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Record W3159163703 · doi:10.5539/elt.v14n5p1

Perception and Interest of English Language Learners (ELL) toward Collaborative Teaching; Evaluation towards Group Activities

2021· article· en· W3159163703 on OpenAlexvenueno aff
Abdulbagi Babiker Ali Abulhassan, Fatima Ibrahim Eltayeb Hamid

Bibliographic record

VenueEnglish Language Teaching · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsEllPsychologyPerceptionNonprobability samplingMathematics educationDescriptive statisticsTest (biology)Teaching methodStatisticsMathematicsDemography

Abstract

fetched live from OpenAlex

This study focuses on evaluating the perceptions of Saudi ELLs enrolled in secondary classes, with an emphasis on group activities. A total of 424 ELLs were enrolled in this study on the basis of purposive sampling technique from eight public schools in Riyadh city, Saudi Arabia during the time period of January 2020 to May 2020. A close-ended questionnaire comprising 23 items was distributed online to collect data regarding perceptions of participants towards collaborative teaching and group activities. Descriptive statistics, independent t-test and One-Way ANOVA were used as statistical tools to analyze the data through SPSS version 25.0. Collaborative teaching techniques and group activities were preferred by ELLs with respect to gender differences and grade-level differences, respectively. It was concluded that students studying in different classes preferred group activities in comparison with collaborative teaching techniques.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.337
Teacher spread0.314 · 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 designObservational
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

Citations8
Published2021
Admission routes1
Has abstractyes

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