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Record W1912448340 · doi:10.24908/pceea.v0i0.3108

The Impact of CEAB Accreditation Requirements Changes on Engineering Curricula Design and Development

2010· article· en· W1912448340 on OpenAlexaffvenueabout
Kin Fun Li, A. Zieliński

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2010
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of VictoriaSimon Fraser University
Fundersnot available
KeywordsAccreditationCurriculumEngineeringEngineering ethicsEngineering managementSystems engineeringMedical educationMedicinePsychologyPedagogy

Abstract

fetched live from OpenAlex

The Canadian Engineering Accreditation Board (CEAB) has recently made some changes to the accreditation criteria for engineering programs, effective fall 2009.The major changes include an attribute-based outcome assessment, increased minimum accreditation units for the entire program, and engineering design and engineering science curriculum components taught by registered professional engineers.The engineering programs at the University of Victoria were among the first programs to be evaluated by the CEAB using the new accreditation criteria.As the directors of the computer and electrical engineering programs respectively, the authors were involved in the preparation of the accreditation documents and the site visit in winter 2010.In this paper, the authors share their recent accreditation experience and also provide some thoughts on the new accreditation criteria's impact on curriculum design and development, and program delivery.

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)0.048
metaresearch head score (Gemma)0.191
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.191
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0050.002
Scholarly communication0.0080.002
Open science0.0050.003
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0070.002

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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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 designQualitative
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

Citations0
Published2010
Admission routes3
Has abstractyes

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