Backpropagation
A process used in training neural networks where the model adjusts its internal weights to reduce errors.
👩🏫 How to Explain by Age Group
Elementary (K–5)
“Imagine a student getting a math question wrong, then learning the right way and trying again. Backpropagation is how computers learn from mistakes, just like that student!”
Middle School (6–8)
“Backpropagation is like checking your answers after a quiz. When the AI gets something wrong, it traces back through its steps to figure out what went wrong and adjusts to do better next time.”
High School (9–12)
"Backpropagation is a learning algorithm used in neural networks. After making a prediction, the AI compares it to the correct answer, calculates the error, and adjusts internal connections (weights) to reduce future errors, similar to refining a process based on feedback.”
🚀 Classroom Expeditions
Mini-journeys into AI thinking.
Elementary (K–5)
Give students a maze worksheet. If they go the wrong way, let them trace back and try again. Then connect the idea to how computers “learn” from wrong answers.
Middle School (6–8)
Have students play a trivia game. After each round, they correct wrong answers and reflect on how their thinking changed. Relate this to how AI corrects its predictions using backpropagation.
High School (9–12)
Simulate a neural network using a spreadsheet: show how predictions, errors, and adjustments work with simple math. Use a visual demo to illustrate how errors flow backward to improve future outputs.
