Online Personal Learning Networks for Older Adults: Impacts on Social and Mental Well-Being
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 retired older adults (age 55+) who use the Internet to facilitate their informal, self-directed learning by creating and maintaining their online personal learning networks (oPLNs), and how such use impacts their personal, social, and mental well-being. Guiding this examination were particular research questions that specifically queried the perceived value of their oPLNs to activate and self-direct their informal learning. The web-conferencing tool WebEx was used to conduct four synchronous online focus groups allowing a total of 15 voluntary, geographically dispersed participants from across Canada to share their experiences and insights. A thematic analysis of the focus group transcripts revealed themes informing how oPLNs facilitated their informal learning goals and influenced participants’ personal valuing of their online activity. As a component of results from the larger research study (Morrison, Litchenwald, & Krystkowiak, 2020; Morrison, Litchewald, & Tang, 2020; Morrison & McCutcheon, 2019) , the findings presented, drawn from the online focus group qualitative data, indicated positive perceived valuing of their informal learning via their oPLNs as well as indications of favorable social and mental well-being outcomes. Interpretive speculation is provided regarding how these informal online learning experiences and oPLNs in particular, may point to a favorable impact on similar retired older adults’ personal, social, and mental well-being.
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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 | 0.001 |
| 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 | 0.000 |
| 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 it