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Machine Learning With Scratch 3.0

Explore and create

Explore and create : Creation lab


Friday, December 4, 11:30 am–12:20 pm PST (Pacific Standard Time)

Heidi Baynes  
Artificial intelligence is part of our daily lives and most of our students don’t remember a world without it. Learn to use Scratch to simulate machine learning, control sprites with both text and voice, and teach the computer to recognize pictures.

Audience: Coaches, Teachers, Technology coordinators/facilitators
Skill level: Beginner
Attendee devices: Devices required
Attendee device specification: Laptop: Chromebook, Mac, PC
Topic: Artificial Intelligence
Grade level: 6-12
Subject area: STEM/STEAM, Computer science
ISTE Standards: For Educators:
Designer
  • Design authentic learning activities that align with content area standards and use digital tools and resources to maximize active, deep learning.
For Students:
Computational Thinker
  • Students understand how automation works and use algorithmic thinking to develop a sequence of steps to create and test automated solutions.
Additional detail: Session recorded for video-on-demand

Proposal summary

Purpose & objective

Artificial Intelligence is part of our daily lives and most of our students don’t remember a world without it. As technologies develop students will graduate into a world where AI and Machine Learning will be heavily integrated into both our personal and professional lives.

This session will introduce beginners to the principles of machine learning and will teach them how to use Scratch 3.0 to introduce machine learning to their students using the familiar platform of Scratch block programming. The activity is comparable to beginning to build one's own Amazon Alexa or Google Home machine.

Using Scratch 3.0 and an extension created by https://machinelearningforkids.co.uk/ participants will learn how to integrate the principles of machine learning into the Scratch platform and to begin teaching students the basics of machine learning. We will simulate machine learning by learning how to control sprites with both text and voice, and teaching the computer to recognize pictures.

Outline

In this hands-on virtual session, participants will follow along with the presenter as she introduces https://machinelearningforkids.co.uk and shows them how to connect it to Scratch 3.0. Participants will work individually or in pairs using their own devices to create a program that recognizes and learns written commands and consequently turns a light on and off, or turns a fan on and off.

5 minute- Introduction of presenter
5 minute- ice breaker
30 minutes- Hands on activity; Participants follow along using another tab to create a machine learning example in Scratch.
10 minutes- Debrief and group discussion on classroom applications
10 minutes- Individuals explore additional templates available through https://machinelearningforkids.co.uk/ and have time to add or change the demo project they created during the session.

Supporting research

https://www.gettingsmart.com/2019/01/teaching-students-about-ai/

https://medium.com/bits-and-behavior/we-need-to-learn-how-to-teach-machine-learning-acc78bac3ff8

https://www.intechopen.com/books/machine-learning-advanced-techniques-and-emerging-applications/machine-learning-in-educational-technology

https://insights.dice.com/2019/06/06/student-resources-ai-ml-education/

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Presenters

Photo
Heidi Baynes, Riverside County Office of Education

Heidi Baynes is a Google Certified Trainer and Innovator and Raspberry Pi Certified Educator. She works as a Coordinator of Educational Technology for the Riverside County Office of Education. She specializes in the integration of technology into classroom instruction and is a strong advocate of computer science education and the #CSforALL movement. Her experience in K-12 education includes online, blended, and traditional classroom models where she has taught multiple subjects and grade levels. She is invested in the importance of the Maker Movement and ways to merge the maker mentality with lesson design to enhance the student learning experience.

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