An Exploration of Distributed Parallel Sorting in GSS

Abstract

When the members of a group work collaboratively using a group support system (GSS), they often "brainstorm" a list of ideas in response to a question or challenge that faces the group. The satisfaction levels of group members are usually high following this activity. However, satisfaction levels with the process almost always drop dramatically when the group is forced to sort, distill, or classify all of the brainstorming feedback in a synchronous, serially-conducted activity, held immediately after the brainstorming activity. Past explanations for the drop in satisfaction often point to the increased time required to complete a sort and to the mental difficulty in sorting large lists (i.e., increased "cognitive load"). The experiment conducted in this study was designed to expose the participants to conditions featuring different levels of cognitive demand, achieved by varying the number of items to be sorted. This design simulates an asynchronous method of sorting group feedback - a process that can be viewed as a "distributed parallel sort." This dissertation explores methods for measuring the cognitive load experienced by a participant during a sorting activity (using the NASA Task Load Index), evaluating the effectiveness of having group members sort partial lists of items instead of working synchronously on the same full list (objectively measured using normalized clustering error against a "gold standard" result), and proposes new methods for mitigating the drop in satisfaction levels that regularly occur in these collaborative settings without compromising the effectiveness of their sorting results. The experimental results imply that an individual's perceived difficulty of the task may rely on other factors, rather than just the length of a list. The results also imply that the NASA-TLX framework to measure cognitive load may need to be refined further (or implemented differently), if it is to be used in GSS research contexts. Finally, two methods are proposed (a facilitation-based recommendation and another technology-enabled option) that may help to mitigate the drop in satisfaction levels, improve a group's effectiveness, and reduce the time required for that group to effectively sort their feedback in collaborative GSS sessions.