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A cognition-centered personalization framework for cultural-heritage content

Abstract

The heterogeneity of the audience of cultural heritage institutions introduces numerous challenges to the delivery of the content. Considering that people differ in the way they perceive, process, and recall information and that their individual cognitive differences influence their experience, performance, and knowledge acquisition when performing cultural-heritage activities, the human-cognition factor should be considered as an important personalization factor within cultural-heritage contexts. To this end, we propose a cognition-centered personalization framework for delivering cultural-heritage activities, tailored to the users’ cognitive characteristics. The framework implements rule-based personalization algorithms that are based on cognition-centered user models that are created implicitly, transparently, and in run-time based on classifiers that correlate end-user cognitive characteristics with interaction and visual behavior patterns. For evaluating the proposed framework and improving the external validity of the experimental results, we conducted two eye-tracking between-subjects user-studies (\(N=226\)) covering two different cognitive styles (field dependence–independence and visualizer–verbalizer) and two different types of cultural activity (visual goal-oriented and visual exploratory). The results provide evidence about the applicability, effectiveness, and efficiency of the proposed framework and underpin the added value of adopting cognition-centered personalization frameworks within digitized cultural-heritage interaction contexts.

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Notes

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    In the literature, various terms have been used to describe these two types of behavior, such as exploration vs. inspection (Helmert et al. 2005) or skimming vs. scrutinizing (Lohmeyer and Meboldt 2015); however, they all describe the same two types.

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Raptis, G.E., Fidas, C., Katsini, C. et al. A cognition-centered personalization framework for cultural-heritage content. User Model User-Adap Inter 29, 9–65 (2019). https://doi.org/10.1007/s11257-019-09226-7

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Keywords

  • Individual cognitive differences
  • Cultural heritage
  • Personalization framework
  • Eye-gaze based user-modeling
  • Evaluation studies