Pedagogy of resonance and physical education: a critical discussion of Rosa’s proposals
Bibliographic record
Abstract
The publication of Hartmut Rosa’s book Pedagogy of resonance caused a stir in the educational community in general and in Physical Education (PE) in particular, arousing both a wave of interest and a degree of circumspection. This contribution offers a critical discussion of what is presented as a ‘new educational model’. After tracing the stages in Rosa’s thinking that led him, from his early philosophical and sociological research on acceleration, alienation and resonance, to formalize a pedagogy of resonance, we summarize its aims and fundamental principles. We then show how Rosa’s educational proposals have been appropriated by other pedagogues, particularly in relation to the teaching of PE. We then compare the pedagogy of resonance with three contemporary scientific approaches and pedagogical models that appear to be convergent, compatible and distinct (flow, enaction, mobilisation). Moreover, we discuss Rosa’s somewhat schematic opposition between resonance, on the one hand, and the acquisition of techniques and competency, on the other. Finally, we show to what extent the pedagogy of resonance is likely to enrich thinking in relation to three major contemporary issues and challenges for School and PE: education for citizenship and living together; education for health and well-being; education for sustainable development. We conclude this critical essay by considering potential directions for research, and its empirical difficulties, in relation to pedagogy of resonance.
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.010 | 0.051 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 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".