TY - GEN
T1 - Assessment of Static and Dynamic Image Presentation for User Cognition and Understanding
AU - Patel, Pankati
AU - Morreale, Patricia
AU - Avirappattu, George
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - The internet supports users who want to locate information with minimal search while remaining engaged. Using a graphical approach for data presentation supports both information and engagement, but it is unknown if static or dynamic graphical display improves cognitive function. Both displays provide information to the viewer, but they are different in functionality and implementation. Static images are still images represented as a PNG, JPEG or PDF, without hidden layers and interactivity. In contrast, dynamic or Scalable Vector Graphics (SVG) images have more flexibility, and different approaches can support interaction with the image. Layers can be hidden which can be revealed by the viewer. Dynamic images hold data that tell the same story but from different viewpoints. In this research, pandemic data including case rate, vaccination rate, and mortality rate data for different states is used. The scope of the data remains the same, with the values varying based on the geographic region or state. The research investigates the effectiveness of interactive visuals to improve cognitive function. Two images, one static and one dynamic, were sequentially presented to viewers, followed by a series of questions after each image to test the user’s cognition. The analyzed responses to the questions conclude whether the dynamic image improved cognition when compared to the static image. The research showed that users preferred dynamic images by a factor of 2 to 1, with the users preferring the interactivity of the image. Further research will fully determine changes in user cognition and understanding.
AB - The internet supports users who want to locate information with minimal search while remaining engaged. Using a graphical approach for data presentation supports both information and engagement, but it is unknown if static or dynamic graphical display improves cognitive function. Both displays provide information to the viewer, but they are different in functionality and implementation. Static images are still images represented as a PNG, JPEG or PDF, without hidden layers and interactivity. In contrast, dynamic or Scalable Vector Graphics (SVG) images have more flexibility, and different approaches can support interaction with the image. Layers can be hidden which can be revealed by the viewer. Dynamic images hold data that tell the same story but from different viewpoints. In this research, pandemic data including case rate, vaccination rate, and mortality rate data for different states is used. The scope of the data remains the same, with the values varying based on the geographic region or state. The research investigates the effectiveness of interactive visuals to improve cognitive function. Two images, one static and one dynamic, were sequentially presented to viewers, followed by a series of questions after each image to test the user’s cognition. The analyzed responses to the questions conclude whether the dynamic image improved cognition when compared to the static image. The research showed that users preferred dynamic images by a factor of 2 to 1, with the users preferring the interactivity of the image. Further research will fully determine changes in user cognition and understanding.
KW - Cognitive function
KW - Data visualization
KW - Usability
UR - http://www.scopus.com/inward/record.url?scp=85140752885&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-17615-9_31
DO - 10.1007/978-3-031-17615-9_31
M3 - Conference contribution
AN - SCOPUS:85140752885
SN - 9783031176142
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 450
EP - 459
BT - HCI International 2022 - Late Breaking Papers. Design, User Experience and Interaction - 24th International Conference on Human-Computer Interaction, HCII 2022, Proceedings
A2 - Kurosu, Masaaki
A2 - Yamamoto, Sakae
A2 - Mori, Hirohiko
A2 - Soares, Marcelo M.
A2 - Rosenzweig, Elizabeth
A2 - Marcus, Aaron
A2 - Rau, Pei-Luen Patrick
A2 - Harris, Don
A2 - Li, Wen-Chin
PB - Springer Science and Business Media Deutschland GmbH
T2 - 24th International Conference on Human-Computer Interaction, HCII 2022
Y2 - 26 June 2022 through 1 July 2022
ER -