PyConZA 2014: "Ipython as a tool for teaching and learning" by Laura Richter

The ipython environment lends itself to teaching and learning: immediate feedback, flexible visualisation, easy access to docstrings and ability to explore modules.

With development of the ipython notebook, this is taken a step further, by providing browser-based access to an ipython environment with the ability to share notebooks with others, embed output products and annotate code.

I will present some experience of using ipython as a teaching tool in a tertiary teaching environment in Radio Astronomy courses in Windhoek, Nairobi and Cape Town.

Transcript

1. • Overview • etc Overview Ipython for Teaching and Learning Laura Richter
2. Context Kenya Namibia South Africa PyconZA, Johannesburg, October 2014
3. Kenya and Namibia JEDI* workshop, ~12 third year plus students *Joint Exchange and Development Initiative, jedi.saao.ac.za, cosmology.org.za/ml-jedi-2 PyConZA, Johannesburg, October 2014
4. Ipython: pragmatics • Python from the ground up • Focus on Astrophysics related tools • Physical handout to follow • Group work • Use of ipython help • Including errors PyConZA, Johannesburg, October 2014
5. Ipython PyConZA, Johannesburg, October 2014
6. Ipython: evaluation PyconZA, Johannesburg, October 2014 Wins • Ipython help • Interactive • Feedback to students • Debugging for tutors • “Discovery through experimentation” Challenges • Student linux proficiency • Standardisation/versioning
7. South Africa SKA South Africa tutorials* PyConZA, Johannesburg, October 2014 *github.com/ska-sa/tutorials
8. South Africa *National Astrophysics and Space Science Programme, star.ac.za NASSP* course, 21 fourth Astrophysics students PyConZA, Johannesburg, October 2014
9. Ipython notebook: emphasis PyconZA, Johannesburg, October 2014 python content python tutorial content tutorial content/python lab interactive lecture notes packaged content tutorial
10. Ipython notebook: pragmatics • Simplest case • Challenges • Linux proficiency • Standardisation/versioning PyconZA, Johannesburg, October 2014
11. • github • nbviewer • cloud computing • runipy • nbconvert PyconZA, Johannesburg, October 2014 Ipython notebook tools
12. Ipython notebook tools ipython notebook + github + nbviewer = magic PyconZA, Johannesburg, October 2014
13. nbviewer demo nbviewer.ipython.org ska-sa/tutorials PyconZA, Johannesburg, October 2014
14. Ipython notebook tools ipython notebook + github + local server / AWS EC2 = magic magic PyconZA, Johannesburg, October 2014
15. AWS EC2 SKA SA tutorial demo PyconZA, Johannesburg, October 2014
16. Ipython notebook tools ipython notebook + github + sagemath cloud = living the dream* PyConZA, Johannesburg, October 2014
17. sagemath cloud demo cloud.sagemath.com github.com/ska-sa/tutorials PyconZA, Johannesburg, October 2014
18. Ipython notebook: evaluation PyConZA, Johannesburg, October 2014 Challenges • Insufficient introductory & setup time • Standardisation/versioning
19. Wins • The ipython wins, plus: • Browser based, cross-platform • Everything in one context • Less necessity for linux expertise • Convenient for assignments • Markdown and LaTeX PyconZA, Johannesburg, October 2014 Ipython notebook: evaluation
20. PyConZA, Johannesburg, October 2014 “It's SO MUCH FASTER to do an assignment in iPython.. IF you can get the code right.” “I got comfortable with python, ipython and at the same time got some work done.” “advantage was that it is fun to use it” “the notebooks are especially cool” “The fact that you can change parameters and see how that affects the output is very useful.” “ability and flexibility to play around with the codes and thus the subject content” “The Fourier transforms make much more sense when you can see it in front of you, and play around with it;” “it is nice that it breaks the code up into pieces. So if there is an error you can identified the error more easily.”
21. Dream with me, for a moment. PyConZA, Johannesburg, October 2014