Rethinking K-6 Scientific literacy: A Case Study of Using Science Books as Tool to Cultivate a Fundamental Sense of Scientific Literacy
Bibliographic record
Abstract
As the discourse of scientific literacy has broadly summed up the goals of science education in the current decade, this study attempts to question how we contextualize appropriate interpretations and feasible approaches to scientific literacy in K-6 science education. With respect to the complex praxis of scientific knowledge and practice, this study emphasizes the participatory framework of scientific literacy which interweaves children's everyday experiences and science learning. This study also concerns children's abilities to understand and enact scientific enterprises (i.e., children's fundamental sense of scientific literacy). As a way of developing K-6 scientific literacy, this study investigates how using science books can broaden the scope of children's understandings of science in life connections and promote a fundamental sense of scientific literacy through talking, reading, and writing skills in Grade two science classrooms in Canada. Second graders were engaged in learning sound for five weeks. During science lessons, children's talks were recorded and their writings were collected for data interpretation. This research finds that using science books can encourage children to become engaged in communicative activities such as talking, reading, and writing in science; furthermore, using science books develops children's inquiry skills. These findings open a further discussion on scientific literacy at the K-6 levels.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".