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Record W2252924954

Reflection on the impact of international work integrated learning (WIL) placements: a 20 year study

2011· other· en· W2252924954 on OpenAlexaboutno aff
Neil Ward

Bibliographic record

VenueSwinburne Research Bank (Swinburne University of Technology) · 2011
Typeother
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsReflection (computer programming)Work (physics)PedagogyEngineering ethicsMathematics educationSociologyPsychologyComputer scienceEngineeringMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Chemistry, University of Surrey (UK) and Swinburne University of Technology (Australia) have been involved in an international work integrated learning (WIL) student exchange programme for more than 20 years. Students undertaking a 4-year chemistry-based undergraduate degree course spend 12-months on placement at a chemical company in numerous countries, such as, the UK, Australia, Canada, New Zealand, etc. Most students feel that this type of WIL experience is 'fantastic' and provides the opportunity to develop academic and future career competencies along with broadening their personal and cultural ideas. Cultural development, including personal development, language enrichment and learning about one's national and international identity may be more rewarding credits of the overseas placement experience. Many former WIL students cite that their international placement played a major role in their career development, and the challenges they had to confront and resolve provided a strong backbone for dealing with future problems. Moreover, many reported that a major bonus of international WIL was that they meet their future partner and the multi-lingual and culture learning outcomes have changed the way they address the upbringing of their own children. More outcomes will also be reported.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.330
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0270.000

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 head0.085
GPT teacher head0.402
Teacher spread0.317 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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