Feedback beyond accuracy: Using eye‐tracking to detect comprehensibility and interest during reading
通过30名参与者阅读18篇新闻文章的眼动实验，发现眼动信号能解释可理解性49.93%和兴趣30.41%的方差，为个性化信息系统提供超越准确性的隐式反馈。
Abstract Knowing what information a user wants is a paramount challenge to information science and technology. Implicit feedback is key to solving this challenge, as it allows information systems to learn about a user's needs and preferences. The available feedback, however, tends to be limited and its interpretation shows to be difficult. To tackle this challenge, we present a user study that explores whether tracking the eyes can unpack part of the complexity inherent to relevance and relevance decisions. The eye behavior of 30 participants reading 18 news articles was compared with their subjectively appraised comprehensibility and interest at a discourse level. Using linear regression models, the eye‐tracking signal explained 49.93% (comprehensibility) and 30.41% (interest) of variance ( p < .001). We conclude that eye behavior provides implicit feedback beyond accuracy that enables new forms of adaptation and interaction support for personalized information systems.