The development of children's epistemic beliefs across the early years of elementary school
Bibliographic record
Abstract
BACKGROUND: A growing body of research shows that the beliefs we hold about the nature of knowing and knowledge (epistemic beliefs) may mediate moral reasoning. However, a limitation of much of the research in the area of epistemic beliefs is the lack of a longitudinal approach. AIMS: The study investigated longitudinal changes in Australian elementary school children's beliefs about knowing and knowledge (epistemic beliefs) across three judgement domains (personal taste, ambiguous facts, and moral values). SAMPLE: The participants in this longitudinal study were tracked from Year 1 through to Year 3 of primary school. In Year 1, there were 169 participants (83 boys, 86 girls) aged 6-7 years (M = 6.7, SD = 0.32). In Year 2, there were 156 participants (79 boys, 77 girls), and in Year 3, there were 129 participants (65 boys, 64 girls). METHODS: Using vignettes that reflected each of the three judgement domains, children were interviewed about the beliefs held by two puppet characters. The interviews took place each year across the early years of elementary education in Year 1, Year 2, and Year 3. RESULTS: Findings revealed that children's epistemic beliefs in each of the judgement domains became more subjectivist over time but that the age at which this occurred differed according to the judgement domain in question. CONCLUSIONS: We argue that it is important for teachers to pay attention to children's beliefs about the nature of knowledge and knowing in the process of scaffolding their reasoning about moral values for active citizenship.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".