Evaluation by Grade 5 and 6 Students of the Promisingness of Ideas in Knowledge-Building Discourse.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Knowledge creation requires identifying and pursuing promising ideas—ideas that in their nascent form may not seem like much but that with development could grow into something big. The goal of our research is to develop a tool to explore the concept of promisingness and “big ideas,” especially elementary school students’ ability to make “promisingness judgments” regarding ideas in peer discourse. Toward this end we developed a “Big Ideas” tool to facilitate students’ selection of the ideas they thought were promising in their online discourse. A study conducted in two Grade 5/6 classes examined the nature of “big ideas” selected from the online discourse of younger Grade 4 students. A preliminary analysis indicated that students tended to identify as promising important facts and questions in the Grade 4 discourse. This study will inform future work in designing tools, language, and techniques to facilitate the concept of promisingness.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it