An introduction to Jupyter notebooks and the Noteable service
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A presentation at Connect More in Scotland, 4 June 2019. Speaker: James Slack, e-learning officer for computational notebooks DLAM, University of Edinburgh. Over the past year, the University of Edinburgh has been developing and piloting the Noteable service to help supporting programming and computational teaching. The Noteable services provide cloud access to Jupyter notebooks; live editable documents that allow you to run code whilst also containing text, data tables and other rich media items such as images and videos. Jupyter allows students to quickly get hands-on with programming content without having to brave an intimidating IDE (integrated development environment) or grapple with the terminal. This session will give an overview of what Jupyter notebooks are and why they are becoming popular for introductory programming courses. There'll be a discussion around how Jupyter has been adopted at the University of Edinburgh and how the Noteable service has been developed to support computational education.
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An introduction to Jupyter notebooks and the Noteable service
- 1. Edinburgh – 4 June Jupyter and Noteable at the University of Edinburgh James Slack & Núria Ruiz
- 2. "The Noteable service is a cloud based platform providing access to Jupyter notebooks online. Noteable provides a central storage space to store and run Jupyter notebooks in a variety of programming languages" Service Description
- 3. •Computational notebook •Multi-language support •Open Source •https://jupyter.org/ What are Jupyter notebooks?
- 4. •Able to provide context alongside live code •Can create visualisations, data tables, embed media and work with remote data sets •Not as daunting as Terminal or IDE •Great for introductions to new students Why use Jupyter?
- 5. How to access? Local Install Jupyterhub
- 6. CFD – Lorena Barba (GWU) Data 8 - Berkeley
- 8. •Central service supported by EDINA •Learn integration •Supporting teaching use case across University Why Noteable?
- 9. • LTI integration with all leading VLEs • Automatic grading across multiple courses and markers with nbgrader • Supporting infrastructure for course file management and identity management • Trialling AWS Cloud set-up to support more users and more intense processing Built for education
- 10. •>600 users •6 different Schools •Alternative use for training •Benchmarking service against market Noteable Pilot – Semester 1
- 11. Semester 1 Case Study •Python programming and data visualisation to 1st year biologists •Previously used IDLE on supported desktops •Used for: Class work, Assignments, Workshops •Students analyse an assignment dataset and submit a Jupyter notebook of their analysis. Quantitative Skills for Biologists 1 – 220 Students
- 12. Semester 1 Case Study continued •Instructors like the system • Able to cover more material • All students work in same environments, less set up • Able to expand class sizes and be more flexible in where classes held •Students like the system •Available through the browser •No technical barrier to access •Students can use any computer and OS and access the server from anywhere •Student course approval ratings increased substantially when we moved to Jupyterhub/Noteable. Quantitative Skills for Biologists 1 – 220 Students
- 13. Semester 1 Case Study •Learn basics of programming in Python •Work through notebooks together with instructor or at own pace in labs •Previously used a text editor and then cmd line Python •Some students were able to work at home if they had Unix machines, all others only had access in labs Introduction to Cognitive Science – 90 students
- 14. Semester 1 Case Study continued •Now all students able to access materials from anywhere •Student Qoutes: •- "liked the interface" - "doesn't make programming daunting" - "encapsulated / user-friendly / play around with it" - "more intuitive than Terminal" Introduction to Cognitive Science – 90 students
- 15. Ongoing Case Study •Intro to Python course open to all staff and students •Half day course with 20 participants •90 on waiting list for first event •Range of experience amongst attendees •Instructor led walkthrough of notebooks with exercises Digital Skills Programme – Introduction to Python
- 16. •>500 users in 4 schools •nbgrader implementation •First round of feedback •Case studies ongoing Noteable Pilot – Semester 2
- 17. Feedback
- 18. •User case studies •Creation of new content/supporting new users •Working with those who "Don't code" •City Region Deal •Edinburgh Futures Institute What's next
- 19. •3-year pilot •Expand Open Education •Deliver new digital pedagogy at scale •Use automated technologies to support quality at scale DLAS – Digital Learning at Scale Future Use Cases
- 20. • Build and maintain tools to make it easier for institutions to adopt • Highlight and showcase how Jupyter can be used in education • Hosted Jupyter Community event • Involved with Community Calls (Last Tuesday each month) Community Engagement
- 21. •Supporting trials at other HE institutions •Noteable for research •Notebooks for schools and colleges •Get in touch for trial access - nuria.ruiz@ed.ac.uk Get involved
- 22. customerservices@jisc.ac.uk jisc.ac.uk Thank you Jupyter and Noteable at the University of Edinburgh james.slack@ed.ac.uk nuria.ruiz@ed.ac.uk James Slack & Núria Ruiz
Notas do Editor
- So firstly, I want to go over Noteable, what is Noteable. Well here is our service definition and as you can see the service provides access to Jupyter notebooks. So here is where talking about Noteable can sometimes be difficult, because to talk about Noteable we need to talk about Jupyter notebooks first.
- The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Originally started out life as the IPython project but quickly took on new life as Jupyter. These notebooks allow you to explore and interact with code in a variety of languages, originally this contained Julia Python and R hence the name but this has now expanded to enable you to work in the Jupyter environment in over a 100 different languages. This is all open source so you can access all of the materials, join the community and contribute to the project. If youd like to know more or want to start getting involved you can head to jupyter.org to find out more.
- So as you can see the benefits from this are the ability to provide context alongside your code that students or colleagues interact with that helps you to build computational narratives. These can become incredibly rich documents as you can also create and interact with data tables and create visualisations of your findings. From students we've also found that this is a lot less intimidating of an environment, many students are put off by the terminal or a traditional IDE and there is a fear of coding that people believe they won't be able to interact or understand. Being able to lower the barrier and make the experience less daunting mean that this is a great platform for introducing concepts quickly and allowing students to start coding.
- Local install – great for exploring concepts on your own but need to manage your libraries and language kernel. Good for exploration but cumbersome for classes. Jupyterhub – cloud service that provides access to notebooks, this service bsed infrastructure means that you can access notebooks without anyneed for installation and also you can pre-configure these environments to contain certain packages. Important as no need to install jupyter but also no need to install any required packages, all students and instructors work in a copy of the same evironment, which means as an instructor if it works for you it will work for your students. Distance learning, creating OERs, dealing with large classes or one of workshops where you don't have time to help everybody get setup and want to maximise the time spent learning.
- Lorena Barba – OER example Data8 Course, huge class size with many people being able to interact with material from wherever they are on whatever setup.
- Hand over to Núria
- Central service, means schools do no have to support individual environments, reducing workload if many schools are individually support infrastructure. Also means that we are able to put more time into development work to add new features, one of these is learn integration we integrate with learn via LTI which means that information about the student is passed across to noteable so we know what courses that student is enrolled on and also means they don't have to login seperately. This gets important later when we start dealing with assessments and grades. Also means schools without the ability or resources to set this up are not left behind.
- Central service, means schools do no have to support individual environments, reducing workload if many schools are individually support infrastructure. Also means that we are able to put more time into development work to add new features, one of these is learn integration we integrate with learn via LTI which means that information about the student is passed across to noteable so we know what courses that student is enrolled on and also means they don't have to login seperately. This gets important later when we start dealing with assessments and grades. Also means schools without the ability or resources to set this up are not left behind.
- Informatics, mathematics, sps, ppls, biological sciences and ECA. Support case for central service supporting many schools Also used as part of digi skills programme Is this the best service for us, what could be better.
- We wanted to give you more of an overview of how our users are making use of noteable, what their use cases and circumstances are and why they have decided to move to Jupyter and Noteable
- Front-loaded programming teaching, still high numbers Less daunting than IDE Essential to smooth running of the course
- 100,000 students with data skills so there is a real emphasis on supporting these kind of platform both within the University