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2015-Winkel, Brian - Sample SIMIODE Course Syllabus
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24 Jun 2015 | Contributor(s): Brian Winkel
Sample SIMIODE Course Syllabus This syllabus is designed for a 15 week, 3 credit hour course using experimentation, modeling, and technology to lead students through a traditional sequence of differential equations topics. All...
SIMIODE RESOURCE GUIDE
24 Jun 2015 | Sample Syllabi and Course Reflections | Contributor(s): Brian Winkel
SIMIODE Resource Guide for Course Materials is fashioned after a traditional textbook's Table of Content. To access the Guide simply click on the Download the PDF Black Box to the Upper Right. This is a listing of all of SIMIODE's Modeling Scenarios and Text Narratives. ...
2016-Zullo, Holly - Differential Equations at Westminster College Personal Account
21 Sep 2016 | Sample Syllabi and Course Reflections | Contributor(s): Holly Zullo
This paper describes the author's experiences teaching differential equations with a strong modeling component at a small liberal arts college. The course structure and incorporation of modeling are discussed, as well as challenges and rewards associated with this approach.
2016-Yagodich, Dina - Reflection - Slowly Introducing Modeling First into Differential Equations Classes
24 Sep 2016 | Sample Syllabi and Course Reflections | Contributor(s): Dina Yagodich
2016-Farley, Rosemary - Differential Equations at Manhattan College: A Personal Account
24 Sep 2016 | Sample Syllabi and Course Reflections | Contributor(s): Rosemary Carroll Farley
This is my personal account of how the SIMIODE modeling first approach was adapted for use in my classes at Manhattan College. The comments here pertain to the 200-level differential equations course that I taught in Spring 2016. This course is required of every student in the...
2018-Banerjee,Soumya and Joyeeta Ghose - A Teaching Resource for Complex Systems, Machine Learning and Computational Biology
05 Jan 2018 | Sample Syllabi and Course Reflections | Contributor(s): Soumya Banerjee, Joyeeta Ghose
This work presents a collection of teaching materials related to complex systems, machinelearning, computational biology and computational immunology.