Perceptions and Conceptions of Feedback: Differences between Levels of Study in a School of Law
Bibliographic record
Abstract
Feedback is a key component of student learning, student progression and the academic experience.1 It is assumed to be important as a result of the relationship between feedback, improved performance and achievement.2 The growing recognition of its importance in the past decade is reflected both in the learning and teaching literature, and in the current context; Evans recently undertook an analysis of 460 articles on feedback in higher education (HE) produced in the past 12 years,3 while simultaneously the UK Quality Assurance Agency for Higher Education (QAA) and the UK Professional Standards Framework (UKPSF) both emphasise the importance of feedback. The QAA states that "effective learning occurs when students are enabled to … make effective and responsible use of … feedback from formative and summative assessment',4 and the UKPSF, which sets out the professional standards *Cov. L.J. 2 and guidelines for HE providers and learners, includes assessment and the giving of feedback as one of the Framework's areas of activity.5
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".