Training Data Thoughts
This worksheet is designed for Grades 6, 7, and 8 to help students explore how artificial intelligence systems learn from training data and why errors sometimes occur. Through close reading, evidence-based explanation, critical thinking, and technology literacy, students analyze incorrect AI responses and connect them to issues such as bias, outdated information, oversimplification, and limited data representation .
Key Learning Objectives
- Training Data Analysis (Grades 6-8)
Students identify how different types of training data problems influence AI outputs and decision-making. - Evidence-Based Explanation
Learners practice explaining their reasoning using details from each scenario and clear cause-and-effect thinking. - Critical Thinking & Error Diagnosis
Students evaluate mistakes, determine likely causes, and distinguish between data gaps, bias, and oversimplification. - Information Source Evaluation
Activities reinforce how the quality and balance of sources affect accuracy and reliability.
Instructional Support
- Educator-Designed Content
Created to introduce AI concepts in a structured, student-accessible format. - Multiple Use Options
Suitable for technology lessons, ELA integration, social studies discussions, or enrichment activities. - Clear, Scaffolded Prompts
Scenarios guide students step by step through analysis and explanation. - Supports Discussion and Writing
Encourages both written responses and classroom conversation about AI behavior.
This printable worksheet helps students build a deeper understanding of how training data shapes artificial intelligence outcomes, accuracy, and fairness. By connecting AI errors to underlying data issues, learners strengthen skills in reasoning, explanation, information evaluation, and digital literacy. It works well in both classroom and homeschool settings as a no-prep resource for teaching thoughtful and responsible engagement with AI systems.
This worksheet is part of our Why Do AI Models Make Mistakes collection.
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