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Enregistrement W4225419617 · doi:10.1096/fasebj.2022.36.s1.r6261

An Anatomy and Physiology Course for Engineers Involving the “Design” of Integrated, Anatomically Unique Creatures

2022· article· en· W4225419617 sur OpenAlexaff
Jenna Usprech, Claudia Krebs

Notice bibliographique

RevueThe FASEB Journal · 2022
Typearticle
Langueen
DomaineEngineering
ThématiqueBiomedical and Engineering Education
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésContext (archaeology)CreaturesAnatomyHuman bodyPhysiologyComputer scienceBiologyNatural (archaeology)

Résumé

récupéré en direct d'OpenAlex

Overview This abstract focuses on a distinctive group project in an introductory anatomy and physiology course for upper‐year undergraduate and graduate engineering students. Background Engineering students in the traditional fields of mechanical, chemical and electrical engineering solve problems and analyze systems by drawing upon fundamental knowledge in chemistry or physics, where processes tend to be well‐defined and well‐characterized. In the field of biology, processes may be characterized, but have a greater degree of variance and a nomenclature unfamiliar to many engineers. Learning the fundamentals of anatomy and physiology in the context of systems to understand, characterize, and design, can be helpful to engineers who lack a background in biology. Upper year engineers are also experienced working in groups as many courses require collaboration in design and would benefit from group work as it relates to anatomy and physiology. Objective and hypothesis The objective of this course, and its core project, was to enable engineers to engage with anatomy and physiology content in a way that promoted their learning of the material, while utilizing their unique analytical approach and leveraging their advanced design and project management skills. We hypothesized that students would gain a deep understanding of anatomy and physiology through the design of a creature – building on their engineering skills and integrating their anatomy knowledge across the 11 human body systems. Project description The centerpiece of the project involved defining a creature that could survive in an environment of the students’ choosing. Each project group chose a body system, and collaborated with adjacent body systems to create one cohesive, integrated organism over the term. The project was executed in groups of 4‐5 students, including at least one graduate student. Deliverables consisted of a presentation, visual representation, written report, and individual reflection. All design choices needed to be scientifically consistent with anatomical and physiological systems. The visual representation could be a physical object, digital rendering, or drawing – anything that assisted in the understanding of the system and creature. Students were asked to consider the following key questions in order to promote the discovery of needs and requirements by the engineering students (part of the engineering design process). (1) What does the environment that the creature lives in look like? (2) What does a complex living organism with body systems look like in this environment? (3) What adaptations are needed by the creature for the environment that they live in? (4) How do the various body systems interact with each other? Project impact Since the project was one of fantasy, rooted in logical and scientifically sound justification, this allowed the engineers to think beyond the technical constraints that are usually imposed on them. Many groups were inspired by a variety of organisms and engineering systems. In their individual reflections, many students described the project to be creative, humorous, and challenging. They also described that the project enhanced their understanding of body systems and further developed their skills in coordination and communication (owing to coordination between groups when working on the integrated organism). Overall, this project provided an effective learning opportunity for the students and a memorable way to interact with this previously unfamiliar topic.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
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: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,051
Score d'incertitude au seuil0,171

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0020,001
Communication savante0,0020,002
Science ouverte0,0010,004
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0510,021

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 Opus0,008
Tête enseignante GPT0,230
Écart entre enseignants0,222 · 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
GenreAutre

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
Publié2022
Routes d'admission1
Résumé présentoui

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