Subways and role‐plays: Using analogies to understand matter and energy flow
Bibliographic record
Abstract
The multidimensional and dynamic nature of flow, be it the flow of solutes across membranes or of reagents and energy through chemical pathways, can render these topics difficult to transmit using traditional approaches such as lecture or Powerpoint slides. This study explored the potential of different types of analogies to promote understanding of two examples of flow: secondary active transport of glucose and the metabolic reactions involved in nutrient processing. Secondary active transport was modeled by asking students in an intermediate physiology course to play the roles of solutes and transporters. The classroom was divided into the gut lumen, the intestinal cell, and the interstitial fluid (ISF), and students without roles (the “advisory group”) determined the initial placement of the transporters and solutes based on a textbook figure. The advisers also provided guidance as to the force promoting the movement of each solute at the luminal and basolateral membranes; self‐propelled (facilitated diffusion), moved by a self‐propelled student representing a different solute (secondary active transport), or “pulled across” by the transporter itself (primary active transport). The simulation was then repeated to give more students the opportunity to participate and all students the opportunity to observe. The percentage of students able to identify the nature of the force (ATP or a gradient) driving the flow of each solute increased from 44% before the simulation to 77% after the simulation, and the performance on a relevant exam question (86%) was higher than that of the exam average (76%). Analysis of narrative answers did not reveal any overt misconceptions introduced by the analogy. Flow in metabolic pathways was modeled using a simplified version of the London Underground Film Map, which names subway stops based on nearby filming locations. The map served as the basis for the introductory section of a guided inquiry learning problem set investigating insulin action that was used both in an undergraduate physiology course and in a high school biology course. Once students were comfortable tracking routes through the interlocking and branching subway system, they used the same process to analyze the flow of carbohydrates, proteins, and fats through biochemical pathways in hepatocytes. The final stage asked students to predict which metabolic pathways would be promoted by insulin, both in hepatocytes and in other insulin target sites. While the first two modules effectively engaged both student populations, the final stage proved too difficult for high school students. The upper‐year undergraduates, however, were able to successfully complete the module and performed well on the relevant exam question (75%, compared to a 68% exam average). In conclusion, both analogies appeared to effectively engage students and, depending on the student population, promote conceptual understanding. Because the concept of flow within metabolic pathways is central to a robust understating of physiology, a modified version of the final section will be developed to better accommodate the high school student audience. Support or Funding Information Senate Research Committee, Bishop's University
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".