Inferring user knowledge level from eye movement patterns

  • Authors:

  • Michael J. Cole;Jacek Gwizdka;Chang Liu;Nicholas J. Belkin;Xiangmin Zhang

  • Affiliations:

  • School of Communication and Information, Rutgers University, New Brunswick, NJ 08901, USA;School of Communication and Information, Rutgers University, New Brunswick, NJ 08901, USA;School of Communication and Information, Rutgers University, New Brunswick, NJ 08901, USA;School of Communication and Information, Rutgers University, New Brunswick, NJ 08901, USA;School of Library and Information Science, Wayne State University, Detroit, MI 80202, USA

  • Venue:
  • Information Processing and Management: an International Journal
  • Year:
  • 2013

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Abstract

The acquisition of information and the search interaction process is influenced strongly by a person's use of their knowledge of the domain and the task. In this paper we show that a user's level of domain knowledge can be inferred from their interactive search behaviors without considering the content of queries or documents. A technique is presented to model a user's information acquisition process during search using only measurements of eye movement patterns. In a user study (n=40) of search in the domain of genomics, a representation of the participant's domain knowledge was constructed using self-ratings of knowledge of genomics-related terms (n=409). Cognitive effort features associated with reading eye movement patterns were calculated for each reading instance during the search tasks. The results show correlations between the cognitive effort due to reading and an individual's level of domain knowledge. We construct exploratory regression models that suggest it is possible to build models that can make predictions of the user's level of knowledge based on real-time measurements of eye movement patterns during a task session.