Modeling User Psychological Experience and Case Study in Online E-learning

Xiyuan Wu, Min Liu, Qinghua Zheng, Yunqiang Zhang, Haifei Li


In the post WWW era, the research of e-learning focuses on facilitating intelligent and proactive services for learners. The quality of user experience determines whether e-learning services would be accepted by learners. However, many researchers traditionally focus on the effectiveness of computer systems or the accuracy of algorithms themselves rather than on user-centric psychological experience. How to model and evaluate user experience taking into account user psychological and cognitive properties are challenging research topics. There are some traditional methods typically proposed to evaluate users’ psychological experience, such as interview, questionnaire etc. They are qualitative and easy to conduct but need more time and resource. And they are liable to subjective views. Based on user web log data, the current paper presents a quantitative approach of modeling user psychological experience in the context of intelligent e-learning. The properties and elements, which affect user experience, are analyzed and quantified. The holistic user experience is quantified through the fusion of analytic hierarchy process (AHP) and Delphi methods. A case study, at a university in China, is conducted for diagnosing whether the result of the proposed approach can be uniform with user subjective experience, and indicates that the proposed approach is effective and complements existing user experience research in intelligent e-learning.


E-learning; Web log analysis; User experience; User centric evaluation

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Copyright (c) 2017 Xiyuan Wu, Min Liu, Qinghua Zheng, Yunqiang Zhang, Haifei Li

International Journal of Emerging Technologies in Learning. ISSN: 1863-0383
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