> For teachers

Grades 3–5

iiNNoo for Elementary School

Young students can discover that a computer's prediction is not magic. It is a number multiplied by another number. These lessons use one or two inputs, one output and whole numbers students can check on paper or in their heads.

Learning objectives

Students will be able to:

  1. 01

    Inputs become outputs

    Describe a neural network as a machine that turns an input number into an output number, one step at a time.

  2. 02

    A weight is a multiplier

    Explain that each connection multiplies the number passing along it, and that a bigger weight makes a bigger output.

  3. 03

    Predict, then check

    Work out what the network will say before it says it, then step through the calculation to check.

  4. 04

    Tune the network

    Change a weight until the network's predictions match what really happened.

Lesson plans

Ready-made plans for a day, three days or a week, with what to say, what to watch for and what to ask afterwards.

Lessons to explore

Here are 6 lessons, in order. Each one opens up the app. You may also find all iiNNoo lessons here.

  1. Observe

    The Zoo Visitors Predictor 01

    This network predicts how many people visit a zoo based on the amount of sunshine. The input value is the hours of sunshine. The output value is the number of visitors. Step through the calculation for the first input. Observe how the weight affects the visitors, then repeat with the other input values.

    Open lesson
  2. Predict

    The Cricket Chirp Predictor

    This network predicts how fast crickets chirp based on the temperature. The input value is the temperature. The output value is the chirps per minute. Crickets chirp about 6 times a minute for each degree, so the connection weight is 6. Before each output value is calculated, predict what it will be. Type your answer when asked.

    Open lesson
  3. Edit

    The Phone Battery Predictor

    This network predicts phone battery usage when playing a video. The input value is the video length in hours. The output value is the percent of battery used. Edit the connection's weight so that the output values match the target outputs. When the numbers are close, the double lines will turn green. Test with all 4 inputs.

    Open lesson
  4. Edit

    The Butterfly Count Predictor

    This network predicts the butterflies in a garden based on the number of flower beds and bushes. The input values are the flower beds and the bushes. The output value is the butterflies. Try to make each bush count twice as much as each flower bed. Edit the second weight to make this happen. Confirm your solution works for all inputs.

    Open lesson
  5. Edit

    The Tomato Harvest Predictor

    This network predicts a garden's tomato harvest. The input values are the daily hours of sun and liters of water. The output value is the kilograms picked. Edit both connection weights so the output values match the target outputs. Hint: both weights are between 0 and 1.

    Open lesson
  6. Edit

    The Smoothie Stand Predictor

    This network predicts a stand's sales based on the temperature. The input value is the temperature. The output values are the smoothies and popsicles sold. Edit both connection weights so that the output values match the target values. It takes 2 steps to calculate both outputs. Confirm your solution works for all inputs.

    Open lesson

Example networks

Complete networks to run and explore freely, with no task to finish.

Ready to bring iiNNoo to your classroom?

Questions or ideas? Email us at support@iinnoo.app.

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