The (mis)alignment between young people’s collective physical activity experience and physical education curriculum development in Ireland
Bibliographic record
Abstract
Major curriculum changes have recently occurred in Ireland, including redeveloping the primary curriculum and the enactment of the Junior Cycle Framework (DES, 2015). Positive and negative experiences affect the attitudes which contribute to determining the quality of curricular experiences. Framed in the work of Fullan, M. (1991. The New Meaning of Educational Change. Toronto: Teachers College Press) and Dewey, J. (1997. Experience and Education. New York, NY: Touchstone), this study aims to understand how young people’s experiences of collective physical activity can inform physical education curriculum development and enactment. Focus group interviews were conducted in three primary and three post-primary schools. The young people’s experiences reflected the features of meaningful physical education: fun opportunities, preferably outside; to socially interact with friends; provision of activities that are both competitive and non-competitive; activities focused on team sport and alternative forms of movement such as yoga; differentiated activities and teams and choice, beyond choosing between team sports only. We argue that the young person’s voice has the potential to inform policy and practice, as well as enforce and advocate for policy and practice that positions young people at the centre of the learning experience.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".