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Record W2972110523 · doi:10.5539/elt.v12n10p14

The Impact of International Proficiency Tests on Language Teaching and Motivation: A Case Study

2019· article· en· W2972110523 on OpenAlexvenueno aff
Abdelmoneim Hassan Adam Khamis

Bibliographic record

VenueEnglish Language Teaching · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMathematics educationYardstickTest (biology)PedagogyPerception

Abstract

fetched live from OpenAlex

This case study of Al-Aqsa School attempts to show that Cambridge Young Learners English Tests (YLE) may hurt learners’ motivation and teaching process. The paper aims to highlight the adoption of Cambridge YLE proficiency tests and explore learners and teachers’ perception of those tests. Also, providing alternative yardstick measures learners’ performance. Combination of a questionnaire, interviews and observation of Cambridge YLE, Movers and Flyers tests were used to collect the data. The evidence presented in this paper suggested that there was a necessity for English language teachers to motivate and prepare pupils of YLE tests at the primary stage. Otherwise, the School should reconsider administering the YLE tests at this fundamental level. The paper recommended progressively institutionalised scholastic accomplishment tests, alongside placement tests at the beginning of the school academic year. The findings should make an essential contribution to the field of applied linguistics and help decision-maker at Al-Aqsa School to take appropriate decisions.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.301
Teacher spread0.286 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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