Older Adults’ Use of Online Personal Learning Networks to Construct Communities of Learning
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
This study investigated how retired older adults (age 55+) use the Internet and social media tools to facilitate their informal, self-directed learning by creating and maintaining online personal learning networks (oPLNs). The research examined what information and communication technologies (ICT) participants included in their oPLNs and how they used these oPLNs to activate and self-direct their informal learning. Employing the web-conferencing tool WebEx, four online focus groups and four one-to-one audio interviews were conducted allowing for a total of 15 voluntary, geographically-dispersed participants from across Canada to synchronously interact and exchange their experiences and insights regarding their oPLNs. Using a thematic analysis method, the discussion transcripts generated were analyzed to examine learning contexts, strategies to manage learning, motivation to learn and achievement of learning goals, as well as to discover emergent themes. It was clear from our findings that oPLNs provided a virtual "learning community" that supported informal, self-directed learning via learner participation and interaction opportunities fostered by ICT-based tools and processes.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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