Jupyter Notebooks: Open Source Computing in Mathematics and the Humanities

ID: 51235 Type: Roundtable
  1. Jacob Koehler, The New School, United States
  2. Soomi Kim, Teachers College, United States

Abstract: In this workshop we will introduce Jupyter notebooks for teaching and learning across the arts and humanities. We demonstrate the notebooks use with R and Python computing languages through classroom tasks that involve ideas from mathematics, design, statistics, computer vision, and animation. Participants with little or no background in programming or experienced educators interested in the new technology of interactive computing will find this workshop of interest. The activities come direct from the classroom experiences in non-traditional undergraduate mathematics classes. The content and pedagogy surrounding the activities are meant to engage students from a variety of academic disciplines and interests. Over the course of the six-hour workshop, participants will be introduced to the Jupyter notebook with both R and Python languages. Participants will also understand how to set up, distribute, and collect classroom materials with the Jupyter notebooks.

Objectives

Introduce Jupyter notebooks as free web based computing tool Demonstrate notebooks use with R and Python computing languages Demonstrate variety of classroom activities possible with Jupyter, R, and Python Demonstrate how to organize a class using this technology online through a website and free course management system

Topical Outline

Introduction to Jupyter, Python, and R •Background on Jupyter and getting set up with the notebooks–Jupyter and Anaconda–Sagemathcloud–Github and Binder •Sequences and Vectors–creating sequences–vectors and operations–basic functions and help •Problem Solving and Markdown Cells •Barplots and Color–The Barplot Function–Simple Plots from Vectors–RColor Brewer–Lab on Colors •Built-In Data in R–The Datasets package–Data Types–Chickweights Data and Pretty Barplots of Data–IQ Data Exploration •ggplot2–the ggplot philosophy–basic aesthetics–ggplot2 visualization lab •Python with Jupyter–Lists–Arrays–Operations with Arrays–Slice and Dice Arrays •Functions and Plotting with Matplotlib–functions–plotting functions with matplotlib–customizing plots with matplotlib •Images as Arrays–Loading images–Manipulating Images–Create a piece of art Lab •Animation–Matplotlib Patches–Animation–Rotating Polygon Lab

Experience Level

Beginner

Qualifications

Dr. Jacob Frias Koehler has been a mathematics teacher for the past 15 years at the high school and undergraduate levels. He currently teaches mathematics at The New School, New York University, and the Borough of Manhattan Community College. Dr. Koehler received his Ph.D. from Columbia University's Teachers College in Mathematics Education under the direction of Dr. Bruce Vogeli and his research focuses on the history of schooling and technology. Dr. Soomi Kim received her Ph.D. in Mathematics Education at the Teachers College, Columbia University under the mentoring of Dr. Bruce Vogeli. She holds a M.S in Computer Science and a M.A in Educational Technology. She taught elementary school, middle school, and college mathematics courses and her research interests include developmental mathematics, instructional strategies, idea-based teaching and learning using technology.

Topics

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