The Contribution of Teacher Feedback to Learners’ Work Revision: A Systematic Literature Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Feedback is an essential aspect of the teaching and learning process since it can objectively describe the learner's performance and guide him through revising their work to improve their academic performance. Studies regarding its application in education have recorded significant pedagogical benefits at the teaching and learning levels. The paper presents the results of a systematic literature review of 76 studies (2012-2022), which evaluated the contribution of teacher feedback to the revision of student work. The review was based on the PRISMA methodology, and studies were selected based on quality criteria. The results showed that most of the studies recorded significant benefits from the application of several types of feedback processes in the successful revision of trainees' work, such as the successful correction of errors, the improvement of the quality of their texts, the assimilation of improvement strategies and the receptivity of teachers and learners. Most of the research concerns English as a second and foreign language course and academic writing, recorded in higher education and collected self-report data, utilizing primarily quasi-experimental intervention.
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.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| 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 it