The Science Teacher: Big Data
As the editor says this month, “Scientific progress doesn’t result from simply accumulating data.” And data is definitely accumulating rapidly! Analyzing and interpreting data is one of the NGSS science and engineering practices, and how to organize, analyze, and interpret data (from students’ own investigations or from the work of others) and how to recognize valid conclusions from data are important if our students are to be informed citizens and potential scientists. (Career of the Month: Data Analyst).
It’s easy to find articles or news sites that summarize data and present an interpretation, but the editor continues: “…students can engage in the higher-order thinking involved in analyzing and interpreting large science datasets (big data) and designing their own inquiries to discover patterns and meaning in mountains of accessible data.” These data are collected by probes and investigators and are often streamed in real time. The featured articles in this edition focus on classroom strategies for investigations using secondary data.
- Thinking Big: Most students have had experience in data in their own investigations. But students and teachers also have access to large data sets via the Internet, from research projects and citizen science databases. The authors discuss the differences between local and large-scale data sets and how to transition to using “big” data in the classroom. The article has examples of strategies (provided in the Connections), a list of K-12 projects that provide big data, and suggestions for classroom projects.
One of the suggested projects that I am familiar with is NOAA’s Data in the Classroom. Each module has five levels of lessons ranging from teacher-presented ones to letting students explore the data to full-blown problem solving and invention. Each module shows the associated data in a variety of formats and guides the users through how to interpret it. There are “checkup” questions throughout, and teachers can download the materials.
- A Day in the Field introduces the term “secondary data”–data collected by others. Students studied a local estuarine system and shared their data with those collecting similar data at other locations. It was an authentic experience in using analysis tools such as mapping and spreadsheets. As the authors noted “Data analysis is about pattern recognition.”
- Harvesting a Sea of Data describes how students can study migration patterns using data from the Ocean Tracks research program. The project provides opportunities for students to study phenomena in faraway locations. (see also the Oceans of Data website)
Continue for Science Scope and Science and Children.