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Record W1806746678 · doi:10.24908/pceea.v0i0.5781

AN EXPLORATION OF COMMUNICATION AND KNOWLEDGE APPLICATION IN MULTIDISCIPLINARY UNDERGRADUATE ENGINEERING CAPSTONE DESIGN TEAMS

2015· article· en· W1806746678 on OpenAlex
Mario Milicevic, Narges Balouchestani Asli, Deborah Tihanyi, Kamran Behdinan

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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsCapstoneMultidisciplinary approachCapstone courseTeamworkMultidisciplinary teamComputer scienceEngineering educationWork (physics)Knowledge sharingKnowledge managementEngineering managementEngineeringSociologyMedicine

Abstract

fetched live from OpenAlex

Multidisciplinary capstone design projectsoffer students the opportunity to solve complexengineering problems that span multiple disciplinesthrough collaborative, team-based learning. Using amixed quantitative and qualitative approach, this studyexamines student experience in a multidisciplinarycapstone design course by analyzing how disciplinaryknowledge is applied, taught, and learned among teammembers. Our preliminary findings suggest correlationsbetween open communication, sharing of disciplinaryknowledge, and the likelihood of taking design risks.Future work will further explore the reasons behind thesecorrelations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.724

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 studies0.0000.000
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 head0.024
GPT teacher head0.263
Teacher spread0.239 · 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