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Am I Like Me? Avatar Self-similarity and Satisfaction in a Professional Training Environment

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Learning and Collaboration Technologies (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14040))

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Abstract

In virtual environments, avatars are used to represent users. Previous research focusing on video games has found that similarity of self and avatar leads to higher satisfaction with one’s avatar. We extend the existing research by examining avatar use in a real-world professional training setting. We asked 472 participants in a full-time online training program about their avatars in their 3D learning environment, i.e., about their satisfaction with their avatars, how similar their avatar was to them, reasons for avatar choice and switching, modifications, and suggestions for improvements. We found that higher self-similarity with one’s avatar leads to greater satisfaction with the avatar and that this effect was partly related to participant gender, with women considering avatar self-similarity as more important than men. Moreover, we found differential patterns for avatar use for female and male participants. Based on our findings, we argue that avatars should represent the diversity that exists in the users to allow for greater identification and for the resulting benefits, since having an avatar that is similar to oneself might improve the experience for all users and help to close a gender fairness-gap that exists regarding a positive learning environment.

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Authors and Affiliations

  1. Heilbronn University, Max-Planck-Street 39, 74081, Heilbronn, Germany

    Monika Pröbster & Nicola Marsden

  2. WBS Gruppe, Lorenzweg 5, 12099, Berlin, Germany

    Ronja-Debora Tomaske-Graff, Doris Herget & Martina Lucht

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  1. Monika Pröbster
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  2. Ronja-Debora Tomaske-Graff
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  3. Doris Herget
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  4. Martina Lucht
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  5. Nicola Marsden
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Correspondence to Monika Pröbster .

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Editors and Affiliations

  1. Cyprus University of Technology, Limassol, Cyprus

    Panayiotis Zaphiris

  2. Cyprus University of Technology, Limassol, Cyprus

    Andri Ioannou

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Pröbster, M., Tomaske-Graff, RD., Herget, D., Lucht, M., Marsden, N. (2023). Am I Like Me? Avatar Self-similarity and Satisfaction in a Professional Training Environment. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2023. Lecture Notes in Computer Science, vol 14040. Springer, Cham. https://doi.org/10.1007/978-3-031-34411-4_26

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  • DOI: https://doi.org/10.1007/978-3-031-34411-4_26

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