How can data science complement the push for coding and computer science classes? CS classes pose unique challenges for educators, who can be inhibited by a lack of subject knowledge, technical training and resources. Meanwhile, data science is a more holistic category that encompasses some coding and computer science skills but also has an emphasis on storytelling, pattern finding, and visualization.
“Data science taps into students’ natural reasoning abilities and helps them understand the world,” said Carole Sailer, a math teacher at North Hollywood High School in Los Angeles Unified, speaking to EdSource. “It doesn’t matter what they want to be — a nurse, a police officer — data science exposes students to state-of-the-art technology and helps them develop their powers of reasoning. It really does inspire kids.”
Continue reading to learn how teachers can incorporate data science into their classrooms, how students can learn at home and what kinds of resources are available.
Learning Data Science at Home
Data science can be complementary to existing curriculum or accessible for students learning at home. Below are a few core areas of data science explained, plus some implementations for at-home learning.
Research design is the strategy to execute a research project and, generally, answer one of two primary questions: What is happening? Why is this happening? Good research design predicts challenges and includes a plan for each step of the process.
How can I learn this at home?
The basic components of research design can be practiced in almost any setting. Look over the five steps of experimental research and think about what experiments you can run in your own home or backyard. For example: How can you determine the average number of dogs that walk past your home every day?
Data analysis is the process of inspecting, cleaning and manipulating datasets to discover new or useful information. This can help guide decision-making, power an application or be used to tell a story. Professional data scientists often use tools like Python or R to wrangle and automate large datasets.
Machine learning uses statistics to find patterns in data and create a computer algorithm that improves the more it is implemented. Data scientists build a model based on sample data that trains the computer on how to make decisions.
Data visualization is telling a story with data using design or graphics. Visualizations encompass everything from interactive dashboards to static infographics. A great data visualization is clear, compelling and accessible for the audience.
How can I learn this at home?
Data visualization professionals recommend regular sketching and doodling. Grab a pen and some paper and imagine how you would show any information around you, in as many ways as possible. Giorgia Lupi and Stefanie Posavec’s Dear Data project can provide some inspiration on where to start.
To support educators and students, MastersInDataScience.org gathered resources and tools that can be used to teach and learn data science skills. Below is a collection of lesson plans, tutorials, datasets and career guides to assist that development.
Bootstrap Data Science Pathway, Bootstrap World: lesson plans and materials (including slide presentations and student workbooks) for a full data science curriculum. Bootstrap modules align with a variety of curriculum standards such as Common Core and CSTA K-12.
Databasic.io:toolkit to introduce the concept of working with data, including analyzing spreadsheets with WTFcsv and data networks with ConnectTheDots. Each tool comes with an Activity Guide for educators.
My First Python Notebook:detailed, step-by-step guide to analyzing data using the Python language and Jupyter notebooks. This tutorial uses data from the California Civic Data coalition on money in politics.
Google’s Python Class: lecture videos, written materials and exercises to learn Python, from setup to utilities. This free resource is recommended for people with “a little bit of programming experience.”
Introduction to Python: open curriculum for teachers and students to learn Python as their first coding language. It covers the basics of object types, loops, functions and classes.
Hour of Python, Trinket: collection of tutorials and challenges to test your Python knowledge. This resource also includes lessons in Spanish, Chinese and Korean.
Census Reporter: interactive exploration of U.S. Census Bureau data meant to help journalists find and visualize data.
U.S. Department of Education Data: government data covering students, educators and schools of all levels. Users can find information on costs, demographics, discipline, safety and more across thousands of datasets.