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Record W3094750526 · doi:10.5539/ijel.v10n6p381

Promoted Peer Review in EFL Writing: Development in Students’ Perceptions and Feedback

2020· article· en· W3094750526 on OpenAlexvenueno aff
Rashed Al-Tamimi

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsnot available
FundersKing Saud University
KeywordsPsychologyMedical educationSession (web analytics)PerceptionPeer feedbackPromotion (chess)Mathematics educationMedicineComputer science

Abstract

fetched live from OpenAlex

While many studies have examined the impact of peer review on EFL students’ perceptions of peer review and acceptance and incorporation of feedback in their writing with the help of training or guidance and guide (check list), using a combination of these techniques plus multiplicity of review sessions, as a promotion, has been underexplored. This study aims to investigate the usefulness of training, guidance, and multiplicity of peer review sessions in changing students’ negative perceptions of peer review and increasing their acceptance and incorporation of feedback in EFL writing. Two training workshops and checklists were used to help students do the review, which was accomplished in five multiple sessions. Thirty-four students voluntarily participated in this study, which employed a five-item pre-/post methodology—the online survey and students’ written drafts as data collection instruments. To analyze the data, independent samples t-tests were used for the five-item survey, percentage of each peer session’s comments (i.e., comments made/comments incorporated) was calculated to assess peers’ acceptance of their partners’ feedback, and a repeated-measures ANOVA was conducted to determine whether participants incorporated more feedback over time. The results showed that, first, the participants revealed positive perceptions of the effectiveness of peer review. Second, the students highly accepted their peers’ feedback. Finally, the students incorporated a significantly higher quantity of reviewers’ feedback into second drafts at the end of every session, starting from the second session. The pedagogical implications of these findings are discussed.

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)0.054
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.054
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.392
Teacher spread0.341 · 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.

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

Citations2
Published2020
Admission routes1
Has abstractyes

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