Training Data Thoughts

In this worksheet, students analyze incorrect AI responses and determine what kind of training data problem may have caused each mistake. Learners identify issues such as outdated information, lack of diversity in examples, oversimplification, or biased samples. For each case, they hypothesize why the model produced the error and explain their reasoning. This activity teaches students the relationship between training data and model accuracy, emphasizing the importance of balanced and representative datasets.

Curriculum Matched Skills

Technology Literacy – Training Data and AI Behavior

English Language Arts – Evidence-Based Explanation

Critical Thinking – Diagnosing Causes of Errors

Social Studies – Evaluating Information Sources

This worksheet is part of our Why Do AI Models Make Mistakes collection.