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Record W2101812019 · doi:10.24908/pceea.v0i0.4680

INNOVATIVE ASSESSMENT OF CEAB GRADUATE ATTRIBUTES IN LARGE CLASS: LAW AND ETHICS IN ENGINEERING PRACTICE

2012· article· en· W2101812019 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2012
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsClass (philosophy)Mathematics educationEquity (law)Graduate studentsPsychologyLifelong learningEngineering ethicsMedical educationEngineeringComputer sciencePedagogyArtificial intelligencePolitical scienceLawMedicine

Abstract

fetched live from OpenAlex

Four CEAB graduate attributes were assessed in a fourth-year common engineering course. The graduate attributes assessed were: professionalism, impact of engineering on society and environment, ethics and equity, and lifelong learning. The course addressed the legal and ethical aspects of engineering practice. The learning objectives were assessed in the midterm and final exams for the entire class (446 students) using multiple choice questions. An innovative method to assess the learning objectives was developed. Each learning objective was divided into a number of knowledge elements or case-study behavioural elements. A question was then developed for each element. The group of questions was used as the basis for establishing scales to measure student performance. Three scales were defined: poor, average, and excellent based on the number of questions the students answered correctly. Based on the assessment results, program improvements related to the learning objectives were identified.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.269
Teacher spread0.252 · 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