Illustration by Rhiannon Newman for the Urban Institute

How Data4Kids Helps Students Log on to Learn

When the COVID-19 pandemic first shut down in-person learning, we knew education wouldn’t be the same. How could kids — especially younger kids in elementary schools — learn and socialize if they weren’t in a real classroom? In late 2021, we worked with a team of people from various groups — including the Concord Consortium, Esri, Found Spatial, the American Statistical Association, the Launch Years initiative at the University of Texas at Austin, and faculty members at the University of Memphis and the University of Tennessee — to provide an open repository of data-related educational material for educators, which resulted in our Data4Kids project.

The question of how to teach kids about data in a virtual environment inspired us to host a four-day special in March 2020 as part of the Data@Urban Digital Discussion series, a daily video conversation with leaders in the data science field. The special series for children focused on how to create data visualizations, write code with Scratch, design map projections, and collect and analyze data. More than 200 children from around the world attended these one-hour live sessions. As kids enthusiastically engaged with us, we saw their hunger for more information, resources, and education.

With support from the South Big Data Hub (via the National Science Foundation), the Urban Institute and our partners created a set of tools and resources to help teach kids in primary and secondary school about data, data science, and data visualization in a virtual environment. We balanced our expertise in data science and data visualization with our partners’ expertise in conducting in-person and online instruction to children across the country.

Preparing the project

Although we are not professional educators, we believe analyzing and communicating data skills will be the currency of the next generation. As such, learning data science concepts is crucial. And as education at all levels increasingly turns to virtual teaching and virtual resources, we wanted to offer parents, educators, and students resources to help them along the way.

To conduct this work, we reached out to STEM educators across the country. We didn’t know exactly what form the final product would be, but we knew it would live on a webpage, be open source and free, and be a living, growing, and evolving project.

With help from our Urban colleagues, we identified 10 people and organizations to participate in the project and invited them to join one of two five-hour virtual meetings in mid-September 2021.

Collaborating across education fields to brainstorm

In our first meeting, we brainstormed what the final project might look like. We discussed how we might engage Urban researchers in the project, make the existing Education Data Portal more kid friendly, and create some kind of “data.gov”-type resource for teachers.

As we brainstormed, we acknowledged some of these ideas were too large to tackle within our time and budget. We also wanted to provide educators tools or resources they could easily use today — but not an information dump. Instead, our tool or resource needed to guide instructors through the concepts, data, and visualizations. Finally, our tool or resource had to engage kids at various ages — what are they learning, how do they learn, and how can educators most effectively teach these concepts?

We landed on “data stories,” or a series of educational resources around different topic areas. Each story would provide a starter kit for educators at different levels — grades 3–5, grades 6–8, and grades 9–12 — and include four primary components:

· data in Microsoft Excel, comma separated value, and Google Sheet formats

· a data dictionary in Microsoft Word and Google Doc formats

· teaching slides in Microsoft PowerPoint and Google Slides formats

· instructor guides that provide additional teaching resources and notes for each story in Microsoft Word and Google Docs formats

Despite already deciding on a path for our project in the first brainstorming meeting, we still needed collaborators’ help in the second brainstorming meeting to define the pieces of the stories and to help us set specific learning goals and an overall organizing principal.

Our second brainstorming session showed us yet another reason why our collaborators are essential — we needed educators to help us shape the content. As one of our participants mentioned, “Teachers need to know what a lesson is designed to teach. It doesn’t constrain them — it frees them to play with the lesson and decide how to best achieve that goal with their students.”

With the data story concept in hand, our second meeting focused on what content would appear in each story and how to structure the instructor guides. In this one meeting, we refined the guide to five main sections:

1. data question

2. data collection

3. data analysis

4. data visualization

5. data equity, ethics, and privacy

As a group, we felt these five areas defined the core tasks in a data analysis workflow. Each section includes a learning goal with sample questions and answers for each aggregate grade level. We also created separate data files for each grade band and a secondary dataset with errors that would prime students to inspect, analyze, and understand the data.

Prototyping the data stories

Guided by our concept, we created the first data story prototype about state-level food insecurity and related measures. Our story contained the four primary components for each grade band and sections. The teaching slides (figure 1) indicate which slides are for each grade band. We then repeat this information with additional notes in the instructor guide (figure 2).

Figure 1. Screenshot of “Data Question” slide for grade band I from the Food Insecurity Data Story.
Figure 2. Screenshot of the instructor guide that outlines the “Data Question” for grade band I from the Food Insecurity Data Story.

With our prototype as an example, our collaborators formed teams and developed data stories, such as who visits national parks, where the highest eviction rates are, and more. We hope parents and educators will use these stories to teach kids about data science.

But we’re not done yet! We’ve included an open form for possible future collaborators to contribute and pitch their ideas for more data stories. We have created templates in all the above toolkits so anyone can assemble a dataset, formulate questions and answers, and develop data visualizations to help educators around the world. We hope you will consider collaborating with us to provide more data stories and data science resources.

-Claire Bowen

-Jonathan Schwabish

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