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Record W3216900385 · doi:10.23977/aetp.2021.59001

The Influence of Teachers' Corrective Feedback on the Accuracy of English Writing

2021· article· en· W3216900385 on OpenAlexvenueno aff
Juan Liu

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2021
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsCorrective feedbackMathematics educationSample (material)Class (philosophy)Computer scienceControl (management)PsychologyFeedback controlEngineeringArtificial intelligenceControl engineering

Abstract

fetched live from OpenAlex

Feedback plays a vital role in writing. Corrective feedback can be defined as the feedback input of teachers to students in writing. In order to explore influence cognitive factors on students' writing accuracy under teachers' corrective feedback, this study uses sample survey, data analysis and drawing method to analyze corrective feedback and streamline the algorithm. The subjects are 66 students from the 6th class of the first high school in a certain county, and the follow-up study lasted for two months. In addition, for comparative analysis, 66 students were divided into two groups, experimental group and the control group. The results showed that most students believe that teachers' corrective feedback can improve writing accuracy, which basically realized the purpose of this study, and pave the way for further research.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.355
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2021
Admission routes1
Has abstractyes

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