Ethos and Practice of a Connected Learning Movement: Interpreting Virtually Connecting Through Alignment with Theory and Survey Results
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Virtually Connecting (VC) is a connected learning volunteer movement that enlivens virtual conference experiences by partnering those that are at the conference with virtual participants that cannot attend. In looking to articulate the ethos and intentions of VC, a manifesto was developed by a group of core members and presented at the Digital Learning Research Network in 2015. This paper connects the group’s ethos, as defined in this manifesto, to various learning theories including Connectivism, connected learning, and the practice of online communities. The paper reports on both quantitative and qualitative results from a survey sent to members of the community over February and March of 2016, as well as some information obtained from blogs and other forms of social media, and ties these results to the manifesto items. This alignment of theory and participant feedback shows continuity between the stated ethos of the community and the impressions of those living the volunteer experience.
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.
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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it