Understanding the nature of science and scientific progress: A theory-building approach
Bibliographic record
Abstract
In 1993 Carey and Smith conjectured that the most promising way to boost students’ understanding of the nature of science is a “theory-building approach to teaching about inquiry.” The research reported here tested this conjecture by comparing results from two Grade 4 classrooms that differed in their emphasis on and technological support for creating and improving theories. One class followed a Knowledge Building approach and used Knowledge Forum®, which together emphasize theory improvement and sustained creative work with ideas. The other class followed an inquiry approach mediated through collaborative project-based activities. Apart from this, the two classes were demographically similar and both fell within the broad category of constructivist, inquiry-based approaches and employed a range of modes and media for investigative research and reports. An augmented version of Carey and Smith’s Nature of Science Interview showed that the Knowledge Building approach resulted in deeper understanding of the nature of theoretical progress, the connections between theories and facts, and the role of ideas in scientific inquiry.
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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 | 0.034 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.014 | 0.006 |
| Science and technology studies | 0.005 | 0.045 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".