Innovation, Critical Pedagogy, and Appreciative Feedback
Bibliographic record
Abstract
The practice of giving and receiving feedback is an essential element of a wholesome educational experience. As learners are engaged in the vulnerable role of waiting for and receiving feedback, there is a significant and potentially problematic power relationship at play in the feedback dyad. This chapter proposes that the practice of giving feedback offers a great scope for innovation, and that critical pedagogy offers a theoretical lens through which such innovation may be understood. This chapter explores and defines innovation through the lens of critical pedagogy, which calls for the intentional questioning of existing power structures in education. A scan of the literature presents the importance of feedback in the learning process, and supports a move towards a dialogic, student-centered process. The writers share two case studies in appreciative feedback and provide a proposed model for innovation in the delivery of feedback. When viewed as a compassionate, supportive act, feedback is well positioned to benefit learners as viewed through the lens of critical pedagogy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".