The Effect of Formative Feedback on Vocabulary Use and Distribution of Vocabulary Knowledge in a Grade Two Knowledge Building Class
Why this work is in the frame
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Bibliographic record
Abstract
This study examines the impact of formative feedback to enhance students' productive written vocabulary. Behavioral, lexical, and network structure analyses were applied to the work of two Grade 2 classes engaged in knowledge building in science. Two variations of feedback including vocabulary and contribution-based visualizations were integrated into the knowledge building practice of the experimental class. Behavioral and lexical measures were calculated with automated tools, and content analysis was used to evaluate depth of understanding. Moreover, the degree of vocabulary distribution throughout the communities was explored. Findings show that formative feedback embedded in knowledge building practices can help students grow their vocabulary, apply new words in productive ways in their writing, and advance community knowledge. Results also show that as students learn and use a more diverse range of words in the context of knowledge building, the more discursively connected they become, and the greater the knowledge distribution across the community.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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