Living Transdisciplinary Curriculum: Teachers’ Experiences with the International Baccalaureate’s Primary Years Programme
Bibliographic record
Abstract
An integrated curriculum that is transdisciplinary in nature seems to be a good fit for 21st Century learning. There are, however, few examples of transdisciplinary curriculum at the K to 12 level. One exception is the International Baccalaureate’s Primary Years Programme (PYP) which features transdisciplinary curriculum for students from ages 3 to 12 around the world. This phenomenological study explored the lived experience of 24 PYP educators to deepen understanding of what such a curriculum looks like in practice. Three main themes were identified. The first, “It’s a framework” outlines participants’ understandings of transdisciplinary teaching and learning and the freedom a transdisciplinary framework can bring. The second theme, “Get on board”, examines participants’ thoughts around what is required to successfully implement a transdisciplinary curriculum. The final theme, “Their learning journey”, discusses participants’ beliefs around the success of a transdisciplinary curriculum. In general, participants appreciated the transdisciplinarity of the program. Concerns revolved around implementation issues. Suggestions on how to implement transdisciplinary teaching and learning in other contexts are provided.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.015 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".