This project will develop web-based knowledge-building environments for the collaborative creation of information landscapes: interactive visualizations that support the sensemaking individuals engage in online, and capture their efforts for the benefit of others who come after them. To guide and motivate the design of these environments, the research builds on theories of sensemaking, which describe the nested and parallel loops through which individuals seek out, analyze, and understand information, grounded in a rich history from organizational behavior, social and cognitive psychology, and human-computer interaction. It will extend theories of individual sensemaking to the situation in which an individual's processing of information for themselves is consumed by others, whose processing in turns improves the sensemaking of those coming after them - what can be called the "distributed sensemaking cycle."
Examining distributed sensemaking in a way that is both rigorous and environmentally valid is a challenging prospect, so this project will take a multi-stage approach involving laboratory studies to characterize the distributed sensemaking process and iteratively develop interfaces; "virtual lab" experiments harnessing crowdsourcing to evaluate these processes and interfaces at a larger scale while bootstrapping the system's value; and controlled field trials to test theories and interfaces in environmentally valid settings.
In order to capture the benefits and costs to both the producer and the consumer, the research will employ an experimental framework that elicits both of their perspectives. The general approach involves the producer using an interface for a sensemaking task and the consumer doing the same task but starting with the results of the producer's work. This approach will iteratively develop interfaces that help individuals forage for information, integrate the results of their foraging into information landscapes, and convey the judgments, decisions, and work they engaged in during the process to others.
The results of this research will advance scientific understanding across a variety of domains, including sensemaking, collaboration, schema induction, and interface design. The research has the potential to improve the efficiency of knowledge work, the training and practice of scientists, and the effectiveness of education. The tools developed in this research will be incorporated and evaluated in educational practice, and will become the center of a community linked to several existing knowledge bases.
