Fostering Creativity Through Education: Lessons From the <scp>PISA</scp> 2022 Survey
Bibliographic record
Abstract
ABSTRACT For the first time, the Programme on International Student Assessment (PISA) has evaluated the creative thinking skills of over 140,000 15‐year‐old students in more than 60 countries, assessing their ability to engage productively in generating, evaluating, and improving ideas. This commentary positions the recent PISA 2022 international survey results in a larger perspective of fostering creativity through education. Specifically, this commentary explores (1) which creative abilities were assessed by the PISA survey. With a clearer understanding of what was assessed, we discuss (2) the main limitation of the PISA global creative thinking score, which is to obscure the profile of strengths and weaknesses of individuals, potentially leading to inaccurate conclusions about individuals' overall abilities. Lastly, (3) we discuss the potential impact of the PISA survey and highlight aspects of creativity, such as the pursuit of personally meaningful goals and self‐expression, that may be more difficult to capture in PISA‐type measurements but that may be fundamental for the cultivation of creativity in school.
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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 | 0.049 | 0.135 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".