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Record W4289537496 · doi:10.24919/2308-4863/52-3-33

CLIL METHODOLOGY IN TEACHING ACADEMIC WRITING AND INTEGRITY

2022· article· en· W4289537496 on OpenAlex
Viktoriia TOKARCHUK, Yuliia SHUBA

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueHumanities science current issues · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsAcademic integrityMathematics educationComputer sciencePedagogyPsychologySociologyEngineering ethicsEngineering

Abstract

fetched live from OpenAlex

The article provides an overview of CLIL methodology as a contemporary approach to teaching non-language subjects in an additional (foreign) language. Having its roots in the French immersion programs and bilingual education in Canada and the USA in the 1950s, CLIL has been gaining popularity in Europe in the last decade. Ukraine has also become one of the countries where CLIL methodology is being actively implemented at different educational levels. CLIL differs from ESP in that the latter aims at forming those foreign language skills which are required from future professionals in the professional environment while CLIL has a dual focus on the content and language. The theoretical framework of CLIL is constituted by 4Cs: content, communication, cognition, and culture. The interrelation of these four principles is supposed to ensure the balanced acquisition of a subject and a foreign language. Researchers differentiate between two models of CLIL -'soft' and 'hard'. 'Soft' CLIL is language-focused while 'hard' CLIL is subject/contentfocused. Between the two ends of the 'soft-hard' continuum there can exist multiple versions of CLIL when teachers select a necessary balance of content and language with regard to the students capabilities and needs. CLIL implies the use of only authentic materials (e.g., textbooks and videos which are intended for native speakers and can represent real life situations). Another important idea behind CLIL is scaffolding -supporting students at all the stages of studying. Scaffolding aims to compensate for the lack of verbal explanation which sometimes can be too complicated and be at variance with the students language competence. Scaffolding can be verbal (vocabulary of the subject) and non-verbal (colours, gestures, pictures, movements, sounds, etc.) with one complementing another. In this paper we provide examples of applying CLIL methodology while teaching academic writing and integrity.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient 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 score0.538
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.313
GPT teacher head0.417
Teacher spread0.104 · 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