Making Sense of Data: Identifying Children’s Strategies for Data Comparisons

ABSTRACT

The statistical properties of data are not present in any individual value, but rather, emerge only by perceiving the set as a whole. Summarizing the statistical properties of sets (e.g., creating ensembles) is ubiquitous in cognition, yet one unanswered question is how this process changes over development. The properties of number sets (e.g., means) provide a unique opportunity to investigate the mechanisms underlying summarization. We presented fourth (~ten-year-old) and sixth grade (~twelve year-old) children from the Midwestern region of the United States with a data comparison task, determining which of two golfers produced the farthest drive, and measured their accuracy, confidence, and eye fixation patterns while solving each trial. Children’s data strategies were identified by coding their eye tracking patterns. The results demonstrated that accuracy and confidence were related to the statistical properties of the sets. Older US children consistently used a strategy that demonstrated attention to diagnostic set properties (e.g., attending to most numbers in a set), whereas most younger children used a variety of strategies, many of which were less accurate (e.g., attending to only one number in a set) or used the same strategies less efficiently than older children (e.g., attending to non-diagnostic place values). The results add to our understanding of US children’s quantitative reasoning by identifying strategies children use to make sense of data, their developmental transitions, and how changes in children’s strategy use is a key component in understanding the developmental improvements in summarizing complex information in the environment.

Acknowledgments

The data that support the findings of this study are available from the corresponding author, BJM, upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15248372.2022.2100395

Notes

¹ Alternative instructions were piloted (e.g., Which is the better golfer? The best golfers can hit the ball the farthest. Based on these numbers, which golfer would you choose for your team for an upcoming tournament?). These alternative wordings led to the same response patterns suggesting that the use if the term “average’ did not materially alter task demands. We also collected self-report strategy data that is reported in the supplemental materials.