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Record W2083085943 · doi:10.5430/elr.v2n2p53

Participating in a Blog: Jordanian EFL Learners' Voices

2013· article· en· W2083085943 on OpenAlexvenueno aff
Nafiseh Zarei, Yasser Al-Shboul

Bibliographic record

VenueEnglish Linguistics Research · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionPsychologySocial mediaMathematics educationEnglish languagePedagogyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This study investigates the Jordanian EFL learners’ perceptions towards language learning through blog. It seeks to assess the usefulness of blogging in enhancing learners’ English language skills. The participants of the present study included 10 post graduate Jordanian EFL Learners who attended English Intensive Course. Data were collected through semi-structured interview questions regarding learners’ feedback on their perceptions to the integrated blog. The data obtained from the semi-structured interview was recorded, transcribed and described by the researchers and finally analyzed qualitatively. The findings of the study revealed that the learners perceived the blog as an interesting and helpful learning tool since interacting via blog helped them improve their English language skills as well as their peer feedback. Hence, the blog played an important role for the Jordanian EFL learners as it allowed them to exchange their experiences and thoughts with peers. The study concluded that integration of social networks, such as blogs into Jordanian EFL learners’ classes could enhance their English language learning processes.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.123
GPT teacher head0.374
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 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

Citations8
Published2013
Admission routes1
Has abstractyes

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