We recently worked with the American Institutes for Research (AIR) to produce a national-level work-based learning map. Built using ArcGIS Online and the Esri JavaScript API, the map can be custom-tailored to specific state or local agency leadership teams. Using these customized maps, teams can better contextualize their workforce development initiatives and refine their understanding of resources and socioeconomic distribution across their region.
Nearly five decades of research has demonstrated that the places where individuals live and learn have a dramatic impact on their opportunities and life outcomes. These place effects—the advantages and disadvantages that one inherits by simply living in a particular location—have a particularly strong impact on one’s access to high-quality education, workforce training, and employment, which are the key ingredients to upward economic mobility. It is vital that leaders in state and local education agencies are mindful of place effects as they help districts and schools to develop work-based learning (WBL) systems across diverse contexts.
Through this application, AIR can more easily identify areas of improved workplace development and analyze the factors that lead to this outcome. This could include factors such as education opportunities, health benefits, or a variety of social factors.
How do I use it?
Users are able to activate different layers that fall under categories such as Education, Health, and Social Factors. By looking across states and the country as a whole, we are able to understand which communities are at a disadvantage when it comes to these factors. As we explained earlier, these factors are vital to spark upward economic mobility. When viewing these different layers, we can have a higher understanding of where these lacking communities are located, and where resources need to be more readily available.
Here is a demo of the application in action.
To visualize connectivity of both cities and communities simultaneously, the Blue Raster team used a combination of heat map cartography in addition to point and polygon data to show where overlaps occur between cities, communities, counties, and states.
