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Human Factors in User Modeling for Intelligent Systems

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A Human-Centered Perspective of Intelligent Personalized Environments and Systems

Part of the book series: Human–Computer Interaction Series ((HCIS))

Abstract

In the current digital landscape, humans take center stage. This has caused a paradigm shift in the realm of intelligent technologies, prompting researchers and (industry) practitioners to reflect on the challenges and complexities involved in understanding the (potential) users of the technologies they develop. In this chapter, we provide an overview of human factors in user modeling, a core component of human-centered intelligent solutions. We discuss critical concepts, dimensions, and theories that inform the design of user models that are more attuned to human characteristics. Additionally, we emphasize the need for a comprehensive user model that simultaneously considers multiple factors to represent the intricacies of individuals’ interests and behaviors. Such a holistic model can, in turn, shape the design of intelligent solutions that are better able to adapt and cater to a wide range of user groups.

Federica Cena, Monica Landoni, Cataldo Musto, Alain D. Starke—Contributed equally.

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Notes

  1. 1.

    By considering the system itself, we account for the fact that individual users—and hence their respective UMs—may change while they interact with the system.

  2. 2.

    Information elicitation methods exploited by adaptive systems should be customized to account for individual preferences and differences, such as the level of expertise, to increase users’ satisfaction [134, 135].

  3. 3.

    Assessing the quality of a UM becomes more challenging with the introduction of human factors. As the number of human factors included in the UM increases, the evaluation approach becomes more user-centered than what is typically employed for assessing UMs.

  4. 4.

    Although somewhat related, as they represent “classes of users,” stereotypes are different from personas. The latter are tools distilled from large sets of user data and used by human designers to keep the user perspective during different stages of system development, whereas stereotypes are automatically created and used by technologies.

  5. 5.

    For an in-depth discussion of cognitive process theories, along with an overview of the applicability of computational cognitive models to improve intelligent systems, please refer to [148].

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Authors and Affiliations

  1. Web Information Systems - EWI - TU Delft, Delft, The Netherlands

    Maria Soledad Pera

  2. Department of Computer Science, University of Torino, Torino, Italy

    Federica Cena

  3. Faculty of Informatics, Università della Svizzera Italiana, Lugano, Switzerland

    Monica Landoni

  4. Department of Computer Science, University of Bari, Bari, Italy

    Cataldo Musto

  5. Faculty of Social and Behavioural Sciences, University of Amsterdam, Amsterdam, The Netherlands

    Alain D. Starke

  6. Department of Information Science and Media Studies, University of Bergen, Bergen, Norway

    Alain D. Starke

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  3. UX Industries & Customer Experience, Product Engineering, SAP SE, Intelligent Enterprise Group, Walldorf, Baden-Württemberg, Germany

    Panagiotis Germanakos

  4. University of Primorska, Koper, Slovenia

    Marko Tkalčič

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Pera, M.S., Cena, F., Landoni, M., Musto, C., Starke, A.D. (2024). Human Factors in User Modeling for Intelligent Systems. In: Ferwerda, B., Graus, M., Germanakos, P., Tkalčič, M. (eds) A Human-Centered Perspective of Intelligent Personalized Environments and Systems. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-031-55109-3_1

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