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An Experiment Study on the Cognitive Schema of Trajectory in Dynamic Visualization

  • Xiaozhou Zhou
  • Chengqi Xue
  • Congzhe Chen
  • Haiyan Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10906)

Abstract

In theory, when the novel has a high-matching degree with the cognitive structure, the cognitive process maintains an equilibrium status, the assimilation process of cognitive schema generates at this time. And the new information may expand the existing cognitive structure in amount and strengthen the schema. However, if the novel has a low-matching degree with the existing cognitive structure, the cognitive process appears unbalance accompanied by the accommodation process. In big data era, the visual features of the movement of objects (trajectory) has become an important element in dynamic visualization. In the display space, the movement pattern corresponds to the movement schema in cognitive schema. Based on this, we designed an experiment to verify the theoretical reasoning of cognitive schemas of trajectory in dynamic visualization. The results showed that the cognitive schemas of trajectory in dynamic visualization could build up by iterative learning in a short time. And the cognitive schema had a certain degree of inclusiveness. The difference degree between the novel and the inherent information was the main factor of the effect of the cognitive schemas. But we didn’t found the obvious distinction between the assimilation process and the accommodation process of cognitive schemas in the experiment. We also found the different dynamic trajectories associated with the effect of cognitive schemas to a certain degree. This research opened up a new perspective of cognitive schemas for the study of dynamic visualization.

Keywords

Dynamic visualization Cognitive schemas Assimilation Accommodation cognitive load 

Notes

Acknowledgement

This paper is supported by National Natural Science Foundation of China (No. 71471037). Thanks for all the participants involved in the experiments.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Xiaozhou Zhou
    • 1
  • Chengqi Xue
    • 1
  • Congzhe Chen
    • 2
  • Haiyan Wang
    • 1
  1. 1.School of Mechanical EngineeringSoutheast UniversityNanjingChina
  2. 2.The 60th Research Institute of General Staff Department of P.L.ANanjingChina

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