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Research on User Experience Classification Based on Phenomenological Method

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12200))

Abstract

An important issue in the construction of the basic theory on user experience is that user experience classification has not yet received a satisfactory answer. This makes it difficult for user experience researchers and designers to practice without clear recognition on research objects. This article points out the existing classification methods are inadequate to explain an independent and clear experience phenomenon. The key challenge lies in the current research methods are not suitable for the user experience task. To overcome it, we utilize a phenomenological method of inductive reasoning method to construct a new framework including 20 experience classification. In the qualitative research based on phenomenological methods, researcher’s own knowledge background tends to have an important impact on the quality and effectiveness of the research. The aim of this research is not trying to provide a once and for all solution, but make the applicability of phenomenological research methods applicable. The proposed framework can provide a possible platform for the discussion of experience classification issues.

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Acknowledgments

This research was supported by the 2019 Science and Technology Plan of Beijing Municipal Education Commission (Grant No. KM201911417005) and the Premium Funding Project for Academic Human Resources Development in Beijing Union University (Grant No. 12210611609-039).

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Correspondence to Jingpeng Jia .

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Jia, J., Dong, X. (2020). Research on User Experience Classification Based on Phenomenological Method. In: Marcus, A., Rosenzweig, E. (eds) Design, User Experience, and Usability. Interaction Design. HCII 2020. Lecture Notes in Computer Science(), vol 12200. Springer, Cham. https://doi.org/10.1007/978-3-030-49713-2_10

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  • DOI: https://doi.org/10.1007/978-3-030-49713-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49712-5

  • Online ISBN: 978-3-030-49713-2

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