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Record W4388960506 · doi:10.5430/wjel.v13n9p31

Multimedia Educational Environment as a Tool for Developing Communicative Competences in the Field of Trilingual Higher Education

2023· article· en· W4388960506 on OpenAlexvenueno aff
Gainigul Ismailova, K. E. Khassenova, Zarina Rakhmatullina, Gulnar Zhumadilova, Shugyla Kenzhina

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicForeign Language Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCommunicative competenceComputer scienceCurriculumCompetence (human resources)Knowledge managementSociologyPedagogyPsychology

Abstract

fetched live from OpenAlex

When examining the conditions of modernity and the specifics of the formation and regulation of social relations, including educational ones, one should establish that they are completely focused on global informatisation and development. The relevance of studying the issue of communicative competence formation in a multimedia educational environment is quite high today, as it meets the challenges of modern society. The purpose of this study is to analyse the process of development and consolidation of communicative competence in the context of trilingual higher education, by using the basics and advantages of multimedia educational environment. The research adopted a functional and systematic methodological approach to examine the role of multimedia educational environments in trilingual higher education communicative competence, progressing through three detailed stages and drawing from a comprehensive literature review sourced from databases like Google Scholar and Scopus. Key methodologies included analysis, synthesis, and comparison, with findings divided into theoretical and practical insights, culminating in conclusions and future research directions. Accordingly, the main general theoretical issues and concepts are revealed in the theoretical part and their specific features are established. The practical part concretises the above-mentioned aspects, according to the purpose of the study. The practical value of this study lies in the fact that it can be used both in the context of methodological material, for curriculum development, and as a primary source for scientific work.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.004
Science and technology studies0.0020.003
Scholarly communication0.0060.007
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.032
GPT teacher head0.397
Teacher spread0.365 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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Same venueWorld Journal of English LanguageSame topicForeign Language Teaching MethodsFrench-language works237,207