Thesis (Ph.D.) - Indiana University, Department of Psychology and Brain Sciences and the Cognitive Science Program, 2021Every day, people are bombarded with information from various sources, and yet they do not have nearly enough time to process it. How do people sift through information and decide what to use, and what do they rely on to make these decisions? How do people respond to inconsistent or conflicting information? The goal of this dissertation is to investigate these core questions as well as their implications in education and business. To do this, my work takes a highly interdisciplinary approach that combines cognitive science, consumer behavior, information systems, and communication studies, using a blend of behavioral experimentation and computational cognitive modeling. I present three papers that examine the mechanisms people engage in when they integrate information displayed in different forms and from different sources in educational and consumer contexts. The first paper approaches learning statistical inference in an experientially grounded way by developing computer simulations. It reveals people’s flexibility to “game” the game, highlighting the importance of ensuring alignment between visual training and learning objectives in educational games. The second paper uses a computational approach to systematically reveal the common ways people ascribe meanings to the five-star rating system when shopping online. The findings suggest two ways to improve the interactions between reputation and feedback systems and their users: normalizing ratings with commentaries and normalizing ratings with clarification and education. The third paper demonstrates how people integrate ratings and reviews into their purchase decisions, and how these decisions can be influenced by the consumers’ justifications. It also unveils the role of information relevance and similarity in social cognition. These insights could be leveraged by different players in the market to influence consumer choice. By examining information integration in education and digital economy, this dissertation helps create a more comprehensive picture of how people generate, disseminate, and consume information. It highlights the mechanisms by which people integrate heterogeneous information to make inferences and decisions, as well as cues and heuristics they rely on to facilitate these everyday tasks. This expanded understanding informs the development of systems whose goal is to facilitate user navigation in the era of big data.