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Record W2234313352 · doi:10.24908/pceea.v0i0.3801

DESIGNING A RUBRIC TO ASSESS THE MODELLING PHASE OF STUDENT DESIGN PROJECTS IN UPPER YEAR ENGINEERING COURSES

2011· article· en· W2234313352 on OpenAlexaffvenue
Thomas F. C. Woodhall, David S. Strong

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsNatural Sciences and Engineering Research Council of CanadaQueen's University
Fundersnot available
KeywordsRubricCapstoneProcess (computing)Key (lock)Computer scienceMathematics educationEngineering design processBridge (graph theory)PsychologyEngineering

Abstract

fetched live from OpenAlex

In order to bridge the gap between a student’s understanding and an instructor’s perception of subject mastery, it is important to assess upper year capstone design projects in a way which targets the important aspects within each stage in the design process while providing feedback that is instructive and helpful. Using the design process itself a rubric was created that assesses a student’s mastery of the modelling phase of the design project (as defined by Dominik). The rubric assesses students in two areas: key concepts and key steps. These areas fully encompass the goals of the modeling phase, not only in terms of the project’s completion, but also relate to the learning goals that instructors should have for the student, as well as providing feedback that can help develop a student’s mastery of the topic area.

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)0.021
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.102
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.068
GPT teacher head0.278
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

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 designNot applicable
Domainnot available
GenreMethods

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

Citations2
Published2011
Admission routes2
Has abstractyes

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Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicDesign Education and PracticeFrench-language works237,207