Asynchronous Discussions to Enhance Online Communities of Inquiry in the Saudi Higher Education Context
Bibliographic record
Abstract
This paper aimed to examine the efficiency of web-based asynchronous discussions in establishing and sustaining online collaborative learning communities in the Saudi higher educational context, by adopting the Community of Inquiry (Garrison et al., 1999) framework as a guiding model. The implementation involved setting up online asynchronous discussions in the Blackboard Learning Management System for a fourth-year undergraduate Education course over 20 days. By using a mixed methodology approach, the results revealed that within the Saudi university context, social presence patterns changed over time, with an overall increase in their levels. This increase attributed to three main factors: the instructors’ effective participation; peers’ active contribution; and the student’s desire to receive higher marks. However, the levels of students’ cognitive presence did not show adequate growth, which is assigned mainly to an inadequate teaching presence. The study also explored the relationships between the three factors and concluded that in order for students to achieve their goals via online learning communities, time is an important consideration.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".