MétaCan
Menu
Back to cohort
Record W2909352809 · doi:10.24908/pceea.v0i0.13084

AN ENGINEERING DESIGN COURSE TO DEVELOP AND ASSESS CRITICAL THINKING AND PROBLEM SOLVING

2018· article· en· W2909352809 on OpenAlexaffvenue
Ryan P. Mulligan, Natalie Simper, Nerissa Mulligan

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsQueen's University
Fundersnot available
KeywordsRubricTest (biology)Engineering design processPlan (archaeology)Mathematics educationProcess (computing)Computer scienceEngineering educationCritical thinkingTest designCourse (navigation)Engineering managementEngineeringPsychologyMechanical engineeringTest methodMathematics

Abstract

fetched live from OpenAlex

A challenging new engineering design course is developed as part of the Engineering Design and Practice Sequence in the Civil Engineering program. This course engages students in a cyclical design process where they plan, build, test, and evaluate a model-scale tidal current turbine. They then use their own observations and analysis to iteratively inform, improve and re-test their design.The two objectives of this paper are to provide a description of the development and structure of this design course, and to assess student learning. The Final Design Reports were externally evaluated using the Valid Assessment of Learning in Undergraduate Education rubrics. Students also completed a standardized test called the Collegiate Learning Assessment as an objective evaluation of longitudinal learning gains. The Civil Engineering students demonstrated significant improvement in critical thinking, problem solving, and written communication skills.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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 teacher head, not a consensus.

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

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

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