Modeling the Glucose Insulin System
Audience
Class size is approximately 40 students. This class is offered Fall, Winter, Spring. Expected deployment term Spring ‘22.
Given this is an introduction to scientific computing, experience with coding and data science is not required and it is expected that the range of prior exposure among students will vary. Familiarity with Calculus is expected from every student.
Other applicable courses that may benefit from this module:
Both the long and short assignments contain the necessary information to provide exposure to differential equations and finding error by method of least squares. The layout may be useful for other introductory courses that require some prior math knowledge. These modules not only enhance the course’s material but also introduce other material that students will face in advanced studies.
Project Summary
Primary Objective
The purpose of this module is to expose students to data science and its real life application, while reinforcing MATLAB functionalities learned in class. Through the short assignment, students are taught how to approach single order differential equations via MATLAB. After initial exposure, the long assignment reinforces their understanding through a rigorous real-life application to emphasize the importance of data science, and applications of Euler’s method, Least Squares, and MATLAB use.
Goals
Establish basic understanding of ODEs and MATLAB functionalities
Identify differential equation model of a real-world system, and propose leading questions to students that practices their analysis of graphical behaviors in relation to equations.
Create a set of assignments that increases in complexity and adds data science principles to fortify understanding
Content Outline
Short Assignment
Three questions introducing the student to ODEs in Matlab.
Long Assignment
Modeling the Glucose Insulin System in Matlab with Euler’s Method and exploring the model by optimizing one parameter for a given set of data using the least squares method.
For more information email: difuse-pi-group@dartmouth.edu
