Teaching Data Literacy SkillsStudents Who Learn to Collect, Analyze, and Visualize Data Will Be Better Prepared for College and Work Demands
Data is everywhere. Collected, stored, open for the taking. Yet most of our society, workforce and students aren’t equipped with the best analytical tool kit to take in and process all this information. How do we keep from drowning in a data lake? And how do we go about teaching data literacy skills to our students to prepare them for the future?
Teaching Data Literacy
We’ve found that data analysis should be taught as a cross-curricular concept, stretching beyond Math coursework and extending into Geography, Social Studies, and Science.
Students need to understand, use, and communicate data effectively. Regardless of the subject matter, focus should be on consistently incorporating numerical or quantitative evidence in order to provide analytical opportunities for students. Much like a graph, there’s an increasing progression of understanding and sophistication of analysis with age and mathematical experience. Younger students start with simple bar graphs (a favorite activity of elementary aged children is graphing the variety of colors of M&Ms or Skittles found in a bag) while a higher level student would utilize tools such as Excel or Google Sheets to customize a unique graph from a data table.
As the content of data develops, inspire students to think beyond basic pie and bar graphs with colorful and interesting examples of displaying data such as the infographics seen here: https://datavizproject.com/
Young students must first learn to read a simple graph for correct and relevant information. Next, they can begin to create a graph based off of data provided. Once they understand how different data sets require varying design (a pie graph vs. a scatter plot, for example), they can further develop their data communication skills- how to take a set of numbers and design an infographic or visual representation to explain the data to others.
As the student enters college, they should feel capable of designing an experiment which identifies the data that should be collected, organize and provide a summarized, visual display of data, and finally make recommendations, solve problems, and form strategies based off this information. Only then will they feel confident to perform similar tasks in the workplace. Perhaps a student with a budding interest in data analysis can join the exploding profession of Business Intelligence and Data Science, highly skilled analysts who use computer algorithms and data lakes to extract important business information, report on consumer trends, and forecast strategies for all types of corporations and government organizations.
Project Data You Can Use
Inspire the next generation of Data Scientists by incorporating more graphing and analysis in your classroom. Scientific data is available to teachers and students on a myriad of platforms. Customize your lesson plans to incorporate the analyzation of significant and relevant numbers.
For example, a Science chapter on habitats and ecosystems can be made more engaging through the use of a free government open access data resource. Encourage a student to research their favorite animals’ environmental distribution using this site: USGS Biodiversity Information Serving Our Nation (BISON), and discuss and record the instantly generated data displayed through an interactive map. There’s also a growing trend in the Citizen Scientist platform such as CitSci.org or the app iNaturalist.org. Even simple field journals to record what types of plants and animals that live around the school and surrounding neighborhoods can be a teaching tool to collect and analyze data. By collaborating, researching, data collecting, and studying the results, students can gain a much deeper understanding and appreciation of the natural world and the impact people make on the Earth.
Another resource educators can access is SocialExplorer.com to visually supplement lessons in history, economics, public policy and geography.
High school teachers can engage their students in data collection and analysis through what these kids are already curious about. Tracking sports statistics, learning social media analytic tools, or charting sales and earnings of popular brands could be some starting off ideas for individual projects. Also, in the era of “Fake News” the ability to study published data to evaluate potential bias or inaccuracies is a terrific conversation starter regarding data manipulation in journalism and the media. Another method of incorporating data sets in everyday classroom discussion is as simple as a graph of which test questions were the most missed or grade distributions of a recent exam. The more students are exposed to data everyday, the greater their understanding of how numbers are communicated and displayed.
Big Data Needs Big Thinkers
Businesses and employers are demanding report generation and data understanding across all departments. It’s becoming easier for non-technical workers to create graphs and charts supporting business data, forecasting, and strategies. The new workforce will need to understand where the numbers are collected, what to learn from the dataset, and how to make decisions based off this research. By increasing data literacy, a student’s mathematical knowledge base is integrated across many subjects, and their confidence to approach problem solving grows. Their knowledge of data interpretation in a variety of college level subjects or professional projects is thereby strengthened too.
Data literacy is a crucial skill set for students learning in the “Big Data” age. Check out EVERFI’s Endeavor – STEM Career Exploration which offers a lesson on big data and the internet of things to introduce students to this type of thinking.
Incorporating data literacy strategies in the classroom from an early level will better prepare these future college students and business employees faced with an unending wave of information. Employers are demanding their workforce have the capacity to make sound business decisions based off of collected data. Let’s prepare our students for these data-driven challenges.