Cooperative Extension System professionals are the essential bridge to advance economic mobility in small and rural communities across the country through a data science-based approach.
Through the Community Learning Network, CES professionals acquire cutting-edge data science knowledge and core competencies targeted at solving economic mobility issues including:
- Representing ideas through data insights
- Reasoning and proving to assess conclusions based on data-driven learning
- Reflective thinking for data science-oriented problem solutions
- Data-informed problem solving
- Selecting data science-based tools and strategies
- Connecting and communicating
Our purpose
Our Community Learning through Data Driven Discovery (CLD3) process connects CES professionals with community partners including university researchers, local government leaders, citizens, and others to tackle economic mobility issues using a data science framework.
The CDL3 process starts by identifying unanswerable questions in a given community. Then, it provides a framework for understanding the causal factors at the root of these issues in order to address them and drive change. CLD3 is a continuous, sustainable, and controlled feedback loop that can be replicated and implemented in your community, and in communities nationwide.
Curriculum Areas of Focus
The Community Learning Network will focus on four key areas in its work, including:
- Community Learning through Data Driven Discovery Process
- Data Discovery
- Data Science Acumen
- Ethics
- Economic Mobility Snapshots
- Continuous Engagement