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Record W3048603188 · doi:10.5430/ijhe.v9n7p230

Innovative Methods in Language Disciplines During Profile Training Implementation

2020· article· en· W3048603188 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Professional Development
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianComputer scienceMathematics educationForeign languageEuropean unionLanguage industryLanguage educationDisciplineReflection (computer programming)Process (computing)Comprehension approachSociologyPsychologyLinguisticsSocial science

Abstract

fetched live from OpenAlex

The advanced pedagogical experience testifies to the presence of a number of methods in the practice of teaching language disciplines used by teachers during profile training at school or other educational institutions. With the development of modern information technologies, the role of traditional methods of studying language disciplines in the educational process is changing to the advantage of more innovative (interactive) methods of studying language disciplines. Therefore, the purpose of the article is to investigate the peculiarities of the application of innovative methods in language disciplines during profile training implementation. To achieve the purpose specified, an academic paper uses a number of general scientific (method of theoretical analysis, method of observation, method of description and method of synthesis) and empirical (experimental method, modeling method and calculation method) research methods. The practical reflection of the state and dynamics of mastering language disciplines during profile training is demonstrated through: the efficiency level of the applied innovative methods of studying language disciplines; the dynamics of the average number of students, involved in studying foreign language per student at the level of higher secondary education; rating of the countries of European Union and Ukraine on English proficiency according to the Global rating of countries and regions; provisions of New Ukrainian School Concept. It has been established that in the countries of European Union the practice of studying language disciplines is based on the translation method, the method of meaningful and language integrated learning, the methods of using digital technologies and the method of using creative objects. The study has revealed that such countries of European Union, as Luxembourg, Romania and Finland have significantly high levels of foreign language proficiency; however, such levels of language command are significantly low in Greece, Denmark, Spain, Germany and Portugal. It has been established that Ukraine is classified as a country with a low level of English language command (proficiency) in the Global Ranking of Countries and Regions (according to data of 2019, 2017 and 2016) and a moderate level of English language proficiency (according to data of 2018 and 2015). The following types of innovative methods, currently used by teachers in language disciplines during profile training, have been summarized, namely: the use of information and computer technology in the process of language learning; the use of developmental methods in the form of dialogue, discussion, seminar or brainstorming; construction of the educational process in the form of a game, project, team game; introduction of creative and interactive tasks into the educational process.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.999

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)0.0020.000

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 head0.088
GPT teacher head0.560
Teacher spread0.472 · 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