Data Table Cleanup

In this worksheet, students examine a messy dataset designed to mimic raw data used to train AI models. The dataset includes duplicate entries, inconsistent labeling, unclear categories, and formatting issues. Students analyze the dataset to identify errors, list duplicate or near-duplicate items, and determine which entries lack proper labels. They then propose rules or systems for cleaning and standardizing the data. The worksheet builds data literacy skills by teaching students how inconsistencies negatively affect AI performance and how clean, reliable datasets produce more accurate results. It reinforces attention to detail and procedural thinking.

Curriculum Matched Skills

Technology Literacy – Data Cleaning and Standardization

Critical Thinking – Identifying Errors and Inconsistencies

English Language Arts – Analytical Reading of Tabular Information

STEM Literacy – Understanding Preprocessing in AI Systems

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