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Record W1578970460 · doi:10.21225/d5688r

Older Adult Learners: A Comparison of Active and Non-Active Learners

2007· article· en· W1578970460 on OpenAlexaffvenueabout
Atlanta Sloane-Seale, Bill Kops

Bibliographic record

VenueCanadian Journal of University Continuing Education · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsLifelong learningGeneral partnershipPsychologyMedical educationSocioeconomic statusPerceptionGerontologyAdult educationPopulationPedagogyMedicinePolitical science

Abstract

fetched live from OpenAlex

This paper reports on a 2004 follow-up study conducted in partnership with the University of Manitoba Continuing Education Division and local senior’s organizations. The partnership was formed in 2002–03 to promote applied research on lifelong learning and older adults, develop new and complement existing educational activities, and explore new program models and instructional methods to meet the educational needs of retirees. The partnership involved the develop- ment of a number of activities: University in May started in 2002, a mini medical series began in 2003, and a survey was completed in 2003 to identify the learning interests, motivations, and barriers among active older adults who participate in learning activities. The 2004 follow-up study compared barriers to participation, learning interests, and motivation to those of a similar population of older adults who held membership with the organizations but had not participated in educational activities for the past two years. The results indicate that the non-active respondents are older, less healthy, less active, less educated, and have lower incomes. Time and motivation to participate may be affected by their socioeconomic standing, health, and sense of well being; that is, their perception of their social reality. Further study to explore the definition of barriers to participation and life long learning for older adults is warranted. Recommendations for program models to facilitate participation in educational opportunities should also be explored.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.270
Teacher spread0.260 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations11
Published2007
Admission routes3
Has abstractyes

Explore more

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