MétaCan
Menu
Retour à la cohorte
Enregistrement W2618689334 · doi:10.18260/1-2--10136

Impacts Of The Nserc Chair In Design Engineering At The University Of Manitoba

2020· article· en· W2618689334 sur OpenAlexaffabout
Myron Britton

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEngineering
ThématiqueBiomedical and Engineering Education
Établissements canadiensUniversity of Manitoba
Organismes subventionnairesnon disponible
Mots-clésBrainstormingTrilogyClass (philosophy)Computer scienceCurriculumEngineering educationEngineering managementEngineering design processWork (physics)Mathematics educationEngineeringPsychologyPedagogyMechanical engineeringArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Main Menu design/build projects. Student response has been positive, and we believe these courses provide a sound base upon which to develop design focussed departmental curricula. That same year, in the Department of Biosystems Engineering, two design courses (Introduction to Biosystems Engineering and Design Project) were integrated with a third year class (Design Methods for Machines for Biosystems) to form what we have come to call a Design Trilogy. All three courses are taught in the same time slot and the laboratory sessions are held at the same time, in the same “Design Office” space. Each class retains its own character (see www.umanitoba.ca/faculties and click on Biosystems Engineering under the Faculty of Engineering) but all student design teams are encouraged to work together toward the solution of their increasingly complex industry based design projects. Joint brainstorming sessions and informal discussions lead to significant levels of interaction. All design teams are required to “contract” with students registered in a Trilogy course other than their own to obtain services to complement their own team skills. The objective is to create a simulated design office situation in which students teach one another on a need-to-know basis. The final output from each design team is a written and an oral report, as well as an “invoice” for the work completed. Experience gained in the Trilogy prior to submitting the Design Chair proposal led us to believe that this approach could be applied, with modifications, to all of the programs offered in the Faculty. In July 1999, Dr. Doug Ruth was appointed Dean of the Faculty of Engineering at the University of Manitoba. One of his stated objectives as Dean was to make the University of Manitoba a recognized leader in design education. To provide the necessary Faculty wide support for this goal, he created a new position, Associate Dean (Design Education). In July 2000, the author was appointed to this position. A proposal to NSERC for funding under their Design Engineering Chair program was developed as a means of supplementing the resources needed to reach Dean Ruth’s goal. The University of Manitoba Chair - the proposal The Design Engineering initiative proposed for the University of Manitoba was to have a Faculty wide focus. It responded to all four NSERC targets; training, design and development, collaboration and promotion. It had a proposed schedule, but it was recognized as a design project in itself, and the uncontrollable elements that are characteristic of the design process were recognized as a delivery constraint. Specific components of the proposal included: 1. Improving the design experience base within the faculty. To accomplish this, it was proposed to appoint Engineers-in-Residence. These persons would be drawn from one of two pools of talent within the engineering profession. Recently retired engineers would be appointed as E-i-Rs and located at the university during the academic year. Other engineers would be seconded from industry to provide specific current input during design course laboratory periods. The goal was to appoint at least dozen retired E-i-Rs (two per program) and as many seconded E-i-Rs within the first two years of the program. Proceedings of the 2002 American Society for Engineering Education Annual Conference & Exposition Copyright © 2002, American Society for Engineering Education Main Menu

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,347
Score d'incertitude au seuil0,128

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,151
Écart entre enseignants0,139 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission2
Résumé présentoui

Explorer davantage

Même sujetBiomedical and Engineering EducationTravaux en français237 207