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Record W2601117084 · doi:10.24908/pceea.v0i0.6509

Designing Rubrics to Assess Engineering Design, Professional Practice, and Communication Over Three Years of Study

2017· article· en· W2601117084 on OpenAlex
Natasha Lanziner, David Strong

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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2017
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsNatural Sciences and Engineering Research Council of CanadaQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRubricPeer assessmentAccreditationProcess (computing)Computer scienceFlexibility (engineering)Mathematics educationEngineering managementEngineeringPsychologyMedical educationMathematics

Abstract

fetched live from OpenAlex

When using rubric-based assessment of students’ understanding of design process in project based courses, it is important to provide specific feedback for major design process elements while avoiding overly prescriptive descriptors [8]. This paper details the development process of a sequence of rubrics used for assessment in successive second, third and fourth year project-based courses. A major consideration in the rubric development process was to ensure the alignment of assessment with course learning outcomes that can be easily mapped to the CEAB graduate attribute accreditation requirements. In the second year course, the rubrics are used to provide students with directed feedback as they learn the basics of engineering design process. The third and fourth year rubrics progress from the second year analytic rubrics by employing elements of holistic assessment. The purpose of evolving these rubrics year over year is to find a balance between the students’ learning and development in design process whilst accommodating variation in projects. This ultimatelyprovides students with greater flexibility and encourages responsibility as they progress through their program.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.305
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0010.000
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 head0.017
GPT teacher head0.260
Teacher spread0.243 · 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