Date of Award

Fall 2023

Access Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Human Factors

Department

Human Factors and Behavioral Neurobiology

Committee Chair

Barbara Chaparro

First Committee Member

Shawn Doherty

Second Committee Member

Christina Frederick

Third Committee Member

Alex Chaparro

Fourth Committee Member

Jonathan Kies

Abstract

Augmented (AR) and Mixed Reality (MR) are new and currently developing technologies. They have been used and shown promise and popularity in the domains of education, training, enterprise, retail, consumer products, and more. However, there is a lack of consistency and standards in AR and MR devices and applications. Interactions and standards in one application may drastically differ from another. This may make it difficult for users, especially those new to these technologies, to learn and feel comfortable using the devices or applications. It may also hinder the usability of the applications as designers may not follow proven techniques to display this information effectively. One way to create these standards is through the development and acceptance of usability or user experience (UX) heuristics. There is a lack of validated and widely accepted heuristics in AR and MR. Those that do exist tend to be too specialized to be valid across types of applications or devices. This dissertation’s goal is to fill this gap through the creation of a validated usability/user experience (UX) heuristic checklist to evaluate AR or MR devices and/or applications by following a validated methodology for developing usability/user experience heuristics (Quiñones et al., 2018).

Previous work had been completed to develop an AR and MR heuristic checklist (Derby & Chaparro, 2022). This work resulted in 11 heuristics and 94 checklist items; however, validation of this checklist was limited. This dissertation broadened the heuristic checklist to ensure applicability to more application types, device types, and use cases. Five different applications and devices were used to validate the checklist through heuristic evaluations and user tests. Experts in the domain also provided their feedback on the heuristic checklist using applications of their choice. A total of 100 revisions were made to the Derby & Chaparro (2022) checklist as a result of this study. The final heuristic checklist consists of 12 heuristics and 109 checklist items that practitioners can use to evaluate AR or MR applications and devices and quantify the results to better inform design.

Additional Files
Fillable GS9_Acceptance JDERBY.Final.pdf (410 kB)
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