Science Theatre at School: Providing a context to learn about socio‐scientific issues
Bibliographic record
Abstract
Science theatre is recognised as a method for teaching socio‐scientific issues (SSI), but is largely under‐researched. The essence of science theatre at school is to shape a contextualisation for science and technology and its relationships to individuals and society at large, with the aim to trigger the imagination, raise questions and stimulate debate among the audience to increase their understanding of the SSI at stake. To further the theoretical basis of science theatre at school, we investigated students’ experiences in coherence with the views from experts about the play’s possibilities and limitations, in the context of a performance about food science and technology. The play dramatised dilemmas that were related to science as a knowledge‐producing process, and through its consumer products. Our study indicated that the societal context for staging science and technology, through consumers’ dilemmas to eat healthy, raised interest among the students to a larger extent than the subject of science and technology per se. According to both students and experts, the level of scientific complexity and the use of caricature to portray scientists may have hampered the possibilities to reach the audience. An alternative to contextualisation on an individualised level is to make scientific controversy and its relationship to various social interests, the heart of the matter. The discussion after the play was considered crucial and appreciated, although the students were critical about the nature of the theses. Exploring the moral positions involved in dilemmas could provide an alternative perspective of understanding to the audience.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".