Volume 17, Issue 1, November 2021
For the November 2021 issue, the invited essay is “Dual Cognitive UXD and Explainable AI” by Karen Cham, Raida Shakiry, and Carl Yates. They describe research in eCommerce and games UX that provides a foundation for dual cognitive, or deep UXD, to understand relationships between biometrics, persuasion, and ethical UX design to support the development of human-centered AIs.
In addition to the essay, this issue includes two methodological research papers—one on heuristics and the other comparing two data collection methods used in surveys.
The first article is “Development and Use of Heuristics to Evaluate Neonatal Medical Devices for Use in Low-Resource Settings,” by Jake Johnston and colleagues. They developed and evaluated heuristics for use in settings like hospitals in low- and middle-income countries to evaluate and discover usability issues with neonatal medical devices. Their results support the ability of domain-specific heuristics to identify potential usability problems that would not be captured using only standard heuristics.
The second article is “Comparison of Select-All-That-Apply Items with Yes/No Forced Choice Items,” by James R. Lewis and Jeff Sauro. They investigated magnitudes of selection rates from select-all-that-apply (SATA) grids with yes/no forced choice grids and series of individual yes/no forced choice items, finding little difference in selection rates but a significant user preference for SATA grids.
Dual Cognitive UXD and Explainable AI
The goal of this essay is to share seminal research findings in eCommerce and games UX as a foundation for a dual cognitive or “deep user experience design” (Deep UXD) that integrates biometric insights. I suggest this can provide a fundamental basis from which to address persuasion, emotion, and trust (PET; Schaffer, 2009) in the development cycle of all human-computer interaction (HCI) applications. I conclude on the future field of application in terms of UX informed human-centered Al (HCAI) and human-in-the-loop (HITL) service design for Industry 4.0. [Read More]
Development and Use of Heuristics to Evaluate Neonatal Medical Devices for Use in Low-Resource Settings
Previous research has shown that for several domains and environments, developing and using domain-specific heuristics can effectively supplement general heuristics to capture additional usability problems. However, no existing heuristic set specifically addresses medical devices for use in low-resource settings, such as hospitals in low- and middle-income countries. These settings are limited by a lack of critical resources such as medical consumables, equipment, and human resources; therefore, they require devices that meet unique usability challenges.
In this paper, we describe the development and use of domain-specific heuristics to evaluate neonatal medical devices intended for low-resource settings. Five additional heuristics were developed to account for specific usability needs in low-resource settings including cleanability, maintainability and reparability, low workload, minimize discomfort, and access to baby. [Read More]
Prior research has suggested that people tend to select more items when presented with a forced choice (yes/no) format than with a select-all-that-apply (SATA) format, and some have argued against ever using SATA in research. We review findings from previous research and report the results of new studies comparing a standard SATA grid format with two forced choice formats: a yes/no grid and a series of individual yes/no questions.
We found no difference in selection rates when both formats appeared in grids. The observed percentage of selection was larger with sets of individual yes/no questions than for SATA grids, but the difference was not statistically significant. We found that participants significantly preferred SATA to forced choice formats. We compare our findings with previous research and discuss the implications for UX researchers and practitioners. [Read More]