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Record W4283118003 · doi:10.5539/jel.v11n4p144

The Use of Blogs on EFL Students’ Writing and Engagement in a Saudi Private School

2022· article· en· W4283118003 on OpenAlexvenueno aff
Dalal A. Bahanshal, Miriam Alkubaidi, Norah A. Alied

Bibliographic record

VenueJournal of Education and Learning · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyContext (archaeology)Collaborative writingClass (philosophy)InterviewPedagogyPerceptionMathematics educationElectronic publishingIntervention (counseling)SociologyThe InternetComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The blog is one of the recent technologies in use for teaching, learning, and practicing writing (Aljumah, 2012). Blogs are an educational tool for continuous learning outside classrooms (Vurdien, 2013). The current study aims to add to the research on blogs in EFL writing by observing the writing development of EFL learners in a Saudi context. The study also investigates learners’ perceptions of utilizing blogs as tools to increase classroom engagement. The data are collected from 36 female high school students by analysing the students’ writing samples before and after the intervention, conducting a questionnaire at the end of the intervention, and interviewing select participants. Although the findings did not show any significant differences between the two writing samples, the responses from the surveys indicated positive perceptions of blogs in writing and of blogs as a tool for increasing engagement. The active interaction in peer feedback and class discussion revealed that the blog is a useful tool for learning writing.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.070
GPT teacher head0.320
Teacher spread0.251 · 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
Published2022
Admission routes1
Has abstractyes

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