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Feedback beyond accuracy: Using eye-tracking to detect comprehensibility and interest during reading.

Frans van der Sluis1, Egon L van den Broek2

  • 1Department of Communication University of Copenhagen Copenhagen Denmark.

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Summary

Tracking eye movements offers valuable implicit feedback for personalized information systems. Eye behavior analysis significantly predicts user comprehension and interest, enhancing system adaptation.

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Area of Science:

  • Information Science and Technology
  • Human-Computer Interaction
  • Cognitive Science

Background:

  • Understanding user information needs is crucial for effective information retrieval systems.
  • Implicit feedback, such as user interactions, is vital for systems to learn user preferences.
  • Existing implicit feedback methods are often limited and difficult to interpret.

Purpose of the Study:

  • To investigate the utility of eye-tracking as a method for gathering implicit feedback.
  • To explore whether eye behavior can elucidate the complexities of user relevance judgments.
  • To determine if eye-tracking data can predict user comprehension and interest in content.

Main Methods:

  • A user study involving 30 participants reading 18 news articles.
  • Collected eye-tracking data (e.g., gaze patterns, fixation durations).
  • Compared eye behavior metrics with subjective ratings of content comprehensibility and interest.

Main Results:

  • Eye-tracking signals significantly explained variance in user-appraised comprehensibility (49.93%) and interest (30.41%).
  • Statistical analysis confirmed the significance of these findings (p < .001).
  • Eye behavior provides a rich source of implicit feedback beyond simple accuracy metrics.

Conclusions:

  • Eye behavior serves as a powerful, implicit signal for understanding user information needs and engagement.
  • Eye-tracking data can enhance personalized information systems by enabling more nuanced adaptation and interaction support.
  • This research opens new avenues for leveraging physiological responses in human-computer interaction.