Biases in data
Recognize all data contains bias but data collection and analysis methods can increase or mitigate the effects of biases.
K–2 Competencies
Recognize how data are affected by decisions made around data design, collection, and interpretation.
Classroom resources
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
Recognize that some biases in data are neutral, while others can be harmful when making decisions and inferences, and some may not cause harm at all. e.g., neutral, preference of apples over oranges in a fruit study; harmful, surveying the coding club to generalize about all students
Understand the importance of considering the context, scope, and purpose of data in order to mitigate bias.
Classroom resources
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
Identify how biases in data affect inferences and questions.
Classroom resources
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
Recognize how biases can obscure inferences drawn from data.
Consider how the consolidation or combination of different data can create additional biases.
Classroom resources
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
Propose multiple perspectives on data to mitigate inherent biases.
Understand the difference between implicit and explicit bias.
Classroom resources
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.
Advanced Competencies
Classroom resources
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