Exploring environmenATL justice and data analytics in an environmental studies lab course.

Area of Science:

• Environmental Science
• Data Analytics
• Environmental Justice

Background:

• Environmental science increasingly utilizes "big data" for research.
• Environmental inequalities disproportionately affect minority and low-income populations in the U.S.
• Historical factors like "redlining" have shaped environmental injustices.

Purpose of the Study:

• To design and integrate an environmental justice and data analytics module in an environmental studies lab course.
• To provide students with tools and strategies to understand, assess, and intervene in environmental injustices.
• To develop students' advocacy and communication skills through data analysis.

Main Methods:

• Introducing an environmental justice framework and its application.
• Examining socioeconomic and environmental factors in Atlanta, Georgia, focusing on redlining.
• Teaching basic data handling and statistical analysis skills (data types, descriptive statistics, sampling, inferential statistics).

Main Results:

• Students critically examine historical and contemporary environmental injustices.
• Students develop research questions to illuminate trends and patterns of environmental justice.
• Students gain practical data analysis skills applicable to real-world issues.

Conclusions:

• Integrating environmental justice and data analytics empowers students to engage in authentic examination of their world.
• The module enhances critical thinking, data literacy, and problem-solving skills.
• Skills gained are transferable to graduate studies and employment, promoting positive societal change.