JupyterHub: Interactive Learning at Scale

Presented at PyCon 2017 Education Summit. May 2017.

Transcript

1. 
 JupyterHub Learning at Scale Carol Willing Cal Poly SLO, Project Jupyter Education Summit May 18, 2017 PyCon 2017 @willingcarol
2. Thank You
3. Agenda • Learning • Jupyter Notebooks and JupyterHub • Principles of learning • Scaling with JupyterHub • Next steps
4. Learning Credit: Karen Rustad Tolva
5. Learning results from what a student does and thinks and only what the student does and thinks. Herbert A. Simon
6. The teacher can advance learning only by influencing what the student does to learn. Herbert A. Simon
7. Jupyter Notebooks and JupyterHub
8. Joy of exploration
9. Jupyter notebooks engage learners
10. A single user Jupyter notebook server Python R Julia
11. JupyterHub
12. 
 • Manages authentication • Spawns single-user notebook servers on-demand • Gives each user a complete notebook server What does the Hub do?
13. Principles of Learning
14. Motivate Curiosity Engage Connect Wow Develop mastery Motivate Apply knowledge
15. Develop mastery Motivate Apply knowledge Develop mastery What if... Iterative Attempts Failure Persistence Interactive Feedback
16. Develop mastery Motivate Apply knowledge Apply knowledge Domains Experience Cross-culture Complex problems
17. Scaling with JupyterHub
18. Motivate 1 • Work with student interests https://nbviewer.jupyter.org/ • Wow with possibilities https://github.com/jupyter/jupyter/wiki/A-gallery- of-interesting-Jupyter-Notebooks • Get them started with tmpnb and binder https://try.jupyter.org http://mybinder.org/ Gallery of Interesting Notebooks nbviewer Project Jupyter community
19. • Start with a proven curriculum http://pyvideo.org/pycon-us-2013/a-hands-on- introduction-to-python-for-beginning-p.html • Hands on to engage students • Takeaway notebooks reduce student stress https://github.com/pythonsd/intro-to- python Motivate 2 Intro to Python San Diego Python
20. • Exploration and experimentation http://pyvideo.org/scipy-2016/labs-in-the-wild-teaching- signal-processing-using-wearables-jupyter-notebooks- scipy-2016.html • Physical media with wearables and electronics • Real world, self-directed projects Motivate 3 Teaching signal processing using Wearables and Jupyter Notebooks Demba Ba
21. • Feedback and communication with students using nbgrader http://kristenthyng.com/blog/2016/09/07/ jupyterhub+nbgrader/ • Progression to complex examples and tasks https://github.com/kthyng/ python4geosciences Develop mastery 1 Python for Geosciences Kristen Thyng
22. Excellent resource on using tmpnb and JupyterHub for teaching http://jupyter.rocks/ https://github.com/tanyaschlusser/Jupyter-with-R Develop mastery 2 Using Jupyter notebooks with R in the classroom Tanya Schlusser
23. Develop mastery 3 Cal Poly SLO Data Science 301 Brian Granger • Intensive data science course for undergraduates https://github.com/calpolydatascience/data301 • Ansible deployment https://github.com/jupyterhub/jupyterhub-deploy- teaching • Research project and student interns http://www.calpolynews.calpoly.edu/news_releases/2015/ July/jupyter.html
24. Apply knowledge 1 Berkeley Data Science Data8 UC Berkeley http://denero.org/data-8-in-spring-2017.html https://github.com/data-8/jupyterhub-k8s http://data8.org/ http://data.berkeley.edu/ http://data.berkeley.edu/about/videos •Campus wide curriculum •Cross-discipline •Kubernetes deployment of JupyterHub • Zero to JupyterHub with Kubernetes https://zero-to-jupyterhub.readthedocs.io
25. Apply knowledge 2 https://github.com/jupyterlab/jupyterlab JupyterLab alpha
26. Next steps • Join Jupyter in Education community • Try no installation needed solutions • Try tmpnb with a workshop • Offer a course with JupyterHub • Scale your curriculum to other courses
27. Resources JupyterHub Read The Docs JupyterHub for teaching deployment Zero to JupyterHub tmpnb binder Microsoft, Continuum, Sage Math Cloud JupyterHub tutorial
29. Thank you!
30. Questions? • Steering Council, Project Jupyter • Software Engineer, Cal Poly SLO • Director, Python Software Foundation • Geek in Residence, Fab Lab San Diego Carol Willing @willingcarol
31. • Kristen Thyng • San Diego Python • UC Berkeley Data Science • Cal Poly SLO • Tanya Schlusser • Demba Ba • Project Jupyter team and community Attributions and recognition
32. 
 JupyterHub Learning at Scale Carol Willing, Cal Poly Education Summit May 18, 2017 PyCon 2017 @willingcarol