Practices of Intermediate Teachers in the Development of Life-Long Scientific Literacy
Bibliographic record
Abstract
Science is important in the everyday lives of Canadians, but fewer than half of Canadians have the basic level of scientific literacy required to interpret the scientific matters they are exposed to daily. The intermediate grades (7 to 10) are often the last stage at which science education is mandatory and thus the last guaranteed opportunity for teachers to foster enduring scientific literacy in their students. In this study I asked: how are a small sample of Canadian intermediate teachers developing life-long scientific literacy among their students? Using semi-structured interviews I spoke with five science teachers; three from Alberta and two from Ontario to provide a greater cross-country perspective. After analysing the interview transcripts for codes and parsing out themes I found the broad and varying definitions of scientific literacy make it difficult to determine when and how scientific literacy is being taught. While this small selection of teachers identified a variety of approaches for teaching scientific literacy they struggled with how to assess scientific literacy. Moving forward I suggest that a concerted effort be made to clarify the meaning of scientific literacy so educators can develop more specific goals when teaching scientific literacy and assessing for its development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".