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Enhanced prediction models for predicting spatial visualization (VZ) in address verification task

  • Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

In the field of Human Computer Interaction and Psychology, it is accepted that spatial visualization (VZ) is one ability that can indicate individual’s performance on computer applications. Since users with different levels of VZ seem to prefer different types of user interfaces (UI), knowing a user’s level of VZ provides a great opportunity for application developers to design software with higher satisfaction and usability. In this paper, we proposed three models to predict a participant’s level of VZ based on the participant’s actions (taps) on the tablet screen while doing an address verification task in the neighborhood using the tablet. After applying the proposed prediction models with data of thirty participants, they yielded an optimal accuracy of 93.33%.

Original languageEnglish
Title of host publicationProceedings of 34th International Conference on Computers and Their Applications, CATA 2019
EditorsGordon Lee, Ying Jin
PublisherThe International Society for Computers and Their Applications (ISCA)
Pages247-256
Number of pages10
ISBN (Electronic)9781510885967
Publication statusPublished - 13 Mar 2019
Event34th International Conference on Computers and Their Applications, CATA 2019 - Honolulu, United States
Duration: 18 Mar 2019 → 20 Mar 2019

Publication series

NameProceedings of 34th International Conference on Computers and Their Applications, CATA 2019

Conference

Conference34th International Conference on Computers and Their Applications, CATA 2019
Country/TerritoryUnited States
CityHonolulu
Period18/03/19 → 20/03/19

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