
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.002
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 head0.011
GPT teacher head0.321
Teacher spread0.310 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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