1. Paul Kassebaum, Ph.D. 24 October 2016
Teaching with MATLAB®
Paul Kassebaum, Ph.D.
24 October 2016

2. Overview
Content: change in content methodologies, not just organization.
Pedagogy: “teaching the algorithms” VS “teaching the tools”; connecting analytic and algorithmic model building.
Structure: one special course / parallel majors / full-integration.
Implementation: enlisting stakeholders; targeting courses.
Materials: development, validation, testing, archiving, distributing.
Faculty development: change thinking, not just skills; engaging nonprogrammers; social learning.
Support and sustainability: going beyond material development and faculty enlistment. What’s the business model?
Norman Chonacky and David Winch. Integrating computation into the undergraduate curriculum: A vision and guidelines for future developments. 6 January DOI: /

3. Content
Change in the organization of content topics will not suffice where change in the content methodologies is the goal.
Reusability of methods, skills sets, and topics for use in other courses and/or disciplines most significant criteria for inclusion in revised content.
Euler’s method for solving difference equations is fundamental, clear connection to analytic methods, motivates other solution methods and numerical analysis, widely applicable to many physical systems.
MATLAB documentation on ODEs
MATLAB example on differential equations
MATLAB Answers discussion on Euler method without ode45
YouTube video on Euler’s method with MATLAB
PDF on implementing Euler’s method in MATLAB

4. Pedagogy “Teaching the algorithms” vs “teaching the tools”.
Similar to “computational science” vs “scientific computing”.
Both is better than one alone.
Connections between analytic and algorithmic methods of forming models.

5. Pedagogy: teaching the tools
MATLAB Academy
Key features
On-demand access
Supports different learning styles: auditory, visual, and kinesthetic
1 free (MATLAB Onramp), and 5 paid courses
Task oriented lessons that include best practices and typical workflows
Benefits
Establish baseline skills for all users
Save time on teaching MATLAB
Access
Purchase individually
Add-on to TAH license for campus-wide access for all

6. Pedagogy: the value of computational thinking
Teaching with MATLAB lets students
run interactive simulations during lessons;
solve problems numerically or analytically;
extract, analyze and visualize experimental data;
model and simulate phenomena to build intuition;
express and simulate equations to test hypotheses;
simulate analytical models to test predictions.

7. Pedagogy: Analytic to Numeric to Modeling

9. Pedagogy: building intuition visualizing and asking what ifs

10. Pedagogy: building intuition visualizing and asking what ifs

11. Pedagogy: building intuition visualizing and asking what ifs

12. Pedagogy: building intuition visualizing and asking what ifs

13. Structure
One special course and/or mods to some or all of traditional courses;
Parallel tracks for conventional and computational majors;
Completely restructured, fully integrated curricula.

14. Structure
Learn more

15. Implementation Equipping your students with MATLAB
Cooperation and collaboration of stakeholders
Deciding what courses to address and in what order

16. Implementation: access to MATLAB (for students)
MATLAB Onramp, free and online
MATLAB Mobile, freemium on phone/tablet
MATLAB Student, low-cost while enrolled
MATLAB Home, low-cost after graduation
MATLAB Online, site license, access from anywhere, no install needed

17. Implementation
Build your Faculty Matrix
Slide by Gregory Goins

18. Implementation
Reach out to MathWorks’ Technical Evangelists

19. Materials Development Validation & Testing Archiving & Distributing
Live scripts
App developer
Hardware support & Internet of Things
GitHub integration
Validation & Testing
Cody Courseware
Archiving & Distributing
SERC
PICUP
File Exchange & Add-on Explorer

20. Materials: development, Live Editor
Open
SERC example: Teaching Quantum Mechanics with MATLAB

21. Materials: development, MATLAB App Designer

22. Materials: development, Hardware Support & IoT
Arduino, iPhone, Android, Raspberry Pi, LEGO, and more
Internet of Things cloud service: ThingSpeak

23. Materials: development, Hardware Support

24. Materials: development, Internet of Things

25. Materials: development MATLAB GitHub integration
Grow project contact list
Make announcements & encourage participation
Listen to feedback
Rewrite, reuse, review code & doc
Release early, release often
Typical development required is 2 person-weeks for a preliminary version of a single concept module.
Collaborative software development practices offer a way to accelerate material development.

26. Materials: development, Free books: why not?

27. Materials: test and validate
Cody Coursework
Key Features
Online, individualized assignments
Automatic grading
Reporting of scores & attempts
Growing library of off-the-shelf assignments
Benefits
Save instructors’ and TAs’ time
Improve student engagement & outcome
Real-time student performance data
Scalable – support any number of students
Access
Instructors: License association (with SMS)
Students: MathWorks account
Contact

28. Materials: archiving, SERC

29. Materials: archiving, PICUP

30. Can link File Exchange entry to GitHub
File Exchange for users
GitHub for contributors

31. Materials: archiving, Add-on Explorer

32. Materials: archiving, MATLAB Courseware

33. Faculty development
Small fraction of faculty currently does most of the computational work in a typical department.
Need to change minds, not just skills.
Change faculty ways of thinking about how numerical computation fits into science courses and disciplines supported by the sciences,
Find the balance between computer expert and Luddite,
Use the power of social arrangements for faculty learning.

34. Faculty development: getting orientated

35. Faculty development: changing minds with webinars on curricula

36. Faculty development: computational thinking comes in flavors
Ramping up computational thinking through different modalities:
visualizations,
apps,
GUIs that generate scripts,
visual programming (Simulink, SimBiology)
scripts,
functions,
object oriented and beyond.

37. Faculty dev: visualization
NetCDF NCEP-NCAR reanalysis data obtained from IRI/LDEO Climate Data Library (

38. Faculty dev: apps

39. Faculty dev: GUIs that generate code

41. Faculty dev: visual programming
Hand-drawn Schematics
SimElectronics

42. Faculty development: skeleton scripts and functions

43. Faculty development: social learning, MATLAB Central

44. Faculty development: social learning, MATLAB Examples

45. Faculty development: social learning, Hackster.io

46. Support and sustainability
Need to sustain any computational integration agenda beyond generating materials and developing initial faculty interest in using them.
“What’s the business model?”

47. Support and sustainability
Slide by Gregory Goins

48. MathWorks is here to help