Wed, Aug 04, 2021:On Demand
Background/Question/Methods:
Biodiversity scientists must be fluent across disciplines; possess quantitative, computational, and data skills for working with large, complex datasets; and have foundational skills and content knowledge from ecology, evolution, systematics and environmental science. To effectively train the emerging workforce, we must teach science as we do science and embrace emerging data science skills and concepts alongside the knowledge, tools and techniques foundational to organismal biology and ecology. The biodiversity science community has recognized a need to unite biodiversity and data sciences and improve data literacy in the emerging science workforce. The National Science Foundation funded a Research Coordination Network: BLUE Data to cultivate a diverse and inclusive network of biodiversity researchers, data scientists, and biology educators focused on undergraduate data-centric biodiversity education. The BLUE Data Network is working to develop strategies and materials to infuse biodiversity data into the core of the undergraduate science curriculum, facilitate broad-scale adoption of biodiversity data literacy competencies, and improve undergraduate biology training to meet increasing workforce demands in data and biodiversity sciences.
Results/Conclusions: The Four Dimensions of Ecology Education (4DEE) provides a framework, learning objectives, and a validated cross-cutting biological themes that strategically address the skills, content, and multi-dimensional thinking critical for competitive biodiversity scientists and conservation and management professionals. We will present examples of how BLUE has utilized the 4DEE framework alongside open access biodiversity data resources, to develop Open Education Resources that employ multi-dimensional thinking, cross cutting themes, ecology practice, core ecological concepts, and Human-environment interactions. We will show how merging the 4DEE framework with the Biodiversity Data Literacy skills and content has facilitated a broader adoption of materials and elevated the education content and application. We will present assessment data from student's participating in these modules indicating learning gains in twenty-first century field skills and ecology content while employing biodiversity data resources and developing skills resulting in a nuanced understanding of collections-based data resources and their downstream application to biodiversity research. Working across disciplines and among networks we can be intentional as we find a way to integrate the skills, knowledge, and tools that harness the data revolution while fostering the core ecological, environmental and organismal biological knowledge necessary to address the emerging questions in biodiversity science resulting in a better trained, environmental problem-solving workforce.
Results/Conclusions: The Four Dimensions of Ecology Education (4DEE) provides a framework, learning objectives, and a validated cross-cutting biological themes that strategically address the skills, content, and multi-dimensional thinking critical for competitive biodiversity scientists and conservation and management professionals. We will present examples of how BLUE has utilized the 4DEE framework alongside open access biodiversity data resources, to develop Open Education Resources that employ multi-dimensional thinking, cross cutting themes, ecology practice, core ecological concepts, and Human-environment interactions. We will show how merging the 4DEE framework with the Biodiversity Data Literacy skills and content has facilitated a broader adoption of materials and elevated the education content and application. We will present assessment data from student's participating in these modules indicating learning gains in twenty-first century field skills and ecology content while employing biodiversity data resources and developing skills resulting in a nuanced understanding of collections-based data resources and their downstream application to biodiversity research. Working across disciplines and among networks we can be intentional as we find a way to integrate the skills, knowledge, and tools that harness the data revolution while fostering the core ecological, environmental and organismal biological knowledge necessary to address the emerging questions in biodiversity science resulting in a better trained, environmental problem-solving workforce.