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Record W3088253536 · doi:10.5539/ies.v13n10p60

Incorporating Adult Learning Principles in High-Risk Equipment Operations Training

2020· article· en· W3088253536 on OpenAlexvenueno aff
Richard Skiba

Bibliographic record

VenueInternational Education Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Leadership and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsVocational educationAdult educationAdult LearningTraining (meteorology)AndragogyHarmAsideLifelong learningPsychologyDutyPedagogyMedical educationMathematics educationMedicinePolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

This paper, primarily based on a literature review, considers the utilization of adult learning principles in training learners to operate high risk equipment. Vocational Education and Training sectors throughout the world are traditionally responsible for training delivery in these areas where generally andragogical principles as defined by Knowles (1970), are applied with, in some cases, application of a heutagogical approach, as outlined by Hase and Kenyon (2000). Aside from considering these approaches, a new approach is proposed, referred to as authology, with a basis of including notions of responsibility and duty of care in adult learning. There are numerous training programs in vocational education and training, such as those related to high risk equipment and plant operation, for which development of learner responsibility is a critical component in the training given the potential to cause harm, injury or fatality.

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)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.215
GPT teacher head0.424
Teacher spread0.209 · 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
Published2020
Admission routes1
Has abstractyes

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