Chapter 2 Learning Outcomes by Subject

When students complete this module, they will be able to:

2.1 Science/Data Science

2.1.1 Overarching LOs - to be applied at all tiers

Understand how data science can be used to create environmental solutions for communities
Place data science questions in context (ecological, environmental, community solution, etc)
Understand complexities and limitations of data
Evaluate drawbacks/benefits of tools like EJScreen
Interpret results in context (ecological, environmental, community solution, etc)

2.1.2 Tier 1 (Intro level)

Prerequisite Knowledge: None!

Explain how environmental indices can affect their community
Evaluate the differences in the tools (EJScreen vs CEJST vs state-based(?) tools)
And the benefits/drawbacks of the tools and how underlying data influences results (e.g., EJScreen uses census data - that is biased)
Evaluate the positives and negatives of abstracting a place to one number
Understand how weighting can impact results
Question policy-makers and land managers on environmental justice issues
Collaboratively develop action plans to move forward from their findings (wording of this sentence?)

2.1.3 Tier 2 (Mid level)

Prerequisite Knowledge: Basic introduction to data science and statistical analyses, e.g.

Access data through R
Execute pre-written example code and interpret the results
Construct and modify R code to test hypotheses
Choose a place and tell a story about why it is identified as an EJ place. What is missing? Is there a place that you thought would show up in EJ screen but does not? What data gap makes that happen?

2.1.4 Tier 3 (Upper Division)

Prerequisite Knowledge:

Student-driven project initiatives (SMART principles)
Formulate a testable question
Justify why this question is interesting with appropriate background information
Create a justified hypothesis
Obtain data from public sources (like EJ screen)
Process raw data into usable formats
Analyze data with appropriate statistical methods to answer the question
Visualize data
Contextualize results in broader context ((ecological, environmental, community solution, etc)
Communicate results through - e.g. a paper, poster, flash talk, other format
quantitative models to address scientific questions?
Testable question
Placed in the context
Obtaining, cleaning, transforming, and processing raw data into usable formats?
Apply a range of statistical methods for inference and prediction…
Build data science products that can be used by a broad audience - or can be transferable to other broader contexts

2.3 Socially Engaged Art:

Geared towards students who

Are interested in creatively expressing and communicating their data analysis
Are interested in connecting and engaging in reciprocal story sharing with local community members about pertinent environmental justice issues

2.3.1 Tier 1: communication (2-3 weeks)

Tier objective : introduce students to science communication, socially engaged art, and research translation with hands-on activities between students and with the general public

Students read foundational literature on the history of socially engaged art practices, and how science, art, and agency are tied together.
Students create a representation of the results from the Data Science and Social Science subjects that can be shared with classmates and the broader community
Representations could take the form of ArcGIS StoryMaps, collage, art installation, composition, art/dance/theater performance, a poster, presentation, etc.
Do a site visit with students and teachers to see the EJ community first-hand and learn from locals (example: Dakota Bdote tour) Class creates a gallery show and/or hosts an event to share creative works with each other and community members.

2.3.2 Tier 2: storytelling (2 weeks)

Tier objective : Students and community members come to a more holistic understanding of the different experiences and perspectives related to environmental justice, for example of how personal experiences are part of shared experiences or a larger picture

Organize a gathering of students and residents with different breadths of traditional and ancestral knowledge like teachers and Indigenous leaders.
Storytelling preparation:
- Hold a reflection session (individually or in groups) and a writing workshop to be able to put ideas and thoughts into words more effectively
- Run a storytelling workshop for students to practice telling and listening to stories
Facilitate an organic sharing and listening of stories between students and community members related to environmental justice from embodied experiences, research, data analysis

2.3.3 Tier 3: co-creation of knowledge (longterm, multi-year)

Tier objective: Build and sustain healthy relationships between students, local stakeholders, and Indigenous leaders. Over time, co-create a collective understanding of the root causes of environmental justice issues in the local community, brainstorm ways to sustainably address these issues, and empower the community to tackle these issues.

Enable communication channels for continued support between students and residents, knowledge exchange and future collaborations.
Engage students and community members in regular meetups and activities to develop a community of students engaged in environmental justice
Support participants (students and community members) through funding sources
Secure funding for a competition for participants to propose a new or an extension to an existing EJ project that the winning team can work on for a year.

Multi-lingual: https://www.enlightenment.org/develop/legacy/program_guide/multilingual_pg