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Record W4391948596 · doi:10.5539/elt.v17n3p19

Adopting E-Learning to Facilitate English Teaching and Learning in Kuwait

2024· article· en· W4391948596 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
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

VenueEnglish Language Teaching · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMathematics educationE learningTeaching methodLinguisticsPedagogyEducational technology

Abstract

fetched live from OpenAlex

This research investigates the implications of adopting e-learning on the teaching and speaking proficiency of English among teachers in Kuwaiti public schools, particularly in the wake of the COVID-19 pandemic. Although many private schools in Kuwait had already transitioned to digital learning platforms, public schools lagged behind. This study used interviews and questionnaires to glean insights from teachers, with a particular focus on their experiences and perceptions. Initial findings suggest that while the shift to online learning introduced challenges, it also offered significant opportunities to improve teaching methodologies and English-speaking capabilities. Despite initial anxieties regarding the transition, e-learning proved to be a flexible and convenient medium, prompting a revaluation of its role in Kuwaiti public high school education. The research underscores the significance of understanding the strengths and weaknesses of e-learning in the English curriculum, especially as the world grapples with the ongoing challenges of the COVID-19 pandemic.

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)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.003
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 head0.011
GPT teacher head0.252
Teacher spread0.242 · 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