Curt Stevens, Ph.D. Thesis in Computer Science University of Colorado at Boulder
Large information spaces present several problems to people searching for interesting information including information overload. This thesis describes a novel approach to handling overload problems in the domain of Usenet News, an open access computerÜbased bulletin board system that distributes messages and software. A conceptual framework is developed that shows the need for (a) flexible organization of information access interfaces, (b) personalized structure to deal with vocabulary mismatches and individual information needs, and (c) semi-autonomous agents that assist in creating this personalized structure. In addition, an operational system (INFOSCOPE) instantiates this framework allowing for the exploration and evaluation of the approach in realistic working environments. Using INFOSCOPE, Usenet readers evolve the predefined system structure to suit their own tasks or semantic interpretations. Agents assist users by suggesting filters based on observed interest patterns. Evaluation of the system indicates that (1) personalized structure is quickly adopted and effectively used; (2) personalized structure reduces information overload caused by uninteresting messages; and (3) INFOSCOPE agents are an effective aid to the creation of personalized structure in Usenet News. However, user studies have exposed deficiencies in the current implementation that indicate a more sophisticated suite of agents could increase the usefulness of many suggestions.
Curt Stevens, Post-Doctoral Research Project, University of Colorado at Boulder
We are developing conceptual frameworks, system architectures, and domain-oriented knowledge-based design environments in support of learning on demand. Our approach exploits the power of high-functionality computer systems in a project-oriented learning environment for undergraduate students (in computer science as well as in other related disciplines). We are placing special emphasis on integrating working and learning and on supporting self-directed and group learning, and these issues will be studied and evaluated in a naturalistic setting. Information overload, the advent of high-functionality systems, and a climate of rapid technological change have created new problems and challenges for education and training. New instructional approaches are needed to circumvent the difficult problems of coverage (i.e., trying to teach people everything that they may need to know in the future) and obsolescence (i.e., trying to predict what specific knowledge someone will need in the future). Learning on demand is the only viable strategy in a world where we cannot learn everything. It is a promising approach for the following reasons: (1) it contextualizes learning by allowing it to be integrated into work rather than relegating it to a separate phase; (2) it lets learners see for themselves the usefulness of new knowledge for actual problem situations, thereby increasing the motivation for learning new skills and information, and (3) it makes new information relevant to the task at hand, thereby leading to better decision making, better products, and better performance.