Facilitating open online discussions: speech acts inspiring and hindering deep conversations
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
Creating an online learning environment that engages learners beyond the given course period is challenging. Open, participant-driven discussion forums, where participants are provided with greater agency on what to learn, how to learn, and whom to learn with, have a unique potential to help learners engage in learning experiences based on their interests and needs. Based on sequential and qualitative analysis of speech acts found in the participant-initiated discussion threads hosted as part of a massive open online course, this paper explored the impact of participant actions as facilitative moves to gain a better understanding of the types of actions in the discussion that stimulated deeper engagement with the ideas of interest. The analysis identified several facilitative moves that nurture or hinder deeper conversation in an open online discussion forum that has design implications. The paper also highlights the potential of analysing conversation sequences of posts as a promising method to study discussion forum data.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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