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Record W6931549440 · doi:10.5281/zenodo.7353169

MULTI-LEVEL PLANNING THEORETICAL MODEL: A PROPOSED FRAMEWORK FOR DESIGNING ADULT EDUCATION PROGRAMS FROM THE PERSPECTIVES OF ADULT EDUCATION PROFESSIONALS

2022· article· en· W6931549440 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsAdult educationGrounded theoryAdult LearningPerspective (graphical)Adult learnerHigher educationQualitative researchReflection (computer programming)

Abstract

fetched live from OpenAlex

This grounded theory research aims to generate a theoretical model by developing frameworks for designing adult education courses and trainings in higher education institutions (HEI) in an Asian country through the perspective and experiences of adult learners. Using purposive sampling, the participants were 13 HEI middle managers who were sent to the University of Toronto in Canada to be trained on how to meet the emerging needs of adult education professionals. The participants were asked to write down their reflection based on guide questions that asked about their insights regarding the success and challenges they encountered during their two-week adult education training. The data were analyzed using Glaser and Strauss’s (1967) model of grounded theory analysis that includes theoretical sampling, constant comparison, and theoretical sensitivity. The findings of the study generated a multi-level theoretical framework, an iterative process from the conceptual stage to the evaluation stage of an adult education program, that will assist HEIs in crafting sustainable adult education programs that exemplify best practices from the academe, industries, and businesses. The model will be useful for HEIs who are looking for innovative adult education models.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.317
Teacher spread0.272 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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