Students in the Computational Cognition Laboratory conducted a group project focused on creating a framework to conceptualize and model cognitive processes during typical decision making tasks. Our study explores how decision-making differs depending on whether there is an objective, correct response or whether one is expressing a personal preference. Importantly, this project combined standard choice responses with innovative mouse-tracking and eye-tracking data recorded throughout each decision among several popular snack foods. The research was conducted by having participants complete 120 choices in each of the two task types, by making every pair among 16 snack foods that varied on their healthiness and other features. They were asked for their preference: with which food they would like to (actually) leave the study. They were also required to learn nutritional scores for each food and then to identify the food with the healthier score. They rated their overall liking for each food, provided ratings for each food on each of five attributes (e.g. taste, healthiness), and then rated the importance of those attributes in typical snack decisions before either choice task. Our results suggest that participants approach the two task types differently and show inconsistencies between snack food ratings and choices. As a group, despite our varied experience in research, we contributed to creating a project that continues to expand the methods used to understand decision making. This project combined the two different tasks of preferential choice and identification and is the first to include all the process-tracing methods we used. This also allowed us to learn about these methods and go beyond just survey choices or simple choice tasks.
Authors: Allie Vo, Kat Pikus, Emma Moughan, Sarah Lett, Chi Vo, Vasudha Sarvagya, Ryan Bruder
Advisor: Joseph Johnson, Psychology
Graduate Advisors: Elizabeth Pettit, Lauren Davidson
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