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Record W1952186102 · doi:10.24908/pceea.v0i0.3619

Towards a scale and tool for the appraisal of CEAB attributes - Progress report on a field test

2011· article· en· W1952186102 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) · 2011
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsGraduation (instrument)Likert scaleScale (ratio)TransferabilityInternshipMeaning (existential)Test (biology)Mathematics educationPsychologyField (mathematics)Critical appraisalMedical educationComputer scienceKnowledge managementEngineeringMathematicsCartographyGeographyMachine learningMedicineLogitMechanical engineering

Abstract

fetched live from OpenAlex

CEAB 2014 requires the appraisal of ‘attributes’. Quasi-competencies are not easy to ‘measure’. Results risk having a ‘local’ meaning with little transferability between institutions. From its interest into CDIO, and in parallel to its partaking in the DOCET project, École Polytechnique developed a 7-level scale, fieldtested by nearly 100 appraisals pre-graduation work experiences. The paper summarizes the rationale behind the 7-level scale when compared to the 5-level CDIO scale, the possible mapping onto the EQF, and reports on the appraisals of students after 16 weeks internships. Supervisors appear to use the tool as a relative Likert-type scale, and will have to undergo a learning curve. Attributes appraisal tools need to be engineered rather than to be determined by consensus.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.164
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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