Abstract
Our objective is to introduce a new approach to extracting and representing decision-making policies, and apply this technique to usability judgments collected on-site for Advanced Distance Learning (ADL) applications. First, we will provide an overview of traditional policy capturing techniques and introduce fuzzy logic as a potentially powerful alternative. Next, we will ask attendees to judge the extent to which specific usability violations within a series of ADL interfaces will interfere with learning. We will end this session by presenting models of expert performance on this task (previously collected and analyzed). Judgment data collected on-site will later be modeled and the validity of two modeling approaches will be assessed via follow-up data collection. Finally, overall results will be sent to all participants. By using examples from ADL applications, we hope to also gain insight into the nature of the usability challenges facing practitioners within this emerging domain.
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More From: Proceedings of the Human Factors and Ergonomics Society Annual Meeting
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