Student Moderators in Asynchronous Online Discussion: A Question of Questions
Bibliographic record
Abstract
Much current research exalts the benefits of having students facilitate weekly discussions in asynchronous online courses. This study seeks to add to what \nis known about student moderation through an analysis of the types of questions students use to spur each discussion. Prior experimental work has demonstrated \nthat the types of questions posed by instructors influence the cognitive levels of responses, but little is known about the extent to which student moderators \nuse these various question forms. Question types and the cognitive levels of responses in an online graduate course were analyzed, and it was found that \nstudents relied on a small number of question forms. In particular, students rarely asked questions directly related to weekly course readings, and did \nnot ask any questions that made connections to previously studied course material. Questions that constrained student choice led to lower levels of responses \ncompared to other question types.
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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 | 0.099 | 0.232 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.009 | 0.025 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".