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Record W1770370153 · doi:10.24908/pceea.v0i0.3892

A COURSE IN MECHATRONICS AND CALLING THE BLUFF ON ACTIVE LEARNING

2011· article· en· W1770370153 on OpenAlexaffvenue
Brian Surgenor, Kevin Firth, Peter Wild

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicMechatronics Education and Applications
Canadian institutionsUniversity of VictoriaQueen's University
Fundersnot available
KeywordsEnthusiasmMechatronicsCourse (navigation)BluffMultidisciplinary approachSubject (documents)Mathematics educationEngineeringActive learning (machine learning)Computer scienceEngineering managementPsychologyArtificial intelligenceSociologyLibrary scienceMathematics

Abstract

fetched live from OpenAlex

When one talks about the elements needed for the next generation of engineering students, a list of the keywords typically includes the following: active learning, integrated learning, just in time instruction, theory versus practise, written and oral communication, multidisciplinary and interdisciplinary teams, lectures, tutorials, laboratories, workshops and design projects. An elective course in mechatronics engineering at Queen’s University is put forward as an example of how one course can encompass all of these elements, and equally important, be able to promote the excitement and enthusiasm among the students for the subject in a manner that should be present in all engineering courses.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.311

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0930.027

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 head0.007
GPT teacher head0.186
Teacher spread0.179 · 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 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

Citations3
Published2011
Admission routes2
Has abstractyes

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