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Review of Cognitive Modeling Software Tools

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Cognitive Modeling for Automated Human Performance Evaluation at Scale

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

Abstract

A large number of cognitive models have been developed and widely used in the HCI domain. GOMS (Gray et al (1993) Hum Comput Interact 8(3):237–309; John and Kieras (1996) ACM Trans Comput-Hum Interact 3(4):320–351) is one of the well-established models for predicting human performance and facilitating UI design. As mentioned in Chap. 2, a number of variants of GOMS models such as KLM (Card et al (1980) Commun ACM 23(7):396–410) and CPM-GOMS (John and Kieras (1996) ACM Trans Comput-Hum Interact 3(4):320–351) are useful to predict task completion time, and to refine UI designs and human task procedures (Paik et al (2015) ACM Trans Comput-Hum Interact 22(5):25:1–25:26. https://doi.org/10.1145/2776891). In this chapter, we present a review of existing software tools that materializing these cognitive models so that they can be used by people without advanced knowledge on cognitive modelling. Although there are lots of existing tools, we mainly introduce CogTool, SANLab-CM, and Cogulator in this chapter. The main reason is that they are well maintained open source projects with a considerable size of user base. In addition, this chapter lists some examples of applying cognitive models and relevant software tools in both HCI and cyber security domains. Furthermore, this chapter concludes with a discussion on issues and challenges of using existing software tools to model complex systems.

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Notes

  1. 1.

    Available at https://github.com/cogtool/cogtool

  2. 2.

    Available at https://github.com/CogWorks/SANLab-CM

  3. 3.

    http://cogworks.cogsci.rpi.edu/projects/software/sanlab-cm/

  4. 4.

    https://web.eecs.umich.edu/~kieras/goms.html

  5. 5.

    http://cogulator.io/primer.html

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Authors and Affiliations

  1. Centre for Vision, Speech, and Signal Processing, University of Surrey, Guildford, UK

    Haiyue Yuan

  2. School of Computing, University of Kent, Canterbury, UK

    Shujun Li

  3. School of Psychology, Department of Psychological Sciences, University of Surrey, Guildford, UK

    Patrice Rusconi

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  1. Haiyue Yuan
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  2. Shujun Li
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Yuan, H., Li, S., Rusconi, P. (2020). Review of Cognitive Modeling Software Tools. In: Cognitive Modeling for Automated Human Performance Evaluation at Scale . Human–Computer Interaction Series(). Springer, Cham. https://doi.org/10.1007/978-3-030-45704-4_3

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  • DOI: https://doi.org/10.1007/978-3-030-45704-4_3

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