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Record W2767734484 · doi:10.5430/ijhe.v6n6p19

Positions and Preferences: Faculty Goes for Lifelong Learning, a View from Turkey

2017· article· en· W2767734484 on OpenAlexvenueno aff
Halil İbrahim Haseski, Hatice Ferhan Odabaşı

Bibliographic record

VenueInternational Journal of Higher Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsLifelong learningPsychologyMedical educationAffect (linguistics)Survey researchPedagogyMathematics educationMedicineApplied psychology

Abstract

fetched live from OpenAlex

The purpose of this study is to investigate academicians’ lifelong learning positions and preferences. The research was designed as survey research. The participants consisted of 230 academicians from Faculty of Education of Anadolu University in Turkey. Data was collected using a survey form which had items about the factors that affect lifelong learning process of academicians. It was found that lifelong learning survey scores of participants vary according to their departments, branches, ages, seniorities, genders and academic titles. It was also found that academicians of education faculty mainly participate in scientific and teaching activities in lifelong learning.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.040
GPT teacher head0.428
Teacher spread0.388 · 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 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

Citations2
Published2017
Admission routes1
Has abstractyes

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