Can Machines Learn?

PreK-2 students typically learn about nutritious eating. The foods used in this activity are all fruits and vegetables as "everyday" (nutritious) foods and snack (or fried) foods and desserts (or treats) as "now & then" (less nutritious) foods.

1. Read Aloud of “Just Try One Bite”

2. What is Data

3. Labeled Dataset Activity

4. Train and test a machine learning model in Teachable Machine

5. What Would You Teach A Machine Activity

Vocabulary

• Data: Information we collect and use to answer questions and make decisions

• Label: Text added to data to help train a machine learning model

Teacher Materials

• Teacher Guide

• Teacher Slides

• Labeled Dataset Activity

  • Google Slide (optional)

  • Seesaw Activity (optional)

  • Teachable Machine

    • Food Images (for training and testing)

• Teacher device and printer

Student Materials

• What Would You Teach A Machine Activity

  • If doing on paper:

    • Handout (print 1 for each student) OR blank paper

    • Pencils, Crayons, Markers (for drawing training images)

    • Magazines, scissors, and glue OR stickers (optional to use for training images instead of drawing)

  • Student devices to access: (optional, if doing digitally)

    • Seesaw OR

    • Google Slides (Click Use Template to make a copy and assign in Google Classroom)

2026 Standards

EK-ALG-ML-02: Recognize attributes of objects to notice patterns and make decisions.
E1-ALG-ML-02: Recognize that AI systems are technologies that use patterns in data to make decisions or generate new things.
E2-ALG-ML-02: Examine how data is used to train a machine learning model.

2017 Standards

1A-DA-07 Identify and describe patterns in data visualizations, such as charts or graphs, to make predictions.

Big Idea 3 - Machine Learning

K-2.3-A-ii Identify patterns in labeled data and determine the features that predict labels. 

K-2.3-A-iii Demonstrate how to train a computer to recognize something. 

K-2.3-C-i Create a labeled dataset with explicit features to illustrate how computers can learn to classify things like foods, movies, or toys. 

K-2.3-C-iii Examine a labeled dataset and identify problems in the data that could lead a computer to make incorrect predictions.