Students' intuitive understanding of promisingness and promisingness judgments to facilitate knowledge advancement
Bibliographic record
Abstract
Abstract: The ability to identify promising ideas is an important but obscure and undeveloped aspect of knowledge building. The goal of this research was to examine the extent to which young students can make promisingness judgments and, as a result, engage in more effective knowledge building. Toward this end we embedded a design experiment in a Grade 3 classroom. In this experiment students were engaged in discussion and reflection of the concept of promisingness and used a Promising Ideas tool to identify promising ideas in their written online discourse. They used the tool for two refinements of idea selections to focus ongoing community dialogue. Results suggest that students as young as 8 years of age can make promisingness judgments that facilitate knowledge advancement in their work. These results inform future work in classroom interventions and tool development to promote promisingness judgments in collaborative knowledge building. Like scientists in research laboratories (Dunbar, 1995), students engaged in knowledge building participate in constructive and progressive knowledge-building discourse, in which they contribute to group dialogue in distinctive ways, including proposing theories, synthesizing ideas, and making analogies (Chuy, Zhang, Resendes, Scardamalia, & Bereiter, 2011). A knowledge building principle that frames such discourse is
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".