Variability in our computational world
Explore how AI model outputs vary based on training data, labeling, and bias. Understand how generative AI and pre-trained models use large datasets to make inferences and how variability in data impacts outcomes.
K–2 Competencies
Classroom resources
Data Science Starter Kit Module 3: Making Sense of Data - Analysis and Modeling
Welcome to the exciting part of data science—making sense of the information you’ve collected! This module focuses on how to analyze data to find patterns, understand what the numbers really mean, and start drawing conclusions.🔗
Analysis and Modeling isn’t about complex mathematics or advanced statistics. It’s about developing the thinking skills to look at data and ask, “What story is this telling me? What patterns do I notice? What questions does this raise?” Whether students are working with simple tally marks or sophisticated datasets, the fundamental thinking is the same.
3–5 Competencies
Classroom resources
Data Science Starter Kit Module 3: Making Sense of Data - Analysis and Modeling
Welcome to the exciting part of data science—making sense of the information you’ve collected! This module focuses on how to analyze data to find patterns, understand what the numbers really mean, and start drawing conclusions.🔗
Analysis and Modeling isn’t about complex mathematics or advanced statistics. It’s about developing the thinking skills to look at data and ask, “What story is this telling me? What patterns do I notice? What questions does this raise?” Whether students are working with simple tally marks or sophisticated datasets, the fundamental thinking is the same.
6–8 Competencies
Conceptualize how the output of AI models such as LLMs vary along a variety of dimensions.
Determine how labeling happens and how it affects the variability of the output of models. e.g., training set that labels dogs vs. cats, consider connections to bias
Classroom resources
Data Science Starter Kit Module 3: Making Sense of Data - Analysis and Modeling
Welcome to the exciting part of data science—making sense of the information you’ve collected! This module focuses on how to analyze data to find patterns, understand what the numbers really mean, and start drawing conclusions.🔗
Analysis and Modeling isn’t about complex mathematics or advanced statistics. It’s about developing the thinking skills to look at data and ask, “What story is this telling me? What patterns do I notice? What questions does this raise?” Whether students are working with simple tally marks or sophisticated datasets, the fundamental thinking is the same.
9–10 Competencies
Acknowledge how variability in the training data for generative AI influences bias in its output. e.g., facial recognition, ownership of DNA data
Classroom resources
Data Science Starter Kit Module 3: Making Sense of Data - Analysis and Modeling
Welcome to the exciting part of data science—making sense of the information you’ve collected! This module focuses on how to analyze data to find patterns, understand what the numbers really mean, and start drawing conclusions.🔗
Analysis and Modeling isn’t about complex mathematics or advanced statistics. It’s about developing the thinking skills to look at data and ask, “What story is this telling me? What patterns do I notice? What questions does this raise?” Whether students are working with simple tally marks or sophisticated datasets, the fundamental thinking is the same.
11–12 Competencies
Appreciate that many AI tools are pre-trained with large quantities of data so that inferences can be drawn on smaller sample sizes.
Classroom resources
Data Science Starter Kit Module 3: Making Sense of Data - Analysis and Modeling
Welcome to the exciting part of data science—making sense of the information you’ve collected! This module focuses on how to analyze data to find patterns, understand what the numbers really mean, and start drawing conclusions.🔗
Analysis and Modeling isn’t about complex mathematics or advanced statistics. It’s about developing the thinking skills to look at data and ask, “What story is this telling me? What patterns do I notice? What questions does this raise?” Whether students are working with simple tally marks or sophisticated datasets, the fundamental thinking is the same.
Advanced Competencies
Classroom resources
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