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
This paper describes an application of learning analytics that builds on an existing research program investigating how students contribute and attend to the messages of others in online discussions. A pedagogical model that translates the concepts and findings of the research program into guidelines for practice and analytics with which students and instructors can assess their discussion participation are presented. The analytics are both embedded in the learning environment and extracted from it, allowing for integrated and reflective metacognitive activity. The pedagogical intervention is based on the principles of (1) Integration (2) Diversity (of Metrics) (3) Agency (4) Reflection (5) Parity and (6) Dialogue. Details of an initial implementation of this approach and preliminary findings are described. Initial results strongly support the value of student-teacher dialogue around the analytics. In contrast, instructor parity in analytics use did not seem as important to students as was expected. Analytics were reported as useful in validating invisible discussion activity, but at times triggered emotionally-charged responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.006 | 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