Developing Problem Based Learning with Undergraduates Using a Web-based Data Investigation Builder Software Tool Janice McDonnell1 , S. Lichtenwalner1, C. Ferraro1, K. Hunter-Thomson1, S. Glenn1 A. deCharon2, M. Mills1, C. Companion2, M. Crowley1, J. Wieclawek3 1Rutgers Institute of Marine & Coastal Sciences, 2University of Maine, Darling Center, 3Raytheon Web Services Poster #1965 The Data Investigation Builder Ocean observing systems (OOS) are advancing our understanding of the natural world by accumulating large quantities of data to address complex oceanographic processes. Utilizing these high volumes of data, for research and education increases both challenges and opportunities to analyze and synthesize these data into scientific understanding. The Data Investigation Builder (DIB) is a web-based tool to develop problem-based activities for undergraduate students that use real-time data to investigate real-world phenomena. DIB activities are intended to be delivered online and consist of student centered learning projects that demonstrate application of a science concept or theme that can generally be utilized within a single class period, or as a homework assignment. Each activity focuses on a core idea in oceanography and uses real data, including data collected from oceanographic instruments, results from numerical models, and laboratory studies. Activities can include animations and conceptual diagrams, providing context to the science concepts or processes that are relevant to students learning about the natural world. Data Investigation Builder Software Tool Interface Professor View Undergraduate Student View A suite of educational data visualization tools have been developed that allow undergraduate students to interact with data from a variety of ocean observing platforms in intuitive and engaging ways. The DIB address the elements identified by Edelson & Gordin (1998) for a successful problem based learning intervention including: Six pilot lessons have been developed to test the utility of the software. Currently a team of community college professors from the NSF funded Community College Undergraduate Research Initiative (CCURI) are partnering with OOI EPE to test the software. Motivating context Learner-appropriate activities Appropriate datasets Scaffolding interfaces Support for learning The Spatial Response from Hurricane Sandy The DIB interface has a series of steps to develop a data driven activity that allows students to explore evidence and address science questions. How does a data investigation “fit” into an undergraduate oceanography class? Learning Objectives In this section the professor identifies their student learning objectives (SLOs). Provide a Motivating Context Why should students care about this investigation? Why is this topic important? How is this investigation relevant to students' lives? Professors can develop an activity with a motivating context or story that spurs students’ interest in the content or helps them understand its relevance toward a larger societal goal. Provide Background Content Before beginning this investigation, what information should students know about or review? Professors provide some brief background information. In this activity, students study the ocean's response to Hurricane Sandy as it passed through the Mid-Atlantic and made landfall. Students analyze air pressure, winds, waves and sea level to describe the temporal and spatial responses. This framework describes how a data investigation from the DIB might be integrated into a typical undergraduate oceanography class. Data investigations can be part of a lesson. Units which are comprised of different lessons support different concepts and themes that comprise the course scope. Teaching with Data Teaching with scientific data provides an entry point for learners to engage in science and make meaning from observations.  Using data in our classes, lecture, and laboratories focuses learning on the process of science while capitalizing on new opportunities created by data sharing and web technology. The exponential growth in scientific data through programs such as the Ocean Observing Initiative (OOI) is providing exciting opportunities for scientists to mine data from sources well beyond their own university based research groups.  Often in the ocean sciences, phenomena of interest are too difficult and expensive for students to explore by direct experience in the classroom.  The OOI provides a critical service to bring ocean science data to the classroom for authentic learning experiences. We define Data-enhanced learning experiences, as including activities in which students collect and interpret their own data and those in which they explore research databases to answer questions. Data enhanced learning experiences can: Prepare students to address real-world complex problems; Develop students’ ability to use scientific methods, including consideration of the values and ethics of working with data; Teach students how to critically evaluate the integrity and robustness of data or evidence and of their consequent interpretations or conclusions; and Provide training in scientific, technical, quantitative, and communication skills. Manduca and Mogk 2002. Using Data in Undergraduate Science Classrooms (Grant NSF-0127298) Students analyze the datasets above to determine the impacts Hurricane Sandy had on the coast of New Jersey. They investigate each piece of evidence and answer the investigation questions on each page. After viewing all of the data, students continue to the Explanation page for instructions on how to answer the Challenge question. Students will justify their answer based on the evidence. Create a Challenge On this page, professors identify the research challenge their students will pursue. Choices include: Develop a conceptual model or diagram that explains the given evidence. Write up a description and analysis of the provided datasets. Construct a written explanation of the observed phenomena seen in the data. Develop a new question from a provided dataset. Identify Datasets to Explore The interface is used to add one or more datasets to the investigation. Datasets can include visualizations, concept maps, images, videos or documents like PDF or Excel files. Ocean Acidification Students develop a conceptual model that explains given evidence about the relationship between increased levels of carbon dioxide in the atmosphere and the physiological changes that are occurring in calcifying organisms. Software tools developed for undergraduate teaching using OOI data support students in developing evidence and reasoning skills.  This lesson encourages students to synthesize multiple data sources to explore and understand a scientific relationship. The student explanation can take the form of a concept map or written report that articulates the students understanding. Explanation Guidance This page is where the entire investigation comes together. Students are asked to answer the Challenge Question by summarizing or synthesizing the datasets they have investigated. The Education and Public Engagements’ (EPE) online data investigations, strive to help students develop strong argumentation skills by focusing on analyzing evidence and backing up their claims. By incorporating this framework of claims evidence, and reasoning for scientific explanation into EPE online exercises, instructional strategies, and assessments, we hope to build students’ conceptual understanding and improve their ability to think and communicate more scientifically. Join Us We invite you to help us build the best tools by joining our site today, playing with the tools, and letting us know what you think. http://education.oceanobservatories.org Kastens 2010 Oceans of Data Institute: http://www.oceansofdata.org