Bringing Real-Time Data into the Classroom to Study Ocean Science Ali Whitmer & Carol Blanchette,...
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Bringing Real-Time Data into the Classroom to Study Ocean Science Ali Whitmer & Carol Blanchette, Marine Science Institute, UC Santa Barbara, Bruce Caron, The New Media Studio, Santa Barbara, CA INTRODUCTION In addition to lab and fieldwork, data manipulation and analysis is the essence of investigative learning in science. Undergraduate students have the capability and desire to work with real datasets, which provide opportunities to explore difficult concepts such as climate change. The ability for students to manipulate data using different methods (means, maxima, anomalies) can be incredibly powerful in understanding how patterns, interpretations and predictions change using different techniques. However there are impediments that keep real dataset manipulation out of the classroom, including the steep learning curve to use powerful analysis and visualization software. Our proposed Ocean Science Data Discovery Center (OSDDC) is a software and curriculum project that leverages existing technologies into a bridge that connects research visualization tools with educational courseware development and assessment. OSDDC offers research-level data visualization and analysis capabilities to its users. This supports inquiry by providing students the technical means to visualize actual datasets acquired via the Internet. This project focuses on marine science topics by linking ocean temperature datasets (e.g., World Ocean Atlas) with biological, geological and ecological datasets, allowing students to investigate relationships among biotic and abiotic processes and across scales. The overarching goals of this project are to: • Build technological tools to effectuate and provide data access, visualization, and analytical capability for marine science learning and to construct and design learning assessment tool capabilities within the software; • Provide key aspects of marine science education through the use of ocean temperature measures from a range of temporal and spatial scales; • Develop marine science data literacy through increasing integration of computer technology (i.e., tools and software) into marine science learning. PROJECT GOALS AN INTEGRATED ASSESSMENT TOOL Within the Ocean Science Data Discovery Center development plan an entirely new layer of software development will occur. This layer will add built-in design and learning assessment capabilities to this and all future Data Discovery tools. In essence, the instructor becomes a "superuser" with an added capability: they can create a series of floating windows queued to specific learning or design elements in the data discovery tool. In these windows, they author questions and other assessment tools (sliders for indexical values, etc.), which provide feedback mechanisms. Users have the option of switching on the assessment capability and answering the questions at the appropriate time during their interaction with the software. The answers are concatenated and then sent to the server for analysis. Pre- and post-tests can also be administered directly through the tool. THE CURRICULUM COMPONENT There are numerous curriculum modules that could be developed around this software and these data sets. This project focuses on the integration of ocean and organismal data. There are multiple advantages to the use of this tool in the assessment and evaluation of this software. Because the questions are queued to the specific content and interface where appropriate, they provide accurate feedback about specific issues. And because the assessment is built into the software, the instructors are not required to do additional work, or gain an additional assessment skill. The assessment layer can also be refined through user evaluations of this capability. This capability will be created for the Ocean Science Data Discovery Center software. But the code will also become a part of the Data Discovery Toolkit and Foundry project in the NSDL, where other developers can freely use and improve this. Again, here is an example of the multiplier effect of shared software resources based on standard-off-the-shelf software authoring programs. From PISCO Coastal Connections © 2002 www.piscoweb.org For example, scientists working with the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO) have been examining organismal distribution patterns at more than 50 sites that span 1,200 miles of the US west coast. At the right is a graph of the biodiversity data (purple bar graph) and data on the recruitment of juvenile mussels in the genus Mytilus (yellow bar graph). Examining the mussel recruitment data reveals a dramatic shift in recruit abundance as you move along the coast. By combining data sets such as these with the World students will have an opportunity to investigate hypotheses relating recruitment data with oceanographic data such as the Nitrate values for the same stretch of coastline plotted at the right. THE SOFTWARE TOOL The Ocean Science Discovery Data Center will be built around an exisitng software tool – World Ocean Atlas Viewer. This viewer currently displays data from the World Ocean Atlas 1998 (www.nodc.noaa.gov ) and will be updated to include 2001 data. WOA Viewer was created by Dr. William A. Prothero (UC, Santa Barbara) and The New Media Studio (Santa Barbara, CA). The World Ocean Atlas Viewer displays 22 types of ocean data. The figure below is the Virtual Viewer display. Students can choose among data sets, which are displayed on the map and described in the text box. By moving the mouse over the map, students can determine the data under the cursor. Students can rotate the map in order to simultaneously view a depth slice as well as the surface view. The depth view can display the same or a different data set relative to the surface data. In the figure to the right, sea surface temperature is displayed on both views. Data sets include: • Sea Surface Temperature • Evaporation • Wind Speed • Global Dissolved Oxygen • Global Chlorophyll • Global Salinity • Outgoing Longwave Radiation About the Data… provides definitions of the data sets. The Slice Viewer plots data with at depth for virtually any “slice” across the ocean that the student draws with the cursor. You have chosen to examine Dissolved Oxygen at depth against Global Chlorophyll data at the sea surface. What are your predictions about the relationship between these variables? Write your answers down before continuing with this exercise.
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Transcript of Bringing Real-Time Data into the Classroom to Study Ocean Science Ali Whitmer & Carol Blanchette,...
Bringing Real-Time Data into the Classroom to Study Ocean Science
Ali Whitmer & Carol Blanchette, Marine Science Institute, UC Santa Barbara,
Bruce Caron, The New Media Studio, Santa Barbara, CA
INTRODUCTION
In addition to lab and fieldwork, data manipulation and analysis is the essence of investigative learning in science. Undergraduate students have the capability and desire to work with real datasets, which provide opportunities to explore difficult concepts such as climate change. The ability for students to manipulate data using different methods (means, maxima, anomalies) can be incredibly powerful in understanding how patterns, interpretations and predictions change using different techniques. However there are impediments that keep real dataset manipulation out of the classroom, including the steep learning curve to use powerful analysis and visualization software. Our proposed Ocean Science Data Discovery Center (OSDDC) is a software and curriculum project that leverages existing technologies into a bridge that connects research visualization tools with educational courseware development and assessment. OSDDC offers research-level data visualization and analysis capabilities to its users. This supports inquiry by providing students the technical means to visualize actual datasets acquired via the Internet. This project focuses on marine science topics by linking ocean temperature datasets (e.g., World Ocean Atlas) with biological, geological and ecological datasets, allowing students to investigate relationships among biotic and abiotic processes and across scales.
The overarching goals of this project are to:
• Build technological tools to effectuate and provide data access, visualization, and analytical capability for marine science learning and to construct and design learning assessment tool capabilities within the software;
• Provide key aspects of marine science education through the use of ocean temperature measures from a range of temporal and spatial scales;
• Develop marine science data literacy through increasing integration of computer technology (i.e., tools and software) into marine science learning.
PROJECT GOALS
AN INTEGRATED ASSESSMENT TOOLWithin the Ocean Science Data Discovery Center development plan an entirely new layer of software development will occur. This layer will add built-in design and learning assessment capabilities to this and all future Data Discovery tools.
In essence, the instructor becomes a "superuser" with an added capability: they can create a series of floating windows queued to specific learning or design elements in the data discovery tool. In these windows, they author questions and other assessment tools (sliders for indexical values, etc.), which provide feedback mechanisms. Users have the option of switching on the assessment capability and answering the questions at the appropriate time during their interaction with the software. The answers are concatenated and then sent to the server for analysis. Pre- and post-tests can also be administered directly through the tool.
THE CURRICULUM COMPONENTThere are numerous curriculum modules that could be developed around this software and these data sets. This project focuses on the integration of ocean and organismal data.
There are multiple advantages to the use of this tool in the assessment and evaluation of this software. Because the questions are queued to the specific content and interface where appropriate, they provide accurate feedback about specific issues. And because the assessment is built into the software, the instructors are not required to do additional work, or gain an additional assessment skill. The assessment layer can also be refined through user evaluations of this capability.
This capability will be created for the Ocean Science Data Discovery Center software. But the code will also become a part of the Data Discovery Toolkit and Foundry project in the NSDL, where other developers can freely use and improve this. Again, here is an example of the multiplier effect of shared software resources based on standard-off-the-shelf software authoring programs.
From PISCO Coastal Connections © 2002 www.piscoweb.org
For example, scientists working with the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO) have been examining organismal distribution patterns at more than 50 sites that span 1,200 miles of the US west coast. At the right is a graph of the biodiversity data (purple bar graph) and data on the recruitment of juvenile mussels in the genus Mytilus (yellow bar graph). Examining the mussel recruitment data reveals a dramatic shift in recruit abundance as you move along the coast. By combining data sets such as these with the World students will have an opportunity to investigate hypotheses relating recruitment data with
oceanographic data such as the Nitrate values for the same stretch of coastline plotted at the right.
THE SOFTWARE TOOL
The Ocean Science Discovery Data Center will be built around an exisitng software tool – World Ocean Atlas Viewer. This viewer currently displays data from the World Ocean Atlas 1998 (www.nodc.noaa.gov) and will be updated to include 2001 data. WOA Viewer was created by Dr. William A. Prothero (UC, Santa Barbara) and The New Media Studio (Santa Barbara, CA). The World Ocean Atlas Viewer displays 22 types of ocean data. The figure below is the Virtual Viewer display. Students can choose among data sets, which are displayed on the map and described in the text box. By moving the mouse over the map, students can determine the data under the cursor.
Students can rotate the map in order to simultaneously view a depth slice as well as the surface view. The depth view can display the same or a different data set relative to the surface data. In the figure to the right, sea surface temperature is displayed on both views.
Data sets include:• Sea Surface Temperature• Evaporation• Wind Speed• Global Dissolved Oxygen• Global Chlorophyll• Global Salinity• Outgoing Longwave Radiation
About the Data…provides definitions of the data sets.
The Slice Viewer plots data with at depth for virtually any “slice” across the ocean that the student draws with the cursor.
You have chosen to examine Dissolved Oxygen at depth against Global Chlorophyll data at the sea surface. What are your predictions about the relationship between these variables? Write your answers down before continuing with this exercise.
