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Record W3208830123 · doi:10.5430/wjel.v12n1p27

The Effects of Trained Peer Feedback for High School Students

2021· article· en· W3208830123 on OpenAlexvenueno aff
Vũ Phi Hổ Phạm, Truong Chinh Le, The Hung Phan, Ngoc Hoang Vy Nguyen

Bibliographic record

VenueWorld Journal of English Language · 2021
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsSpellingPeer feedbackPunctuationGrammarVocabularyTest (biology)Mathematics educationPsychologyWord (group theory)Quality (philosophy)CapitalizationComputer scienceControl (management)LinguisticsArtificial intelligence

Abstract

fetched live from OpenAlex

Peer feedback is proved to be effective in helping enhance students' writing quality, but few studies were employed to train high school students to be better peer reviewers. The current study involved 64 grade-11 students in a province in Vietnam to see whether trained peer feedback could be effective for high school students. The experimental group was trained to conduct peer feedback, while the control group did it naturally. The semester lasted for 16 weeks. Data collection was from the pre-test, post-tests, and semi-structured interviews. The results revealed that the most common errors that the students committed were grammar (verbs, articles, repositions), followed by vocabulary (word order, word choice, word form), and mechanics (capitalization, spelling, punctuation). In addition, the students in the experimental group who received peer feedback training could significantly reduce the written errors in the post-test. The students obtained positive attitudes towards peer feedback activities in the writing classroom.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.013
GPT teacher head0.357
Teacher spread0.344 · 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 designNot applicable
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

Citations4
Published2021
Admission routes1
Has abstractyes

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