Data-driven decision-making is a necessary lifetime skill. Many professions require people to use data and data analytics daily, and data science supports our lives outside of work, too—from deciding where to live to tracking our fitness goals.
As a result, there are movements to update and improve the teaching of data science in schools and create additional data standards, particularly in middle and high school. But starting at a young age, students need to be able to collect data, organize it, make sense of it, and communicate it. As elementary teachers plan for the school year, teachers can bring data science into the classroom in meaningful and effective ways.
6 Ways to Bring Data Science Into Your Classroom
1. Connect data science to the content you’re teaching: Think about ways to incorporate data tasks and discussions about data into your existing instruction. As students move from kindergarten to first grade, they are learning how to count. In addition to practicing routine skills, such as counting groups of objects, use real-world data and displays to help contextualize these concepts. You might have these students collect rocks on the playground, sort them by color or shapes, and then make a display to represent each group.
In second grade, when studying measurement, children can measure their pencils using appropriate tools for the grade and then make a bar graph of the different lengths.
2. Weave data throughout many subjects: Teaching about data and building data literacy doesn’t have to be limited to math or science instruction. Elementary classrooms have a unique opportunity to look for occasions to leverage data when teaching all subjects. When teaching a social studies unit involving transportation, for example, consider surveying students to see what modes of travel (such as walking, riding in a car, taking school buses, or using public transportation) students use to get to school. Making a tally, chart, or graph to visualize the differences would contribute to understanding.
Transportation applications span from pre-K to first grade, when students explore how people move from place to place, and up to fourth and fifth grade, when students see how historical advances in transportation affect community businesses. Keep in mind that when information relates directly to students’ lives, their interest grows.
In the early-grade example, a student might observe from a bar graph that most people ride in a car and only a few walk. A teacher can ask questions about why that might be the case. Students might relate to living very close to school, where walking is a short distance. Their friend lives a long way and needs to ride in a car. That is easy for them to understand because it is concrete and what they do every day. That understanding would help when talking about other vehicles, like trains and airplanes, to cover even longer distances.
3. Rearrange routines: Sometimes using a different perspective helps students understand the significance of the information. They more clearly see the mechanics of how the model is built. For example, consider reversing the typical process: Instead of gathering data first and then looking at a graphic, give a graphic first and ask students what they observe. What do they notice? What do they wonder? What facts can they discern from the representation? Students often observe features that show surprisingly deep insights. Rich conversations and great learning can follow.
For example, a fourth-grade teacher could give students a graph that recorded different thumb lengths in inches when the class is using line plots, measurement, and fraction standards. Typical observations and questions would cover the population of whose thumbs were measured, whether people were the same ages, and if people with same thumb lengths were the same height. This could also be done with a science or health unit.
4. Let students direct their own learning: Instead of giving students a set of numbers to arrange into a particular chart in a particular way, let students discuss and determine how to organize the data. With a collection of seeds for science class, students may group them in different ways (color, size, shape) and express characteristics in different formats (pictograph, line plot, or bar graph). This presents a great opportunity for interesting data discussions, a comparison of information observed, and the chance to analyze strategies used.
5. Represent data in different ways: When students are confronted with a series of numbers, they may have difficulty making sense of them. Visual representations of data are often easier to comprehend; different types of graphics can trigger distinctive features. Patterns, trends, and outliers may be more clearly visible in tables, bar graphs, and other types of visuals. Vary options or give choices. Some will register better with one student than another or be more applicable in a situation.
For example, students could survey each other about their favorite colors, tally the frequency of each choice, write the number represented by the tally, and then make a bar graph representing the class choices. The tally helps students keep track of the count, the number quantifies the amount, and the bar graph easily identifies the most frequent choice by length.
6. Ask critical questions about data to drive learning: Quantity questions begin early as children determine “how many.” By third grade, students find “how many more or less” are in a category and find measures from a scaled chart. In fifth grade, students learn to “even out” objects in groups and level distributions so that categories become equal. You can also try adding questions beyond quantity about sources of data and methods of collection and implications of findings, especially in upper elementary grades.
For example, in the transportation problem above, asking about who gave the data and whether the results will be the same from different groups will help students begin to evaluate data relevance and predictability; will walkers have different perspectives than those who ride the school bus? Qualitative questions can go a long way in creating discerning data users.
Teachers can find plenty of other resources to learn more about bringing rich data science instruction into the classroom. Among those are the American Statistical Association’s recent Pre-K–12 Guidelines for Assessment and Instruction in Statistical Education II (GAISE II) and the data science section in the California Mathematics Framework.
Don’t be afraid to give data science a try in your classroom. You don’t have to embed it in every lesson. That can be overwhelming. But slowly, over time, you just might find there are more opportunities to develop these skills than you realize. I have no doubt your students will thank you for it.