Concept A1.2
AI Literacy

Data are produced by people

Recognize that data represent decisions about measurement and inclusion involving people who are and are not immediately present.

K–2 Competencies

Recognize the importance of asking questions about how data were collected.

K-2.A.1.2a

Classroom resources

Classroom Tip
Getting Started

Data Science Starter Kit - Module 1: Data Dispositions and Responsibilities

Welcome to the foundation of data science education! This module focuses on developing the right mindset for working with data—both for you and your students.🔗

Data Dispositions and Responsibilities isn’t about memorizing definitions or learning technical skills. It’s about cultivating curiosity, healthy skepticism, and ethical thinking. These are the habits of mind that make everything else in data science meaningful and responsible.

3–5 Competencies

Ask questions about how data are collected or considered.

3-5.A.1.2a

Understand that data is generated by people who make decisions about what and how to measure.

3-5.A.1.2b

Classroom resources

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Getting Started
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Data Science Starter Kit - Module 1: Data Dispositions and Responsibilities

Welcome to the foundation of data science education! This module focuses on developing the right mindset for working with data—both for you and your students.🔗

Data Dispositions and Responsibilities isn’t about memorizing definitions or learning technical skills. It’s about cultivating curiosity, healthy skepticism, and ethical thinking. These are the habits of mind that make everything else in data science meaningful and responsible.

6–8 Competencies

Ask questions regarding the origins of specific automated measures (e.g., webtracking, email meta-data, user accounts).

6-8.A.1.2a

Recognize the limits of the information the data can provide and the story it can tell.

6-8.A.1.2b

Recognize that conclusions may need to be revised in the future as more knowledge and data become available.

6-8.A.1.2c

Classroom resources

Classroom Tip
Getting Started
Thank you for your feedback.
Write more feedback

Data Science Starter Kit - Module 1: Data Dispositions and Responsibilities

Welcome to the foundation of data science education! This module focuses on developing the right mindset for working with data—both for you and your students.🔗

Data Dispositions and Responsibilities isn’t about memorizing definitions or learning technical skills. It’s about cultivating curiosity, healthy skepticism, and ethical thinking. These are the habits of mind that make everything else in data science meaningful and responsible.

9–10 Competencies

Explain how data-based decisions are revisited as new evidence or societal needs emerge (e.g., blood pressure cut-off numbers, dietary guidance, medical benchmarks).

9-10.A.1.2a

Evaluate why data models require updates to maintain accuracy and relevance.

9-10.A.1.2b

Classroom resources

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Getting Started
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Data Science Starter Kit - Module 1: Data Dispositions and Responsibilities

Welcome to the foundation of data science education! This module focuses on developing the right mindset for working with data—both for you and your students.🔗

Data Dispositions and Responsibilities isn’t about memorizing definitions or learning technical skills. It’s about cultivating curiosity, healthy skepticism, and ethical thinking. These are the habits of mind that make everything else in data science meaningful and responsible.

11–12 Competencies

Explore the origins of some standardized unit measurements (e.g., horsepower, mole, scores on AP exams).

11-12.A.1.2a

Identify the risks and tradeoffs of using traditional measurements (e.g., IQ, BMI).

11-12.A.1.2b

Classroom resources

Classroom Tip
Getting Started
Thank you for your feedback.
Write more feedback

Data Science Starter Kit - Module 1: Data Dispositions and Responsibilities

Welcome to the foundation of data science education! This module focuses on developing the right mindset for working with data—both for you and your students.🔗

Data Dispositions and Responsibilities isn’t about memorizing definitions or learning technical skills. It’s about cultivating curiosity, healthy skepticism, and ethical thinking. These are the habits of mind that make everything else in data science meaningful and responsible.

Classroom resources

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