The Effect of Direct and Indirect Written Corrective Feedback on Accuracy and Fluency of University Students' English Writing
Bibliographic record
Abstract
This research aimed to determine the effect of WCF (Written Corrective Feedback), direct and indirect, on overall accuracy, error types, and overall accuracy and fluency in pre-test, post-test, and delayed post-test in rewritten text. The research questions examined the potential links between the direct & indirect WFC, grammar & non-grammar errors, and standpoint of feedback for accuracy and fluency. A total of 100 English as a Foreign Language (EFL) students from the University of Pahlawan Tuanku Tambusai in Indonesia were involved in the research. The findings revealed significant variations among the three experimental groups in the proportions of both effectively and unsuccessfully rectified errors. as well as the proportions of uncorrected and deleted errors in both grammar and non-grammar categories. The cohort that received the Direct WCF had the most significant enhancement in accuracy. This study showed that offering direct WCF (written corrective feedback) can enhance participants accuracy gradually over an extended period of time (long term). Indirect written corrective feedback (WCF) can enhance participants' fluency in terms of overall word count. while direct WCF can improve participants' fluency in terms of t-units over a longer period of time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".