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Record W2886656207 · doi:10.21125/edulearn.2018.2225

AN INTERNATIONAL CROSS-DISCIPLINARY STUDENT COLLABORATION: A RETROSPECTIVE EIGHT YEARS

2018· article· en· W2886656207 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEDULEARN proceedings · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsToronto Metropolitan University
FundersHigher Education Authority
KeywordsCross disciplinaryKingdomLibrary scienceDisciplinePolitical scienceComputer scienceData scienceLaw

Abstract

fetched live from OpenAlex

A successful construction endeavour invariably obliges a successful collaborative effort among its many multi-disciplinary stakeholders. Teachers of construction education today are increasingly aware of the need to teach their students skills to enable them to work collaboratively with their peers from other related disciplines. In the present day context of an increasingly globalized construction industry amidst a current rapid advancement in communication technology, an ability to work collaboratively with peers across a geographical divide within an online environment is a valuable skill to have. This paper presents the collective experiences of two distant universities where students from two related disciplines -architectural science (with a construction project management major) and civil engineering -collaborate on a joint student assignment across a time and geographical divide. It presents a description of the project and its intent, teaching pedagogy, students' feedback and the challenges of establishing the framework.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.000
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 head0.023
GPT teacher head0.462
Teacher spread0.440 · 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