Cafaro receives NSF EAGER grant to study how causation and correlation are learned
August 30, 2018
Francesco Cafaro, assistant professor of informatics in the Department of Human-Centered Computing at the Indiana University School of Informatics and Computing at IUPUI, was recently awarded a $299,879 NSF EAGER grant for his research, “Aiding Reasoning About Correlation and Causation.”
The EArly-concept Grant for Exploratory Research (EAGER) supports exploratory projects that are in early stages and that “involve different approaches, apply new expertise, or engage novel disciplinary or interdisciplinary perspectives,” according to the NSF website.
Cafaro’s project will be conducted at Discovery Place, a science museum in Charlotte, NC, and will investigate how cognition theories can be used in designing interactive installations that improve people’s understanding of causation and correlation while exploring displayed data sets. The goal is to develop bridges between cognition, human-computer interaction, and long-term learning of STEM concepts found in the museum’s exhibits. The findings will inform the design of novel, tangible, and natural user interfaces for informal learning.
Three of Cafaro’s research assistants, Swati Mishra, Milka Trajkova, and Disha Bora, contributed to preliminary activities conducted over the summer and fall of 2017, in preparation for the grant work. Trajkova will continue this fall.
Davide Bolchini, chair of the Department of Human-Centered Computing, said, “We are very excited to see this project funded by the NSF. Such exploratory work exemplifies the foundational research that uniquely combines complementary disciplines—from embodied cognition to design science—to drive ‘high-risk/high-pay off’ research activities with great discovery potential. The interactive installation developed by Professor Cafaro and his students in Charlotte is an ideal living lab to bring to life and evaluate the ideas explored in this EAGER project.”
Causation and correlation are often confused, leading people to assume causality when there is none, although correlation can offer hints at causality. A simple example is the strong correlation between ice cream sales and number of drownings—both increase during the summer, but one does not cause the other.
The project will be conducted in four phases. In phase one, visitors will interact—using full-body or tangible interaction styles—with a visualization of geo-referenced datasets on a projected screen. The two different interaction styles are thought to prime people to use alternate mental patterns to reason about causation and correlation.
In phase two, the research team will experiment with different data visualizations—line charts or heat maps, for example—and in the third phase, visitors will personalize the displayed dataset. In the final phase, visitors will be asked to evaluate data-based claims several weeks or months after their visit in order to evaluate transferability of learning across time and to other contexts, such as a science article.
“This multidisciplinary work fundamentally cuts across the areas of cyberlearning and human-computer interaction. If successful, it will allow designers to craft interactive installations in which the ‘interaction’ facilitates people’s comprehension of what they see on the screen,” Cafaro said.
Learn more about Cafaro’s NSF award.
This material is based upon work supported by the National Science Foundation under Grant No. 1848898. 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.