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Record W2732347781 · doi:10.18260/1-2--11469

Team Development In A Preliminary Year Design Class

2020· article· en· W2732347781 on OpenAlexaffabout
Matt Frye, Myron Britton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSession (web analytics)ResidenceClass (philosophy)Work (physics)Team teachingEngineering educationFirst classTeam managementMedical educationMathematics educationPsychologyComputer scienceEngineering managementEngineeringTeaching methodSociologyKnowledge managementArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

This paper describes the approach taken to team development in a preliminary year engineering design class at the University of Manitoba.With this approach, student design teams assume a significant level of responsibility for the conduct of all components of the course.The course management system that emphasizes individual and collective responsibilities and formal training in team development is discussed.Engineering Design is a required Preliminary Year course for all Engineering students at the University of Manitoba.More than 1200 students have taken this course since its introduction in January 1999.Classes as large as 100 students attend one lecture and one three-hour laboratory period per week.Laboratory work is Design Team based, so effective operation of the teams is critical if we are to meet our teaching goals.Team membership is assigned by the professor.A maximum of 20 Design Teams are created per section, each with a target size of five students.Initially no Design Team will have fewer than four or more than six members.Team size can decrease during the term because of withdrawals, but in no case will a team continue with fewer that three members.Only twice since the initiation of the course has it been necessary to deal with the integration of depleted Design Teams.The stated purpose of the course is to provide students with an introduction to the engineering design process.Design realities such as assumption, approximation, uncertainty, and compromise are introduced through open-ended, student-controlled, laboratory projects.Individual and collective responsibilities are emphasised through the course management system that has been developed.

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)0.005
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0050.001
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.004

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 head0.041
GPT teacher head0.241
Teacher spread0.201 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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