Their winning paper was entitled "The Positive Effects of Verbal Encouragement in Mathematics Education Using a Social Robot." Brown is a Ph.D. student in the Human-Automation Systems Lab, which is led by Howard.

Studies have shown that using verbal encouragement strategies in education helps to maximize learning. This idea is derived from traditional classroom settings where teachers use behavioral strategies to maintain student engagement. Motivated by these educational practices, Brown and Howard have examined using a Socially Interactive Robotic Tutor (SIRT) that incorporates a variety of verbal cues into multiple math learning scenarios.

In their paper, Brown and Howard present the robotic tutor, the methods used to engage students in the learning scenario, and results from integrating the robotic tutor in the classroom environment. Results derived from 44 students engaging with SIRT during a tablet-based math test show that, when compared to non-interactive methods, verbal cues are able to increase and/or maintain student engagement regardless of student age and math content level.