The Use of Online Corrective Feedback in Academic Writing by L1 Malay Learners
Bibliographic record
Abstract
Conventional corrective feedback has been widely practiced but has been said to be tedious, stressful and time consuming. As such, the focus of this study is to investigate the use of an alternative method to giving corrective feedback namely, an online corrective feedback through e-mail. In order to examine if this innovative form of corrective feedback can be applied to the teaching and learning of academic writing, an experimental design was used with a control group and an experimental group of L1 Malay learners who were pursuing an academic writing course at the tertiary level. Interviews were also conducted on selected individuals to determine whether the use of online corrective feedback was practical in assisting learners improve their writing from the first draft to the final product. The statistical analysis applied to this research indicated that online corrective feedback may be an effective way to improve writing skills of learners and save time. Thus, the results showed that online corrective feedback should be potentially useful when integrated into the teaching and learning of academic writing.
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 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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".