Cutting Edge > Data, Simulations and Models > Workshop 02 > Program Guide

Program Guide

This program guide is designed to help link workshop content to resources available on the web in order to facilitate effective teaching in a data-rich environment. Participants are encouraged to preview the on line resources connected with this workshop so that they may enhance their workshop experience. For each part of the workshop program, this guide provides links to web pages, papers, data sources and examples illustrating the topic at hand. Use this guide to prepare for the workshop, to help you integrate global data sets into your teaching, or to share this information with colleagues. This guide is intended to be growing resource; we encourage you to contribute additional examples of data sources, tools or examples that should be added to these lists.

8:30 - 9:30 am

The Value of Teaching with Data: Insights from Learning Science (PowerPoint 310kB Mar23 04)
Danny Edelson, Northwestern University

Current, widespread educational techniques do not match our goals for students in our science classes. We want them to have deep understanding of fundamental science, and we want them to understand the process of doing science. Research and theories from the Learning Sciences provide us with frameworks for thinking about how and why to integrate opportunities for students to conduct investigations with data into science courses. The Learning-for-Use framework (Edelson, 2001) is one such framework. It emphasizes the need to

  1. Build interest-based motivation for specific learning objectives on the part of students
  2. Provide students with opportunities to construct understanding through a vivid combination of direct and indirect experiences, and
  3. Reflect upon and apply their understanding in meaningful contexts.
In this talk, I will present the Learning-for-Use framework and its grounding in cognitive science research.



Blumenfeld, P. C., Soloway, E., Marx, R., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating Project-Based Learning: Sustaining the Doing, Supporting the Learning. Educational Psychologist, 26(3 & 4), 369-398.

Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (1999). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press.

Edelson, D. C. (2001). Learning-For-Use: A framework for the design of technology-supported inquiry activities. Journal of Research in Science Teaching, 38(3), 355-385.

Gordin, D. N., & Pea, R. D. (1995). Prospects for Scientific Visualization as an Educational Technology. Journal of the Learning Sciences, 4(3), 249-279.

Linn, M. C., & Hsi, S. (2000). Computers, teachers, peers: Science learning partners. Mahwah, NJ: Erlbaum.

9:30 - 10:15 and 10:15 - 11:00 am

Tools and techniques

Workshop leaders are presenting the techniques they have developed for successful adaptation of global data sets to a classroom setting. They will share their experiences about the successes and pitfalls of creating learning materials for a data-rich environment. Topics may include how to establish learning goals, the design elements that are most effective, access issues, ability to learn about and master the use of tools, how to design exercises around the data, and what class outcomes might be. Participants will be able to work closely with the leaders to gain insights about the tools and discuss the techniques and technology. This session will be presented twice so that participants can learn about 2 of the 4 tools. We encourage workshop participants to become familiar with the resources that will be discussed. More resources are available at the NSDL Using Data Tools Collection.

11:00 - 12:00

Using data to teach geoscience thinking

This session will address how we use data to help students think like scientists. Many educators feel passionately that it is important to engage students with data as part of teaching science. Some insist that it is critical that students solve authentic questions with real data. Others want students to have the experience of collecting data and using it to answer a question. Why do we want to use data in the classroom? Is work with data necessary to inculcate scientific habits of mind? Why do we think it is important? What learning goals are supported in this way? Is using data an essential step in promoting discovery- and inquiry-based science? How does it affect student's knowledge base, skills or attitude toward science? Discussion of these topics is taking place in the NSDL Using Data Portal.

Jim Hays
Exploring climate data sets (e.g, radiation, atmospheric and oceanographic) can help students think differently about climate system processes than they do if they read or are told about them. These data sets are often most useful for student problem solving, particularly in groups. We will explore how several data sets can be accessed and what kinds of processes students can learn from them.

Hays, Pfirman, Blumenthal, Kastens and Menke (2000) Earth Science instruction with digital data: Computers and Geosciences v. 26 p. 657 - 668

A wide range of classroom activities that employ the use of data can be found in the NSDL Using Data Examples and Activities Collection. These examples cover audiences from elementary school through graduate school, and are drawn from a variety of topics within the earth sciences. In some cases the exercises involve the collection of data as well as the interpretation. Other examples use existing data sets that are imported and manipulated. In either case, the pedagogy relies on the use of "real life" data within the lesson.

1:00 - 2:00

Effective teaching practices

This session addresses the practical and pedagogical issues of developing and using data-rich classroom materials. The NSDL Using Data Pedagogical and Practical Issues Collection provide a wealth of background information on instructional design, inquiry-based learning, pedagogical philosophies and establishing goals and outcomes.

Mike Taber
So you want to use data in your teaching? What else must be considered as part of your instructional plan?

Data provides a rich opportunity to engage students in the fundamentals of inquiry. Most non-majors recite scientific inquiry as the "scientific method," and fail to recognize critical components such as, observation and exploration and the power of methodical trial and error. Most non-majors lack the technical skills associated with analysis tools (even Excel!) necessary to fully explore data. Learning goals must link inquiry objectives, content understanding, and technical skill development. The Learning For Use design method is utilized as the framework for design of the student's learning experiences in two courses: Principles of Scientific Inquiry (40 students) and Introduction to Geology (250 students).

Data on a self-assessment of inquiry methods from students in Principles of Scientific Inquiry will be presented. Pre-post data on the inquiry skill development of students throughout a course project will also be presented. Results from the self-assessment and the pre-post skill development provide an opportunity to rethink course design, the planned (and largely, unplanned) use of data, and the overall pedagogical delivery of objectives.

Derry, G. (1999). What Science is and How it Works. Princeton University Press. 309pp.
Edelson, D. C. (2001). Learning-For-Use: A framework for the design of technology-supported inquiry activities. Journal of Research in Science Teaching, 38(3), 355-385.

2:00 - 3:00

Evaluation strategies

In all types of teaching and learning, it is important to establish clear goals and means of evaluating whether those goals have been reached. With inquiry-based learning, student assessment may be less straightforward than a traditional quiz or exam. These presenters will discuss strategies for assessment of student work in data-rich learning activities.

Danny Edelson
Assessment with process-oriented rubrics: A developmental approach
An important challenge for evaluation and assessment is tracking students' learning over time. This is particularly difficult when looking at skills, rather than factual knowledge. I will be presenting an approach developed by assessment researchers at Berkeley that enables instructors to track students' abilities over time using rubrics that capture process skills.

Roberts, L., Wilson, M., & Draney, K. (1997, June) The SEPUP Assessment System: An Overview. University of California, Berkeley: BEAR Report Series, SA-97-1. (available at http://bearcenter.berkeley.edu/publications/Overview.final.pdf)

More resources and discussion can be found at the DLESE Assessment and Evaluation page (which is still in prototype form).

3:00 - 4:00

Activity plans

A major goal of this workshop is to help you create a plan for an activity for your own classroom. To preview the work we will do in this session, investigate the instructions and report form. We hope you will come to the workshop with an activity and data-set(s) in mind to work on.

The quantity and diversity of data sets available on line can be staggering, but there is certainly one or more that will align with your interests and that of your classes, and may spark the creativity needed to develop new learning materials.

The NSDL Using Data Data Sets and Tools Collection provides many examples of data sets that you might use. These include numerical, graphical, GIS, and image data sets as well as data sets that combine these elements. Data sets are grouped by topic, type of data set, and the level of scientific background knowledge required to use the data.

4:00-4:45

Final discussion

Additional Resources

Discussions of using global data in the classroom are ongoing on the NSDL Using Data Discussion List.

This program guide draws upon resources in the NSDL Using Data Portal. created as part of the NSF NSDL grant for Core Infrastructure to UCAR.

The DLESE Community Issues and Groups Using Data site provides a centralized location for obtaining information on activities addressing Using Global Data Sets in the Geosciences

Another session taking place at the AGU Meeting of interest to educators and related to Using Data: Using Global Data Sets in a Local Context.


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