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Effectiveness of the Adaptive Heuristic Evaluation Method for Augmented Reality Interfaces.

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Title: Effectiveness of the Adaptive Heuristic Evaluation Method for Augmented Reality Interfaces.
Authors: Lim, Dobin1 (AUTHOR), Suh, Gangseok1 (AUTHOR), Shin, Subin1 (AUTHOR), Hwang, Wonil1 (AUTHOR) wonil@ssu.ac.kr
Source: International Journal of Human-Computer Interaction. Jun2026, Vol. 42 Issue 11, p7948-7973. 26p.
Subjects: Augmented reality, Heuristic, User-centered system design, Evaluators
Abstract: This study proposes an adaptive heuristic evaluation method that tailors heuristics to evaluators and applies it to the usability evaluation of augmented reality (AR) applications to examine its effectiveness. The performance of the evaluation methods was assessed based on the usability problems discovered and their severity, and the differences were analyzed using the McNemar test. Results showed that the adaptive method considering evaluators' heuristic satisfaction effectively identified screen design problems and problems related to the relationship between virtual objects and real-world objects in high-interaction AR interfaces. However, it was less effective in detecting problems related to virtual objects. The adaptive method based on the evaluators' AR experience levels showed lower performance than the adaptive method considering heuristic satisfaction. This study demonstrates that the adaptive method reflecting evaluators' heuristic satisfaction outperforms traditional method in specific aspects. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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PubType: Academic Journal
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  Data: Effectiveness of the Adaptive Heuristic Evaluation Method for Augmented Reality Interfaces.
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  Data: <searchLink fieldCode="AR" term="%22Lim%2C+Dobin%22">Lim, Dobin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Suh%2C+Gangseok%22">Suh, Gangseok</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shin%2C+Subin%22">Shin, Subin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hwang%2C+Wonil%22">Hwang, Wonil</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wonil@ssu.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Jun2026, Vol. 42 Issue 11, p7948-7973. 26p.
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  Data: <searchLink fieldCode="DE" term="%22Augmented+reality%22">Augmented reality</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic%22">Heuristic</searchLink><br /><searchLink fieldCode="DE" term="%22User-centered+system+design%22">User-centered system design</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluators%22">Evaluators</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: This study proposes an adaptive heuristic evaluation method that tailors heuristics to evaluators and applies it to the usability evaluation of augmented reality (AR) applications to examine its effectiveness. The performance of the evaluation methods was assessed based on the usability problems discovered and their severity, and the differences were analyzed using the McNemar test. Results showed that the adaptive method considering evaluators' heuristic satisfaction effectively identified screen design problems and problems related to the relationship between virtual objects and real-world objects in high-interaction AR interfaces. However, it was less effective in detecting problems related to virtual objects. The adaptive method based on the evaluators' AR experience levels showed lower performance than the adaptive method considering heuristic satisfaction. This study demonstrates that the adaptive method reflecting evaluators' heuristic satisfaction outperforms traditional method in specific aspects. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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        Type: general
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      – SubjectFull: User-centered system design
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              M: 06
              Text: Jun2026
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              Y: 2026
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