Intersections between Tutorial Engagement, Directive Feedback, and Critical Reflection
Bibliographic record
Abstract
A handful of research studies have investigated the effect of writing centre tutorials on subsequent revisions. This classroom-based study adds to that research by reporting results from a collaborative study between a composition professor and a writing centre tutor. The aim of the study was to examine the influence of writing centre tutorials on immediate student revisions as well as final drafts. The analysis was extensively framed by the Vygotskyan sociocultural model of language and cognitive development with an emphasis on tutor-student engagement as reciprocal interaction which include directive feedback and consequential revision. This study employed a qualitative design with students in a sophomore-level core composition course. Participants attended a writing centre session concerning their major writing assignment. Data triangulation included analysis of assignment drafts, observation notes, and tutorial transcripts. Findings revealed that students attended to feedback that was directive and straightforward. Additionally, students did not attend to citation feedback unless it was direct and explicit. Furthermore, students sometimes overgeneralized and misapplied the feedback. The findings highlight the impact of individual learner factors as well as the results of directive feedback on revisions.
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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 | 0.015 | 0.135 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".