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Record W1916316638 · doi:10.24908/pceea.v0i0.5820

PATHWAYS BETWEEN ENGINEERING AND EDUCATION FACULTIES: EFFORTS TO ESTABLISH AN ENGINEERING EDUCATION GRADUATE PROGRAM AT THE UNIVERSITY OF MANITOBA

2015· article· en· W1916316638 on OpenAlexafffundvenueabout
Sandra Ingram, Richard P. Hechter, Jillian Seniuk Cicek, Douglas Ruth

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Manitoba
KeywordsAccreditationScope (computer science)Engineering ethicsEngineering educationGraduate educationHigher educationEngineeringMedical educationPolitical sciencePedagogySociologyEngineering managementMedicineComputer science

Abstract

fetched live from OpenAlex

Engineering education is a recognized field of research and inquiry that draws on a number of established disciplines to enhance the practice and teaching of engineering. Within the last ten years, some universities in the U.S. and abroad have developed engineering education graduate programs with an emphasis on drawing from the education discipline in particular. These programs range in scope from those in which graduate students maintain a technical area of expertise alongside a focus on pedagogy to more interdisciplinary collaborations with education faculties. In Canada, such programs are still in development and the more recent movement towards outcomes-based assessment in engineering schools to satisfy changing accreditation requirements, has further mobilized an institutional interest in teaching and learning processes. This paper reports on the evolution of such a program, combining the expertise of both engineering and education faculties at the University of Manitoba to achieve this synergy.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
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 studies0.0000.000
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 head0.014
GPT teacher head0.199
Teacher spread0.185 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2015
Admission routes4
Has abstractyes

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