Data Table Cleanup

This worksheet helps students in Grades 6, 7, and 8 build data literacy, critical thinking, and technology skills by analyzing a messy dataset similar to those used in AI training. Learners examine tables with duplicate entries, inconsistent labels, unclear categories, and formatting problems, then identify errors and propose rules for cleaning and standardizing the data.

Learning Goals

• Data Cleaning & Standardization (Grades 6-8) – Recognizing duplicates, inconsistencies, and missing labels in datasets
• Critical Thinking – Identifying how errors and unclear structure reduce data quality
• Analytical Reading of Tables – Interpreting tabular information carefully and accurately
• STEM & AI Literacy – Understanding preprocessing as a key step in building reliable AI systems

Instructional Benefits

• Teacher-Created Resource – Designed to align with ELA, STEM, and technology literacy standards
• Authentic Data Practice – Mimics real-world challenges found in raw AI training data
• Rule-Based Reasoning – Students propose clear systems for cleaning and organizing data
• Attention to Detail – Reinforces careful observation and procedural thinking
• Low-Prep Format – Easy to print and use in classrooms or homeschool settings

This printable worksheet helps students see how small data issues can lead to large AI problems. By identifying errors and designing cleanup rules, learners strengthen analytical reasoning, data organization skills, and understanding of how clean datasets support accurate AI outcomes. It is a practical resource for classroom and homeschool instruction focused on data quality, preprocessing, and responsible AI development.

This worksheet is part of our AI Data Labeling Game Worksheets collection.