Bibliographic record
Abstract
The role of social presence as defined by the community of inquiry (CoI) framework is critiqued through a review of recent literature. Evidence is presented that questions the actual extent of knowledge co-construction that occurs in most higher education settings and therefore challenges the framework’s underlying assumption of the need for sustained, contiguous, two-way communication in higher-level online learning environments. The CoI framework has evolved from the description of a learning process within a social constructivist paradigm to an empirically testable construct in an objectivist paradigm. Related research results indicate that social presence does not impact cognitive presence in a meaningful way and that best teaching practices suggested by CoI-based studies are informed by objectivist, cognitively oriented learning theories. These suggest that higher-order cognition may be achieved through wide and varied combinations of learner–teacher, learner–content, and learner–learner interaction. Controlled studies can and should be undertaken to compare learning outcomes using sustained, contiguous, two-way communication to other learning models. To facilitate this, subcategories of social and teaching presences need to be revamped and analysis adjusted to separate processes that support explicitly group-based learning activities from those used by individual students.
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 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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.044 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.005 | 0.004 |
| 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".