Teaching and Learning with Jupyter
“Teaching and Learning with Jupyter” delves into the educational applications of Jupyter notebooks, exploring their role in enhancing the teaching and learning experience. The document discusses how Jupyter notebooks can be utilized as interactive tools for coding, data analysis, and visualization, fostering a more engaging and hands-on learning environment. It also highlights the versatility of Jupyter notebooks in various educational settings, from classrooms to online courses. By leveraging the functionalities of Jupyter notebooks, educators can effectively convey complex concepts, promote active learning, and empower students to explore and experiment with coding and data analysis.
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Chapter 7 Usage case studies
Contributors to this chapter: you may increase adoption by new users if you integrate information about some of the following into your case: Demonstrate that you can increase students’ ability to: En...
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Chapter 2 Why we use Jupyter notebooks
2.1 Why do we use Jupyter? As teachers we are responsible for many activities, including creating lessons, lectures, courses, assignments, and supportive environments; encouraging engagement and perfo...
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Chapter 6 Getting your class going with Jupyter
You have several options on how to get Jupyter notebooks to your students. You can ask students to install Jupyter on their own computers, install Jupyter on lab computers for students to use, or run ...
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Chapter 5 Jupyter Notebook ecosystem
5.1 Language support: kernels The Jupyter system supports over 100 programming languages (called “kernels” in the Jupyter ecosystem) including Python, Java, R, Julia, Matlab, Octave, Scheme, Processin...
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Lorena A. Barba, Lecia J. Barker, Douglas S. Blank, Jed Brown, Allen B. Downey, Timothy George, Lindsey J. Heagy, Kyle T. Mandli, Jason K. Moore, David Lippert, Kyle E. Niemeyer, Ryan R. Watkins, Rich...
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Chapter 3 Notebooks in teaching and learning
Jupyter notebooks are a valuable tool for teachers, but their value can only be leveraged if you apply them correctly within the context of your course. In this chapter, you will learn how teachers ca...
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Chapter 9 Glossary
Anaconda : a free, open-source package manager, environment manager, Python distribution, and collection of over 1,500+ open source packages including and also Jupyter. https://www.anaconda.com/what-i...
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Chapter 8 About the authors
8.1 Project lead Lorena A. Barba George Washington University labarba@email.gwu.edu @LorenaABarba Lorena A. Barba is Associate Professor of Mechanical and Aerospace Engineering at the George Washingto...
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References
Barba, L., & Forsyth, G. (2018). CFD Python: The 12 steps to Navier–Stokes equations. Journal of Open Source Education , 1 (9), 21. https://doi.org/10.21105/jose.00021 Brenner, S. C., & Scott, L. R. (...
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Chapter 4 A catalogue of pedagogical patterns
4.1 Introduction In this chapter, we present a collection of patterns that are particularly aligned with teaching and learning with Jupyter. Each pattern is targeted at specific learning goals, audien...
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Lorena A. Barba, Lecia J. Barker, Douglas S. Blank, Jed Brown, Allen B. Downey, Timothy George, Lindsey J. Heagy, Kyle T. Mandli, Jason K. Moore, David Lippert, Kyle E. Niemeyer, Ryan R. Watkins, Rich...
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