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Record W2109291969 · doi:10.24908/pceea.v0i0.3611

Employing Co-op Employer Evaluations to Assess Outcomes

2011· article· en· W2109291969 on OpenAlexaffvenueabout
Wayne J. Parker, Rocco Fondacaro, Oscar Nespoli

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAccreditationWork (physics)Presentation (obstetrics)Engineering educationProcess (computing)Term (time)Medical educationWork in processHigher educationComputer scienceEngineering managementPsychologyEngineeringPolitical scienceOperations managementMedicineMechanical engineering

Abstract

fetched live from OpenAlex

The Faculty of Engineering at the University of Waterloo is preparing to employ outcomes-based assessments to inform program improvement as required by the Canadian Engineering Accreditation Board (CEAB) and the Ontario Council of Academic Vice Presidents (OCAV). Engineering at Waterloo requires all students to complete five 4-month work terms to graduate; a model of Co-operative education that involves a sequence of alternating work and academic terms. Upon completion of each work term employers complete a Student Performance Evaluation (SPE) that provides students with feedback on their work term and is employed to assign a grade to the student for the term. This presentation will describe an innovative use of historical SPE information to initiate a process that will lead to their use for outcomesassessment for program enhancement.

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)0.043
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.091
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.265
Teacher spread0.234 · 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 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

Citations5
Published2011
Admission routes3
Has abstractyes

Explore more

Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicEngineering Education and Curriculum DevelopmentFrench-language works237,207