Math Hacks for Scratch by Michael Mays - ISBN: 9781718503380
Paperback
Code math’s mysteries in Scratch: projects, games, and mind-bending fun.

Math Hacks for Scratch

Unlock the Power of Math with Scratch Programming

$49.14

  • Paperback

    240 pages

  • Release Date

    10 December 2024

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Summary

Push Scratch programming to the limits as you explore primes, Fibonacci numbers, Pascal’s triangle, and other mathematical curiosities through hands-on coding projects. If you’re a student looking for project ideas to practice your math and coding skills, or a Scratch enthusiast just looking for something different, this is the book for you!

Discover the exciting intersection of mathematics and programming with Math Hacks for Scratch. This book is perfect for kids, ed…

Book Details

ISBN-13:9781718503380
ISBN-10:1718503385
Author:Michael Mays
Publisher:No Starch Press,US
Imprint:No Starch Press,US
Format:Paperback
Number of Pages:240
Release Date:10 December 2024
Weight:369g
Dimensions:234mm x 177mm
What They're Saying

Critics Review

“Inspired by the author’s grandchildren, this book offers up a playful approach to mathematics learning using the block-based coding language pioneered by Scratch. Dr. Michael Mays has done a compelling job of using a creative coding platform to enliven and enrich young people’s engagement with math, by using coding to engage with numbers, puzzles, and patterns.” —Margaret Honey, President & CEO, Scratch Foundation“Michael Mays’ Math Hacks for Scratch is a combination of code and calculation that I wish I had as a student. It takes the challenges you find in math books and adds a Scratch programming twist. These 33 projects are more fun than doing math on a boring whiteboard.”—Al Sweigart, software developer and bestselling author of Automate the Boring Stuff with Python

About The Author

Michael Mays

Michael Mays has a PhD in mathematics from Penn State University. His teaching career at West Virginia University spanned 40 years, including roles as director of the Institute for Math Learning and chair of the Department of Statistics. His innovative approach to math education has earned him recognition as an Eberly Teaching Professor.

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