The Quantitative Reasoning Skills Audiences Need to Understand News Reports
Recent research from Knology investigated the kinds of quantitative reasoning skills audiences need to make sense of news reports in four topic areas.
Knology researchers have been studying the ways numbers and statistics are presented in news stories. Recently, we published a paper in collaboration with our colleagues at PBS NewsHour that assessed the amount of quantitative data presented in various media sources, and the kinds of quantitative reasoning capabilities that audiences would need to make sense of the information they are presented with.
The paper, titled Surveying the Landscape of Numbers in U.S. News, appears in the first 2022 issue of Numeracy. For this study, the researchers compiled 230 news reports across four topic areas that typically use a lot of quantitative content - health, science, economy, and politics. These stories, which were collected using Google News, came from 74 different news outlets and included a mix of text and video formats. From this dataset, we hoped to understand how often stories in these areas require audiences to apply quantitative reasoning skills and in what ways they need to do so.
What follows are the research questions that we asked and what our analysis of the news reports showed.
How much quantitative reasoning do “typical” news stories require from readers? About two-thirds of the stories in the corpus required audiences to know why data are needed and how they are produced, and to have some knowledge of descriptive statistics. Less than half of the stories required readers to be familiar with probability and inferential statistics, while only a tenth required some familiarity with data visualization.
Are there differences between different types of stories?
Economic and health news stories required the most quantitative knowledge to interpret stories. Almost all stories in these two areas required audiences to know why data are needed and how they are produced, and familiarity with descriptive statistics. However, we didn’t see any differences between legacy and digital-first outlets or between text and video.
What relationships, if any, exist between the conceptual/story level and the sentence or clause level?
We assessed the quantitative content that appeared in individual clauses in news stories, as well as what quantitative reasoning skills they would need to make sense of the story as a whole. Overall, stories with more quantitative content in each sentence also required more complicated conceptual understanding. The more interesting finding is that sentences with quantitative content generally fell into two types: those that reported magnitudes (often official statistics) and the methods for estimating those magnitudes; and those that reported comparisons between probabilities, percentages, averages, and other such quantities.
Our findings raised some interesting questions about the editorial decision making behind choices to include or exclude quantitative information from news stories. Future research studies could explore questions such as why do economic stories with obvious human interest angles focus mostly on reporting numbers or why do science stories which require complex calculations at many levels focus mostly on human interest angle?
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About this Study
This research is supported by the National Science Foundation under Grant #1906802. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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