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Record W2922319208 · doi:10.5539/elt.v12n4p149

Primary Teachers’ Perceptions of CLIL Implementation in Spain

2019· article· en· W2922319208 on OpenAlexvenueno aff
José María Campillo Ferrer, Raquel Criado Sánchez, Pedro Moruno Miralles

Bibliographic record

VenueEnglish Language Teaching · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsContent and language integrated learningPsychologyPerceptionPedagogyMathematics educationForeign language

Abstract

fetched live from OpenAlex

CLIL (Content and Language Integrated Learning) has been one of the major innovations that has been implemented in Spain in the last decades and many questions have arisen in relation to its effectiveness. The aim of this article is to report primary teachers’ perceptions of the most relevant aspects of CLIL teaching of Science and Social Science in Primary Education in the Region of Murcia. Their perceptions of this integrated approach are crucial to meet their needs, coordinate their efforts and develop good practice. Results from this research emphasize an extensive application of CLIL methodological guidelines and the use of a wide range of tools when evaluating learners’ competences. Additionally, they have expressed their satisfaction with language assistants when motivating pupils and fostering their oral skills and intercultural awareness. However, CLIL teachers believe Public Administration should provide more resources, further training and enhanced coordination to improve the quality of education under this paradigm.

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)0.005
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.256
Teacher spread0.248 · 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 designQualitative
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

Citations38
Published2019
Admission routes1
Has abstractyes

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