When I was a child, around 10 years old, I pored over the annual publication World Almanac and tried to make meaning of the world through banks of data I found interesting, primarily information about sports and US presidents. I would skim the almanac for something interesting and then copy or reformat the data on either notebook or graph paper. By doing this, I began to make meaning of the data set: what was the maximum, what was the range, what was the average over the years? For a reason we scientists all understand better now, this pastime gave me great pleasure. I still like data: sports statistics, music statistics, and various science-related data. I guess I like looking for patterns. Now that I teach science, I also see the value in having my students gather and analyze data.
Part of the inquiry-learning model emphasizes course activities that involve collecting, organizing, and interpreting scientific data. Both the Benchmarks for Science Literacy (American Association for the Advancement of Science, 1993) and the National Science Education Standards (National Research Council, 1996) call on teachers to design courses so that students learn science by doing science: posing relevant, testable questions; designing appropriate protocols for investigating these questions; and assembling and deciphering the results of the investigations. In this way, educators promote the scientific literacy of all students. Some have argued that inquiry activities are aligned with how learners construct deep and lasting meaning from their educational experiences (Tobin et al., 1994; Bransford et al., 2000).
Here, I describe and summarize inquiry-based ecological activities that emphasize long-term data gathering. These exercises are appropriate for either high school or nonmajor college students. By long-term data, I mean data that are collected over several semesters, terms, or years, by different students in different courses. Although each data-gathering project includes other essential aspects of inquiry learning, such as forming hypotheses, developing experimental designs, and communicating findings, I focus here on the data-related components of the activities, in the hope that science instructors might develop their own projects that emphasize long-term data collection over many semesters, terms, or years.
* The Value of Long-Term Data Collection
Long-term data collection is critical to the scientific understanding of many ecological systems and provides insights into local and global environmental changes. Scientists are increasingly developing collaborative networks to gather and share long-term data that further scientific research. Efforts such as the National Science Foundation's Long Term Ecological Research Network (http://www.lternet.edu/) have enabled scientists to intensively track changes in 26 varied ecosystems across the United States (Hobbie, 2003). The US Geological Survey's North American Breeding Bird Survey (http:// www.pwrc.usgs.gov/BBS/index.html) has tracked bird populations since 1966 and has significantly contributed to our understanding of bird conservation (Valiela & Martinetto, 2007). Some long-term data-collection efforts involve "citizen scientists"--trained volunteer data collectors (including students) who assist scientists in gathering data. Some examples are the Community Collaborative Rain, Snow and Hail Network (http://www.cocorahs.org); the World Water Monitoring Day program (http://www.worldwatermonitoringday.org); the GLOBE Program (http://www.globe.gov/r/); and various projects sponsored by the Cornell Laboratory of Ornithology (e.g., the search for the Ivory-billed Woodpecker; http://www.birds.cornell.edu/ivory/). Such efforts provide meaningful information that can lead to scientific insights at many scales.
* Data & Inquiry Skills
Various state science standards either lump together or divide data-based inquiry skills (Illinois State Board of Education, 1997; Vermont Department of Education, 2010). …