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Analyzing Animated Representations of Complex Causal Semantics

Causal relationships are inherent in the world around us and are intrinsic to our decision making process. Michotte's Theory of Ampliation suggests that the perception of causality can be enhanced under appropriate spatiotemporal conditions. We extended this theory and proposed that simple static and animated designs, based on structural and temporal rules, enable the perception of complex causal semantics, such as additive, mediated, and bidirectional causalities. Results of our experiment showed that participants were ~5% more accurate and ~8% faster with the animations, than with the static representations. Overall our results show that animations that are designed based on perceptual rules assist the comprehension of complex causal relations.

http://dl.acm.org/citation.cfm?id=1620993.1621009

Nivedita R. Kadaba, Pourang P. Irani and Jason Leboe. 2009. Analyzing Animated Representations of Complex Causal Semantics. In Proceedings of the 6th Symposium on Applied Perception in Graphics and Visualization (APGV '09). Chania, Crete, Greece. ACM, 77-84.

Bibtext Entry

@INPROCEEDINGS { kadaba09b,
    AUTHOR = { Nivedita R. Kadaba and Pourang P. Irani and Jason Leboe },
    TITLE = { Analyzing Animated Representations of Complex Causal Semantics },
    BOOKTITLE = { Proceedings of the 6th Symposium on Applied Perception in Graphics and Visualization (APGV '09) },
    YEAR = { 2009 },
    PAGES = { 77--84 },
    DOI = { 10.1145/1620993.1621009 },
    PUBLISHER = { ACM },
    ADDRESS = { Chania, Crete, Greece },
}

Authors

Pourang Irani

Pourang Irani

Professor
Canada Research Chair

As well as: , Jason Leboe