User-Centered Design Principles for Online Learning Communities
Bibliographic record
Abstract
This chapter examines current research on online learning communities (OLCs), with aim of identifying User-Centred Design (UCD) principles critical to the emergence and sustainability of distributed communities of practice (DCoP), a kind of an OLC. This research synthesis is motivated by the authors’ involvement in constructing a DCoP dedicated to improving awareness, research and sharing data and knowledge in the field of governance and international development. It argues that the sociotechnical research programme offers useable insights on questions of constructability. Its attention in particular to participatory design and human-computer interaction are germane to designing User-Centered online learning communities. Aside from these insights, research has yet to probe in any systematic fashion the factors affecting the perfromance and sustainability of DCoP. The chapter concludes with a discussion of User-Centred Design (UCD) principles for online learning community to support the construction and deployment of online learning communities.
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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 | 0.020 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".