Online Learning Opportunities Provided by the Engineering Communities of Practice
Bibliographic record
Abstract
This paper examines learning opportunities provided by the online engineering communities of practice. These communities are communities of professionals and others, who share knowledge and resources using the Internet as a communication and collaboration channel and a shared virtual community space. The discussion in the paper is based on a recent study of design features and functionality of existing online professional communities of practice, and on the authors' experience in teaching and development of the computer-based learning resources. One of the models for a virtual community of practice that provides great means for knowledge sharing and collaboration is the "Knowledge Portal" model. This model fulfills the basic online community of practice portal requirements including online learning resources that support learning opportunities for the members of the community. The authors discuss several learning scenarios enabled by the online Knowledge Portal and demonstrate how online resources could be used in the Civil Engineering materials curriculum. Within the conclusion, the authors recommend some design features and useful functionality of the online communities of practice that facilitate lifelong learning by the members of the community and enable wide-ranging learning opportunities for students that are entering the professional engineering field.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".