Growth patterns and E-Moderating Supports in Asynchronous Online Discussions in an Undergraduate Blended Course
Bibliographic record
Abstract
<p>This study presents a case study of asynchronous online discussions’ (AOD) growth patterns in an undergraduate blended course to address the gap in our current understanding of how threads are developed in peer-moderated AODs. Building on a taxonomy of thread pattern proposed by Chan, Hew and Cheung (2009), growth patterns of thirty-six forums were explored on three patterns: Short Thread Pattern (SHTP), Extended Thread Pattern (ETP), and Split Thread Pattern (STP). The impact of peer moderating supports on thread growth was also investigated. Types of peer moderators’ supports were explored utilizing a coding scheme from Smet, Keer, Wever, and Valcke’s (2010) study. STP pattern was found to be more common than the other patterns with 74 (37.94%) out of 195 threaded discussions growing on it. The results also showed that, compared to SHTP, in both STP and ETP the occurrences of ‘Information exchange’ and ‘Knowledge construction’ supports appeared to be more, while the presences of supports stimulating ‘Development’, ‘Access and motivation’ and ‘Socialization’ were less. Furthermore, the use of ‘Access and motivation’ and ‘Socialization’ supports appeared to enhance early thread termination when used individually. Thread continuity was reinforced by the use of ‘Knowledge construction’ support with other moderating supports.<em></em></p>
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.
How this classification was reachedexpand
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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".