Measuring and Improving User Experience Through Artificial Intelligence-Aided Design

Frontiers in Psychology

article

Bin Yang¹  Long Wei²  Zihan Pu¹ 

[1] School of Design, Jiangnan University;Zhejiang Province Key Laboratory of Smart Management & Application of Modern Agricultural Resources, Huzhou University

关键词: user experience;    artificial intelligence aided design;    human computer interaction;    mobile application design;    deep neural network;    usability evaluation;   

DOI  :  10.3389/fpsyg.2020.595374

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

This paper aims to propose a methodology for measuring user experience (UX) by using artificial intelligence-aided design (AIAD) technology in mobile application design. Unlike the traditional assistance design tools, AIAD focuses on the rational use of artificial intelligence (AI) technology to measure and improve UX since conventional data collection methods (such as user interview and user observation) for user behavior data are inefficient and time-consuming. We propose to obtain user behavior data from logs of mobile application. In order to protect the privacy of users, only a few dimensions of information is used in the process of browsing and operating mobile application. The goal of the proposed methodology is to make the deep neural network model simulate the user’s experience in the process of operating a mobile application as much as possible. We design and use projected pages of application to train neural networks for specific tasks. These projected pages consist of the click information of all users in the process of completing a certain task. Thus, features of user behavior can be aggregated and mapped in the connection layers and the hidden layers. Finally, the optimized design is executed on the social communication application to verify the efficiency of the proposed methodology.

【 授权许可】

CC BY