Transformation and Education: The Voice of the Learner in Peters' Concept of Teaching
Bibliographic record
Abstract
On several occasions in his work, R. S. Peters identifies a difficulty inherent in teaching that underscores the complexity of this relationship: the teacher has the task of passing on knowledge while at the same time allowing knowledge that is passed on to be criticised and revised by the learner. This inquiry asks: first, how does Peters envisage these two tasks coming together in teaching, and, second, does he go far enough in developing what it means for the teacher to recognise the difference and otherness of the learner? At the heart of the matter in answering these questions is how to conceive of the connection between learning and the transformation of the individual. Before turning to Peters, this inquiry begins by discussing connections between transformation and learning in classical and contemporary philosophical discourse. In this context, notions of discontinuity and interruption are shown to be central to understanding transformational learning processes. Peters' thought is then located within this discourse and taken up in three central ways: (1) by analysing his notion of teaching (2) by examining the ideas of learning and transformation embedded in his concept of teaching, and (3) by inquiring into how these issues relate to his idea of philosophy of education as a central part of teacher education.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.045 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| 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".