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Learning to Swim: The transition from data desert to deluge in undergraduate biology education.

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Presentation on theme: "Learning to Swim: The transition from data desert to deluge in undergraduate biology education."— Presentation transcript:

1 Learning to Swim: The transition from data desert to deluge in undergraduate biology education

2 Nature of science in policy documents … undergraduates need to understand the process of science, the interdisciplinary nature of the new biology, and how science is closely integrated within society. Students also should be competent in communication and collaboration, as well as have a certain level of quantitative competency, and a basic ability to understand and interpret data. Vision and Change: A Call to Action (2011)

3 William Harris http://science.howstuffworks.com/innovation/scientific-experiments/scientific-method6.htm

4 Public Perception of Science Paul Vallett http://electroncafe.wordpress.com/2011/05/04/scientific-process-rage/

5 Science In Reality Paul Vallett http://electroncafe.wordpress.com/2011/05/04/scientific-process-rage/

6 http://undsci.berkeley.edu/lessons/pdfs/alvarez_woflow.pdf

7 Cornell Lab of Ornithology - Online Research in Biology

8 Ecological Society & Science Pipes – Data for the Ecology Classroom

9 Rocky Mountain Biological Lab - Bringing a Field Station Into the Classroom

10 Claudia Neuhauser - UMN

11 CUREnet – Course-based Undergraduate Research Experiences NSF – Research Coordination Network Erin Dolan and Dave Micklos First meeting this February

12 Open Questions How do you manage classrooms to take advantage of scientific data and support student inquiry? – What are data literacy skills? What skills does the teacher need? What do students need? – What types of resources should projects provide Instructional resources Professional development Assessment models

13 Data Life Cycle

14 Core Competencies for Data Information Literacy Introduction to Databases and Data Formats Discovery and Acquisition of Data Data Management and Organization Data Conversion and Interoperability Quality Assurance Metadata Data Curation and Re-use Cultures of Practice Data Preservation Data Analysis Data Visualization Ethics, including citation of data Determining Data Information Literacy Needs: A Study of Students and Research Faculty Jacob Carlson, Michael Fosmire, C.C. Miller, and Megan Sapp Nelson

15 Model for Data Literacy Skills in Science and Science Education FIGURE 1 A diagrammatic representation of how scientific data literary skills play an important role in science and science education.

16 Model for Teaching Scientific Data Literacy Skills Figure 2: A diagrammatic representation of a Data Skills Unit. The unit is made up of three elements: -Learning Objectives -Instructional Strategies -Performance Assessments


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