Abstract
Getting a large audience to actively participate in a lecture is a challenge faced by many lecturers. The value of active participation is well supported in current research with significant contribution made by the introduction of electronic response systems (ERS). ERS allows each member of the audience to participate by using a hand-held device (like a TV remote control), responding to (usually) multiple-choice questions presented on a board. This article is introducing a new approach to the use of ERS, making the audience engage in a decision- making process based on multi-attribute utility theory (MAUT), a commonly used theory in decision making, aiming to: • Help conference participants, in a large group setting, prioritize suggestions and action items developed over the previous days of a conference, drawing on discussions held in concurrent, small group break out sessions. • Organize those suggestions/items into a prioritized list that reflects the discussions and honors individual participant voice. • Generate a list, based on the group organization process that will direct future innovation for conference participants and organizers. • Present the collective knowledge from the conference in a way that participants can see themselves as contributing partners in the conference outcome statements. This article, then, describes a case study of decision making in a large audience, keeping each participant involved in a meaningful process of an elaborated analysis of action items. The technology, the process, and the experiment are presented as a study of the feasibility of using such systems in large audiences. We introduce here the term large group decision support system (LGDSS) to describe the process of using technology to assist a large audience in making decisions.
Key Terms in this Chapter
Electronic Response System (ERS): ERS is a clicker-based data collection system.
Large Group Decision Support System (LGDSS): A methodology for prioritizing alternative solutions to a problem in a large group setting (unlimited number of participants).
ThinkClick: ThinkClick is an LGDSS using MAUT methodology and ERS.
Knowledge Harvesting: Knowledge harvesting is the process of documentation and integration of knowledge created within an organization or a situation.
Multi-Attribute Utility Theory (MAUT): MAUT is a popular theory of decision making.