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03-learning_outcomes.Rmd
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# Learning Outcomes by Subject
When students complete this module, they will be able to:
## Science/Data Science
### 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)
### 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?)
### 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?
### 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
## Social Science:
Geared towards students who
Never have made a map before
### Tier 1:
- Explain how environmental data science tools reflect our understandings of race and can both perpetuate and challenge racism
- Interpret maps
- Expand understanding of maps (through resources like this counter mapping project and memory maps)
- Navigate the EJScreen tool and/or other similar tools to answer relevant, student-generated research questions about environmental (in)justice
- Understand how these can benefit their own community and neighborhood
### Tier 2:
- Involve in ethnographic studies
- Be able to infer data with a broad socio-economic context
- Visualization of data using programming languages such as R
- Maybe tie-up with different environmental law firms to get a hands-on learning experience by interning/volunteering!
- Be able to come up with concept maps to project a boarder relationship with different interactions
- Think of gathering qualitative data through interviews and surveys that are based around ethics
### Tier 3:
- Placement opportunities for students interested in continuing this field of science
- Introduce public health implications of the data and research?
- Discuss data ethics?
## 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
### 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.
### 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
### 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