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Record W2969299092 · doi:10.1186/s41039-019-0104-5

Empowering older adults’ informal, self-directed learning: harnessing the potential of online personal learning networks

2019· article· en· W2969299092 on OpenAlexafffund
Dirk Morrison, Jessica McCutheon

Bibliographic record

VenueResearch and Practice in Technology Enhanced Learning · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInformal learningLifelong learningThe InternetLeverage (statistics)FacilitationAdaptation (eye)Social mediaPsychologyKnowledge managementComputer scienceInternet privacyWorld Wide WebPedagogyArtificial intelligence

Abstract

fetched live from OpenAlex

Information and communication technologies have had an enormous impact on how we live, work, communicate, re-create, and connect with others. However, there is a paucity of research regarding older adult learners’ adoption and adaptation of Internet-based tools, techniques, and resources to support their informal, self-directed lifelong learning goals. This research contributes to our understanding of how and why older adults leverage the Internet and social media tools to create, develop, and maintain online personal learning networks (oPLNs) for the purposes of self-directed knowledge acquisition, personal development, and the facilitation of healthy aging.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.015
GPT teacher head0.360
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations44
Published2019
Admission routes2
Has abstractyes

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