Fictional placemaking creating meaningful contexts for causal reasoning in secondary school biology education
Bibliographic record
Abstract
In secondary science education, students often do not feel engaged with the scientific concepts that are taught, which hinders conceptual learning. This lack of engagement can be overcome by fictional placemaking. Therefore, the purpose of our design-based research is to explore how the creation and use of fictional places lead to meaningful contexts providing opportunities for the learning of biology. Four design principles were formulated from theories on: (1) pedagogy of place; (2) communities of practice; (3) imaginative teaching; and (4) story-based learning. Based on these principles a lesson series was designed in which students were challenged to create societies living in domes on Mars as a fictional place. This lesson series was conducted in a ninth-grade class (28 students) at pre-university level. It was evaluated on the contribution of the design principles to create a meaningful context for the learning of biology. This research focuses on causal reasoning, which is a key competency in biology. The analysis of artefacts of group work showed evidence that students expressed different types of causal reasoning. Reflection on each of the design principles made clear how fictional placemaking provides opportunities for the development of students’ causal reasoning.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".