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Record W2887814253 · doi:10.24908/pceea.v0i0.10311

DESIGN OF A CONSISTENT INTERDISCIPLINARY AND DUAL FACULTY CAPSTONE EXPERIENCE AT THE UNIVERSITY OF MANITOBA

2018· article· en· W2887814253 on OpenAlexafffundvenueabout
W.C.D. DeGagne, Paul Labossière

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Manitoba
FundersUniversity of Toronto
KeywordsCapstoneAccreditationEngineering educationCapstone courseEngineering ethicsWork (physics)ArchitectureMedical educationEngineeringEngineering managementPedagogySociologyMedicineComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Abstract - One of the most effective and efficient ways for an engineering program to facilitate compliance with the Canadian Engineering Accreditation Board (CEAB) accreditation criteria is through capstone design projects and courses, [1]. Currently, the University of Manitoba Faculty of Engineering has several capstone design courses; however, each is independently focused on its own respective discipline. The resulting educational experience for students, though rigorous and challenging, is maintained within the boundaries of the students’ engineering discipline, thereby neglecting to provide the opportunity for students to work with people from multiple disciplines and across different faculties. This style/mode of education, where students work in silos, arguably does not reflect real world engineering. Program representatives from the Faculty of Engineering at the University of Manitoba agree that the capstones should be more reflective of real life situations. For this paper, we were hoping to present the research results of a pilot interdisciplinary capstone that was to be launch in the winter of 2017. Unfortunately, the pilot course was not offered because of low student enrollment. So we decided to take an innovative and creative approach to the research. Since, at the University of Manitoba, the Dean of Engineering is also the Dean of the Faculty of Architecture, rather than team with an outside industry focus group, we decided to develop a holistic course with the Faculty of Architecture. The Dean supports this strategy. Interdisciplinary courses are most important because they "…articulate the difference between educational problems and workplace problems" [2]. And allow "(students) persons from different disciplines to work collaboratively and are integrated to combine their knowledge to solve a problem"[3]. This paper explores and explains how that Engineering/Architecture Multidiscipline Capstone and Dual Faculty course will be developed, touches on the early stages of its initiation and implementation, and outlines how the success of the new course will be evaluated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.003
Scholarly communication0.0040.002
Open science0.0030.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.011
GPT teacher head0.203
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations2
Published2018
Admission routes4
Has abstractyes

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