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Updated: Jul 3, 2025

Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions
Published on: June 21, 2019
Do redundant graphical attributes reduce decision-making efficiency?
Tao Jin1, Chunpeng Chen1, Yuting Xia1
1College of Mechanical and Electrical Engineering, China University of Petroleum (East China), Qingdao, China.
Abstract:
Multiple time-series graphs are commonly used for data visualisation, but few scholars have investigated the impact of graphical attributes on decision-making efficiency. This study explores the effects of graphical attributes of varying redundancy conditions on decision-making efficiency. Two experimental conditions were developed for the experiment: non-redundant (independent graphical attributes: colour, linear and marker) and redundant (combinations of two and more graphical attributes: colour and linear, colour and marker, etc.). A total of 60 people took part in both experiments and performed two tasks: maximisation and discrimination. The experiments revealed that the addition of attributes, such as colour, marker or linear, decreased response time (RT), but the combination of colour & linear & marker increased RT. This is more significant in discrimination tasks. We provide empirical evidence for the design of time-series data visualisations and encourage the combination of two of these graphical attributes, such as colour & linear, colour & marker or linear & marker, when conditions allow, to improve decision-making efficiency.
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