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Record W4285010585 · doi:10.5539/elt.v15n8p1

English as an International Language Project-Based Learning: A Focus on Young Chinese Learners’ Beliefs

2022· article· en· W4285010585 on OpenAlexvenueno aff
Xiaoli Zheng

Bibliographic record

VenueEnglish Language Teaching · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyLanguage acquisitionFocus groupPedagogyConstruct (python library)Mathematics educationProject-based learningLanguage assessmentSociologyComputer science

Abstract

fetched live from OpenAlex

This study explored young Chinese learners' beliefs about English as an international language through project-based language learning in a Chinese rural school. Three English teachers and 102 Grade 6 Chinese EFL learners participated in two separate phases. Phase 1 explored how teachers implemented the project-based language learning via classroom observation and semi-structured interviews. The findings from this phase were used to construct the six aspects of the EIL project-based language learning questionnaire in Phase 2. The questionnaire was developed to explore learners’ beliefs about EIL and project-based language learning in a Chinese rural school. The questionnaire revealed that the learners strongly believed in learning English as an international language through project-based language learning. Five aspects received similar positive responses, namely, collaboration, authenticity, intellectual challenge and accomplishment, and project management and reflection. However, only the aspect of public product received a more negative response.

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)0.002
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.274
Teacher spread0.261 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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