Eye Tracking based Cognitive-Centered User Models

C. Fidas
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引用次数: 1

Abstract

State-of-the-art predictive user models, like Goals, Operators, Methods, and Selection Rules (GOMS) or Keystroke-Level Model (KLM), do not consider human differences in information processing, and do not model user interaction by also considering visual behavior patterns of users during task execution. This can be accredited mainly to insufficient methods and approaches on how to model such interdependencies and thus correlate users’ cognitive characteristics with their interaction and visual behavior during task execution, and ultimately considering such cognitive-centered user models practically within current state-of-the-art information systems’ personalization and adaptation approaches. In this paper, we elaborate on such an endeavor and propose a seven-step, gaze-based human cognitive-centered user model as a basis of synthesizing user cognitive styles along with their interaction and visual behavior patterns. Aiming to prove the validity of the suggested user model, we applied it in the context of an eye tracking study that investigated influences of users’ human cognitive differences on their visual behavior in user authentication within traditional desktop and mixed reality contexts. Initial results of the study are also reported. CCS CONCEPTS • Human-centered computing ~ HCI theory, concepts and models ~ Empirical studies in HCI.
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基于认知中心用户模型的眼动追踪
最先进的预测用户模型,如目标、操作符、方法和选择规则(GOMS)或击键级模型(KLM),没有考虑信息处理中的人类差异,也没有通过考虑用户在任务执行期间的视觉行为模式来建模用户交互。这主要是由于在如何建立这种相互依赖关系的模型,从而将用户的认知特征与任务执行过程中的交互和视觉行为联系起来的方法和途径不足,并最终在当前最先进的信息系统的个性化和适应方法中实际考虑这种以认知为中心的用户模型。在本文中,我们详细阐述了这一努力,并提出了一个七步,基于注视的人类认知中心用户模型,作为综合用户认知风格及其交互和视觉行为模式的基础。为了证明建议的用户模型的有效性,我们将其应用于一项眼动追踪研究中,该研究调查了传统桌面和混合现实环境下用户在用户认证中人类认知差异对其视觉行为的影响。本文还报告了研究的初步结果。•以人为中心的计算~ HCI理论、概念和模型~ HCI的实证研究。
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