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Record W4382501122 · doi:10.5539/elt.v16n6p1

A Comparative-Correlative Study of Test Rubrics Used as Benchmarks in Assessing IELTS and TOEFL Speaking Skills

2023· article· en· W4382501122 on OpenAlexvenueno aff
Esmaeil Bagheridoust, Yasameen Khalid Khairullah

Bibliographic record

VenueEnglish Language Teaching · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsTest of English as a Foreign LanguageRubricPsychologyTest (biology)Mathematics educationCorrelationLanguage assessmentMathematics

Abstract

fetched live from OpenAlex

The study focused on the comparative correlative study Test Rubrics Used as Benchmarks in Assessing International English Language Testing System (IELTS) and Test of English as a Foreign Language (TOEFL) Speaking Skills. To carry out this project, the researcher searched for IELTS and TOEFL candidates and recruited and finally selected 37 male and female candidates who took both standard tests for various reasons. The statistical results obtained (mainly Pearson's correlation coefficient of correlation moments) showed significant joint variability between IELTS Speaking scores derived from IELTS test bars and frequency band description factors, TOEFL Speaking scores derived from TOEFL test bars, and assessment scores. criteria. The results show that there is a high correlation index (0.862**) between the two tests scoring systems for speaking. The results also reflect a high correlation index (.903**) between the two tests scoring systems, assessing general English proficiency and speaking ability using both tests rubrics.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.172
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.345
Teacher spread0.328 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

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