A recent paper published in Numeracy, by Knology and our NewsHour colleagues, offers a research agenda for studying the relationship between journalism and adult quantitative reasoning. In short, news media can play a big role in improving quantitative reasoning among US adults who are not in school. Learning quantitative reasoning from the news also offers a way to level the playing field particularly for students who previously may not have been exposed to statistical topics and concepts during their time in school.

Outside of school settings, prior research shows that US adults regularly encounter opportunities for quantitative reasoning when they consume news media. Some of the work referenced for this study found that there is quantitative content in up to half of all news stories. Further bolstering those fundings, we also examined stories that were produced by PBS NewsHour in a two-week period including content for broadcast and web. Out of 152 stories, a little less than half required at least some understanding of statistics.

Two recent news stories are described in the paper from the distinct perspectives of journalist and researcher. The first focused on the math underlying specific musical hits. It covered statistical concepts such as measures of central tendency, trends over time, outliers, and mathematical models from political science. A second story looked at how institutionalization impacts migrant families and children. Making sense of this story required understanding several statistical concepts, many of which were explored within the text, as well as some details about how the studies were conducted.

The need for statistical reasoning became particularly evident in 2020 with the emergence of COVID-19. The ensuing confusion in the early days of the pandemic provided fertile ground for misinformation about things like infection rates and access to testing to spread. For journalists at NewsHour, combating misinterpretation meant adding caveats to official numbers they included in their reports as a way to suggest that these figures were subject to change as more information became available. At that point in time, official numbers were known to underreport the prevalence of COVID-19 in the US public. When members of the public were asked to comment on variations of a story that included details about the number of cases, audiences who say the caveat language gave higher estimates for the number of cases compared to those who saw a version of the story that didn’t include caveats.

Let’s Put it to Work

For Journalists: It is critical for adult audiences to understand what numbers reported in the news mean, which numbers to trust, and how to use those numbers in their personal lives. Outside of school settings, news media is where most US adults are directly exposed to statistical information and quantitative reasoning. The task for journalists is to find ways to communicate the numbers in their stories in ways that audiences can understand and that are accurate. To help with this, Knology is publishing a series of articles that explore whether different ways of reporting on numbers and of visualizing numbers improves public understanding of statistics or judgments of news credibility.

For Researchers: The paper lays out a research agenda and we hope others will work with us to answer some of the questions that we lay out. There are several areas that are open for further study. In terms of adult quantitative reasoning, can quantitative reasoning be increased through informal activities? Also, how accurate are adult’s perceptions of their quantitative reasoning? Other questions could explore the attributes and affordances of news. For example, what attributes and affordances of news content are associated with greater quantitative reasoning? Researchers could also explore potential differences in quantitative reasoning among adults who consume news from different sources.

Funding

These materials were produced for Meaningful Math, a research project funded through National Science Foundation Award #DRL-1906802. The authors are solely responsible for the content on this page.

Photo credit: Chris Liverani on Unsplash.