Interaction behind the scenes: Exploring knowledge and user intent in interactive decision-making processes

Abstract

Logging user interaction data with computational artifacts can be handy in identifying activities and issues associated with interactive decisionmaking processes. However, while such data commonly results in a temporally linear construction, information involved in such processes is not well structured from a knowledge engineering perspective. Consequently, both its consumption and understanding are not straightforward processes. Considering highly immersive environments with interaction through multiple modalities, the tracking of such knowledge becomes even more complex. Such environments have been increasingly used to support decision-making practices, which may involve cognitive-intense activities and critical thinking. Inferring concepts and knowledge from logging data in such activities is key for improving design of decision support systems, and general systems as well.