MétaCan
Menu
Back to cohort
Record W2886700377

Work-integrated learning and professional accreditation policies: An environmental health higher education perspective

2018· article· en· W2886700377 on OpenAlexfundno aff
Louise Dunn, Rosemary Nicholson, Kirstin Ross, Lisa Bricknell, Belinda Davies, Toni Hannelly, Jane-Louise Lampard, Zoë Murray, Jacques Oosthuizen, Anne Roiko, James L. Wood

Bibliographic record

VenueQUT ePrints (Queensland University of Technology) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
FundersUniversity of South AfricaCollege of Engineering, Michigan State UniversityTshwane University of TechnologyUniversity of WaterlooUniversity of SurreyCurtin University of TechnologyUniversity of CincinnatiGriffith UniversityDeakin UniversityMichigan State UniversityFlinders UniversityUniversity of New EnglandMassey UniversityAuckland University of Technology, New ZealandSouthern Cross UniversityQueensland University of TechnologyUniversity of WaikatoUniversity of New South Wales
KeywordsAccreditationStakeholderWork (physics)Perspective (graphical)Participatory action researchCitizen journalismEngineering ethicsMedical educationPublic relationsProfessional developmentPedagogySociologyPolitical scienceMedicineEngineeringComputer science
DOInot available

Abstract

fetched live from OpenAlex

<b>Free to read on publisher website</b> The introduction of a new work-integrated learning (WIL) policy for university environmental health education programs seeking professional accreditation identified a number of problems. This included how to evaluate the acceptability of differing approaches to WIL for course accreditation purposes and a need to develop an agreed understanding of what constitutes WIL in environmental health. This paper describes a Participatory Action Research (PAR) approach undertaken as an initial step towards addressing these problems. The key recommendation from this research is the need to develop a framework to evaluate approaches to WIL in environmental health. In such a framework, it is argued that a shift in focus from a specified period of time students are engaged in WIL, to greater consideration of the essential pedagogical features of the WIL activity is required. Additionally, input from all stakeholder groups, universities, students, employers and the professional body, is required.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.016
GPT teacher head0.322
Teacher spread0.306 · 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 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

Citations5
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueQUT ePrints (Queensland University of Technology)Same topicHigher Education and EmployabilityFrench-language works237,207