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Record W7001988785

Mapping the use of ePortfolios for RPL in Australia

2011· article· en· W7001988785 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAcquire (CQUniversity) · 2011
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsWorkforceVocational educationWork (physics)AutonomyHuman capitalHigher educationExploratory researchWorkforce developmentDistance educationTraining (meteorology)Workplace learning
DOInot available

Abstract

fetched live from OpenAlex

Recognition of prior learning (RPL) was first introduced in Australia in 1992 as part of the national framework for the recognition of training (NFROT). It has become an embedded in the Australian Qualifications Framework (AQF) and since then has slowly become a central activity within post compulsory education and training. Today RPL has become a significant activity within the vocational education and training (VET) sector when compared to other post compulsory educational sectors. This can be partially explained by the fact that RPL is mandatory in the VET sector, unlike the higher education (HE) sector which is self-accrediting and has a certain amount of autonomy in deciding whether or not to adopt RPL policy. RPL is also a significant activity outside the education sector and impacts on broader human capital and workforce development policy and initiatives. The aim of this paper is to map the application of ePortfolios and mobile web devices for the recognition of prior learning as a new and emergent area of practice. In particular the use of ePortfolios and RPL for the recognition of work based skills and professional recognition will be explored. The research conducted is exploratory and involves a content analysis of several secondary data sources including: papers from the 2009 and 2010 Australian ePortfolio Conferences; funded RPL projects through the Australian Flexible Learning Framework- 009-2011; and conference papers form the Australian Vocational Education Training Research Association (AVETRA). It is envisaged the research will be expanded to international developments in the same areas and will use the Prior Learning International Research Centre (PLIRC) based at Thompson Rivers University in BC, Canada, as a major conduit to the research. PLIRC comprises a group of international scholars in the field of RPL. The centre has been developing an international research agenda for RPL since June 2009 and it is hoped this research will form part of that future international research agenda.

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.

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 score0.035
Threshold uncertainty score0.242

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 studies0.0000.000
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 head0.258
GPT teacher head0.280
Teacher spread0.022 · 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