An Anatomy and Physiology Course for Engineers Involving the “Design” of Integrated, Anatomically Unique Creatures
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.051 | 0.021 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".