There are so many ways to engage your students in the discovery of a concept. Model-building (the 3D kind), simulations, and investigations are great ways to get students moving, to get them asking questions, making hypotheses, and testing their ideas. But let’s be real, we don’t always have the time or materials to use these practices. Sometimes, the clock is a real factor. Money for supplies is another one.
One of my favorite ways to engage students in discovery is through analyzing and interpreting data. There are a few benefits of using data for discovery. For one, the materials can be minimal. While you can certainly task students with obtaining the data (from web resources, for example), you can also simply provide the data to students if access to technology is an issue. Along those lines, you don’t need 20 basketballs and 5 lamps and 150 pieces of limestone and so on and so forth. You get the picture. While I love investigations and simulations and models, putting those into practice all the time can be overwhelming, and depending on your situation, simply unrealistic.
And it’s ok because you have data.
And Analyzing and Interpreting Data is an important Science and Engineering Practice.
Using Data Without Technology
As I mentioned, you can use data to guide discovery without any access to technology. In Resource Availability: Water In The Desert, I provide data to my students in several forms — maps, satellite images, photographs, and data tables. This approach obviously requires you to source the data ahead of time. For my stations activity, I actually dug it up from various sources — NASA’s website, research papers, Flickr photographs, and so on. But if you don’t have time for that, there are databases for educators that provide “ready to go” data.
NOAA has some great “classroom ready” resources here, while Data Nuggets has been a longtime favorite of mine for tying literacy and data into my lessons. Their resources are “student-friendly” versions of real scientific research, including data tables and graphs that are actually accessible to students. These can be printed ahead of time and provided to students, no tech required!
Using Data From Web Resources
That said, if you DO have access to technology, students can collect data for themselves from web resources. This approach involves students in a small way in Planning and Carrying Out Investigations. While they aren’t so involved in the planning, they are collecting the data. Subsequently, they are then analyzing and interpreting it.
In Exploring Climate Data With Climatograms, students are tasked with collecting temperature and precipitation data from assigned cities. They analyze this data by creating climatograms, and by examining the climatograms from different cities, they can interpret the climate data to categorize U.S. cities by their climate zone.
This activity could just as well be done without technology (and I do include that as an option, for those crunched on time). But adding that extra step of students obtaining the data themselves does, as I mentioned, incorporate another SEP in a small way.
Using Simulations To Collect Data
One last approach for incorporating data – without the hands-on investigations or model-building – is to use simulations. Simulations can be an easy way to carry out an investigation and/or test a model with reduced demands on time, materials, and money.
For example, in my Climate Factors: Latitude activity, students use a simulation to understand the impact of Earth’s tilt and the angle of incidence on the energy that reaches Earth’s surface. This activity brings in the Science and Engineering Practice of Planning and Carrying Out Investigations as well, as students must determine what evidence they will collect and describe how it relates to the question they are investigating.
The wonderful thing about simulations today is that there are SO MANY out there! PhET Labs, Concord Consortium, and PBS Nova Labs are a few resources I use frequently, but there are so many additional ones out there, too. They can serve as a great way to get students engaged with data to discover your content ideas.