How to teach data storytelling in the history classroom
Throughout modern history, visionaries have understood the power of data. Ida B. Wells recognized it when she scoured newspapers to compile data on lynching throughout the American South, and Florence Nightingale knew it when she visualized the number of preventable deaths caused by unsanitary hospital conditions during the Crimean War. Neil Halloran certainly understands it when he builds and narrates his data-driven documentaries, films such as The Fallen of World War II. A common insight shared by these data visionaries is that it’s the stories within and beyond the data that hold power—not just the data itself. As teachers, if we want to help students harness the power of data, we need to help them unlock their own storytelling potential.
But why should we teach this in history? Isn’t it enough to teach students to analyze data visualizations and pull information from them? This analysis is important, to be sure. We certainly want students to be able to watch The Fallen of World War II and identify the number of military and civilian casualties in the Soviet Union, or deduce that of all the war’s participants, Poland lost the greatest percentage of its population. However, numbers or percentages alone can obscure the people they represent, and by themselves can fall short of communicating a complete picture of the past. Numbers can be easy to forget; stories stick with us. This is one reason that historians often communicate through historical narrative. Storytelling is a key part of understanding history because it gives structure to the past. We’re more likely to remember stories than disconnected dates, places, and statistics.
Storytelling in The Fallen of World War II
With The Fallen of World War II, Neil Halloran offers a master class in using elements of story to make meaning of historical data. He establishes the spatial and temporal setting for his audience (the European and Asian Theaters during the Second World War), and he helps orient us in time, noting the current age of those who would have seen a battlefield during that war.1 This is one of several ways he humanizes the data central to the story. Throughout the documentary, he shows us vivid photographs of the men, women, and children behind the numbers. Even his use of human symbols to represent the data serves as another reminder that these are people, not just numbers.
After a brief introduction, Halloran sets up the theme of his story, stating, “We're going to tally up the tens of millions of people whose lives [were]e cut short by the war and see how these numbers stack up to other wars in history...” From there, we’re confronted with the central problem that drives the story: he gives us the number of US war casualties—the first of several such statistics. Then the plot unfolds with the story’s focus shifting from countries’ total casualties to particularly deadly battles and events, with the sequence of events occasionally displayed on a timeline to help viewers see the continuous yet changing buildup of casualties. By the end of the documentary, as Halloran compares the deaths in World War II to deaths in wars since its end, we are left with the feeling that perhaps we, not just the soldiers, are characters in the story who are left to help determine what the story’s resolution might be.
Students might not produce a data-driven documentary like The Fallen of World War II, but they can tell stories with data. In doing so, they can practice writing historical narratives. Often, when students encounter data visualizations in multimodal texts or research projects, they find them complex and overwhelming. Even with relatively simple data visualizations, they might pay attention to overall trends while ignoring more subtle—yet important—details. Data storytelling not only helps them make sense of data visualizations by encouraging them to account for details, it also encourages them to see through the data to the people they represent, and beyond the data to the contextual factors that are shaping it. As with any story though, the hardest part is getting started. My solution is to use a technique called “story starters.” Let’s look at an example.
Scaffolding data narratives: story starters, questioning, and research
This Our World in Data graph on life expectancy since World War II shows an overall trend of increasing life expectancy worldwide and in different world regions from 1950 to 2023 (I’ve added the United States to the default graph as a reference point for students.) This, by itself, is a good story about advancements in medicine, public health, and technology. However, this graph includes a few other stories worth telling. First, there are sharp dips in life expectancy in Asia around 1960, in Africa in 1994, and throughout the world around 2021. In addition, Africa’s average life expectancy remains consistently lower than all other regions and is below the world average. Asia’s is below the world average until 1990. Any one of these stories is ripe for further investigation. However, in the example below, I focus on dips in life expectancy. My goal is to have students use this graph to investigate the causes of the drops in life expectancy and write a narrative explaining the events behind the numbers and how it affected the people involved.
Here’s how this looks in the classroom:
- Before students write their first data story, I always have them watch The Fallen of World War II so we can discuss the elements of storytelling Halloran uses, including the ways he humanizes the data.
- It’s important that students are able to extract basic information from the graph they’re using to tell the story, so depending on students’ data-literacy skills, you might also scaffold with an analysis activity like Level 1 and 2 hierarchical questioning.
- Next, give them the story starter. Ideally, the story starter (a) models how to set up a problem or challenge (for example: Despite rising average life expectancy, there have been moments of sharp decline.); (b) has blank spaces for them to fill in so you can assess their background knowledge and skills; and (c) gives them space to complete a good portion of the story. Ask students to fill in the blank spaces on their own, and then discuss. Here’s an example:
In 2023, life expectancy for the average child in the world was 73 years. That means that the average child born in 2023 could expect to live to 73 if the average age of death at the time did not change over their lifetime. This was a significant increase since 1950, when the world’s average life expectancy was only 46.4 years. This overall increase in life expectancy is largely due to ______.
Notably, life expectancy is not the same everywhere. If you were born in the United States in 2023, your life expectancy was higher than the world average, at around ______, but if you were born in Africa, your life expectancy was much lower, at just under ______.
Despite rising life expectancy since 1950, several regions have seen sharp drops in life expectancy at moments in time. In Asia, for example...
- Next, ask questions to make sure they can identify all the key story elements, and talk about how they want to weave the elements into the narrative they write to finish the story starter:
- What’s the setting? Where does the story take place? Over what time period?
- Who are the people the data represents? Or who are the people affected by the data?
- What are key events or observations they’ll want to include in their story? Make sure they write them in chronological order. NOTE: At this point, I don’t have them conduct the background research on these observations. I just want them to identify those they’ll include.
- What’s the main struggle, problem, or challenge presented by the data?
- Is there a theme or main message they can gather from the data?
- Finally, students should conduct research on the observations they’ve identified to include in the story they write to complete the story starter. They should learn about what was causing the changes, who was involved, and what the impact was. If possible, ask them to search for images and eyewitness accounts to include in their story.
Even with a story starter, this process will likely require multiple drafts. The first draft might focus on ensuring students can write the story—that they’re able to explain what they see in the graph. The second draft might incorporate the explanation of events. Finally, the third draft might focus on further humanizing the story by incorporating images and quotes from eyewitness accounts. No matter your process, data storytelling will enable students to walk away with a clearer understanding of what the data means and a better picture of the people the data represents than analysis alone would have provided.
No matter which version of OER Project: World History you teach, you can try out data storytelling in your classroom! You’ll find The Fallen in Origins Lesson 8.6, 1200 Lesson 7.8, 1750 Lesson 7.6, and AP Lesson 7.7. We’d love to hear how it goes—share your feedback in the community! And for more strategies and resources, check out our Data Literacy Guide and our Data Literacy page.
1 However, you’ll want to point out to students that the video was released in 2015, so the math has changed!