Research on the Influence of User and Graphic–Text Combined Icon Construal Level Fitting on Visual Cognition
Source abstract
Abstract
Based on the individual traits of the user’s construal level differences, this study examines the visual cognition differences of graphic–text combined icon concreteness in the interface between users with high and low construal levels. We classified four types of graphic–text combined icons, which are as follows: concrete graphic + concrete text (Ci + Ct), concrete graphic + abstract text (Ci + At), abstract graphic + concrete text (Ai + Ct), and abstract graphic + abstract text (Ai + At). According to the behavioral experiment results, there is no visual cognitive difference between the two types of traits users in Ci + Ct. In terms of Ci + At and Ai + Ct, the visual cognitive performance of high construal level users is slightly better than that of low construal level users. In Ai + At, there are obvious visual cognitive differences between the two types of users. Visual cognitive fluency plays a mediating role in response time and matching rates of the two types of users. Based on the construal level perspective, this study considers the visual cognitive differences based on the user’s stable traits. It provides a certain reference for the graphic–text combined icons’ design in the adaptive human–computer interaction interface.
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Research context
OpenAlex topics: Color perception and design · Technology Adoption and User Behaviour · Behavioral Health and Interventions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Southeast University, Nanjing 211189, China
Department of Art and Design, Beijing University of Chemical Technology, Beijing 100029, China
School of Design Art and Media, Nanjing University of Science and Technology, Nanjing 210014, China
School of Art and Design, Nanjing University of Technology, Nanjing 210031, China
School of Art Design and Media, East China University of Science and Technology, Shanghai 200237, China
Funding
Natural Science Foundation of China · Jiangsu province graduate scientific research innovation project · Shanghai Pu jiang Program
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Show source-provided references
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