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Enregistrement W3003105828 · doi:10.24908/pceea.vi0.13708

Arduino-based Sensor Device – An Engineering Physics Second-year Design Project within the Engineering Design and Practice Sequence (EDPS) of the Queen’s Engineering Professional Spine

2019· article· en· W3003105828 sur OpenAlexaffvenueabout
R. Knobel, Mark Chen, L. Clapham

Notice bibliographique

RevueProceedings of the Canadian Engineering Education Association (CEEA) · 2019
Typearticle
Langueen
DomaineEngineering
ThématiqueExperimental Learning in Engineering
Établissements canadiensQueen's University
Organismes subventionnairesnon disponible
Mots-clésAccreditationEngineering design processScope (computer science)EngineeringEngineering educationProcess (computing)Engineering managementEngineering ethicsMedical educationComputer scienceMedicineMechanical engineering

Résumé

récupéré en direct d'OpenAlex

In 2011, Queen’s Engineering began rollout of its "Engineering Design and Practice Sequence (EDPS)". The EDPS is a "professional spine" sequence of courses over four years, meant to address and incorporate into all of its engineering programs the majority of the 12 Graduate attributes required by the Canadian Engineering Accreditation Board (CEAB). In year 1, the first EDPS course – Engineering Practice I - introduces students to engineering design and problem solving, but with little formal instruction in the design process and engineering tools. Formal instruction in these aspects comes in second year, in Engineering Design and Practice II (course number APSC200). Finally, in third and fourth year, students undertake significant design projects in their discipline. The second-year version of the professional spine, APSC200, is a one-term course taken by all students. This begins with a 6-week Faculty-wide course module, followed by a 6-week program-specific module. In the first Faculty-wide segment, students learn the design process – problem definition and scope, idea generation and broadening tools, decision-making tools, economic analysis, stakeholders, risk, and safety. Students are exposed to the necessity of formal design techniques via a zero-level "P0" project, and taught these techniques during a more extensive P1 project. The second 6 weeks of APSC200 involves a discipline-specific project (P2) in which the student teams practice the skills introduced in the earlier portion of the course while working through a design project chosen to emphasize the skills of their program. This paper focusses on the development and implementation of the P2 project for students in the Queen’s Engineering Physics program. The goal of this project is to introduce discipline-specific tools and techniques, to excite students in their chosen engineering discipline, and to put into practice the formal design techniques introduced earlier. The P2 project developed for Engineering Physics was entitled a "Compact Environmental Monitoring Station". The premise was that the Ontario Ministry of the Environment (MOE) issued an RFP for small, cheap sensor devices that could be provided to every Ontario household, and set up to "crowdsource" environmental data for the MOE. Student teams were required to research and justify which environmental parameters would be appropriate for their monitoring device, decide on parameters to monitor, design the device, and build a working prototype of the device. The device specifications required the use of an Arduino-based platform, interfacing the chosen sensor(s) to a laptop computer using MatLab. Since only some students were familiar with Arduinos and MatLab, two "just in time" workshops were delivered on these topics, using a "flipped lab" approach. For the prototype design and build, students had only 4 weeks and a budget of $100. Arduino boards and some basic sensors were supplied, with students able to source and purchase other components within their budget. The prototype-build provided the students with a valuable hands-on experience and also helped them to fully appreciate unexpected practical design constraints. Given the short timeframe (4-weeks) for the design and build, prototypes were very impressive, with many including solar power or rechargeable batteries, Bluetooth connectivity, 3-D printed packaging, IPhone or Android apps, as well as calibration functions. This paper will summarize the development of this Engineering Physics P2 module, and will report on the first year of offering it in its current format.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,050

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0150,004

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 Opus0,014
Tête enseignante GPT0,238
Écart entre enseignants0,225 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
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

Citations0
Publié2019
Routes d'admission3
Résumé présentoui

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Même revueProceedings of the Canadian Engineering Education Association (CEEA)Même sujetExperimental Learning in EngineeringTravaux en français237 207