Abstract While virtual reality (VR) games are beneficial for older adults to improve their physical functions and cognitive abilities, VR research often does not include older adults. Our review of the proceedings of major HCI conferences (i.e. ASSETS, CHI, CHI PLAY, CSCW and DIS) between 2016 and 2020 shows that only three out of 352 VR-related papers involved older adults. Consequently, older adults tend to encounter user experience (UX) problems with VR. One common way to identify UX problems is to conduct usability testing with think-aloud (TA) protocols. As VR games tend to be perceptually and physically demanding, older adults might need to allocate more resources to VR content and interaction and thus have fewer resources for thinking aloud. This raises the question of whether TA protocols are still a viable approach to detecting UX problems of VR games for older adult participants. To answer this question, we conducted usability testing with older adults who played two common types of VR games (i.e. the exergame and experience game) using concurrent and retrospective TA protocols (i.e. CTA and RTA), which are widely used in the industry. We analyzed participants’ TA verbalizations and uncovered how different categories of verbalizations indicate UX problems. We further show how older adults perceived the effects of thinking aloud on their game experiences in two TA protocols and offer design implications.

The white cane is used as one of the options for mobility by people who are blind or visually impaired (BVI) but it comes with limitations like the lack of overhead detection and recognition of safety hazards. Smart canes were designed to address some of the white cane’s issues but the adoption of this technology has been minimal. We spoke with 16 BVI participants for an in-depth view on their smart cane experiences and needs. While the biggest concern was related to cost, we found that other factors like product consistency, durability, and the lack of awareness, trust, and confidence from the users all contribute to the low adoption rate of smart canes.

Few students with disabilities transition from undergraduate to graduate programs. Graduate students often receive ineffective and insufficient accommodations, including lack of support specific to graduate students, because disability services policies are shaped by undergraduate experiences. To understand how disability services offices accommodate graduate students: we (1) critically analyzed disability services websites of 18 U.S. institutions, and (2) interviewed 17 disability services staff. Disability services websites publicly present institutional accommodation policies and guidelines, and staff are responsible for identifying, providing, and implementing reasonable accommodations. We found that policies may be interpreted differently depending on specific student circumstances. We discuss our findings in two main themes: (a) Policies and attitudes ascribed to disability, technology, and faculty, and (b) Impacts of policies and perspectives on accommodation decisions for graduate students. The contributions of this work include an empirical investigation of institutional support for disabled graduate students and suggestions for how to improve support from disability services offices to empower students.

Subtle patterns in users’ think-aloud (TA) verbalizations and speech features are shown to be telltale signs of User Experience (UX) problems. However, such patterns were uncovered among young adults. Whether such patterns apply for older adults remains unknown. We conducted TA usability testing with older adults using physical and digital products. We analyzed their verbalizations, extracted speech features, identified UX problems, and uncovered the patterns that indicate UX problems. Our results show that when older adults encounter problems, their verbalizations tend to include observations (remarks), negations, question words and words with negative sentiments; and their voices tend to include high loudness, high pitch and high speech rate. We compare these subtle patterns with those of young adults uncovered in recent studies and discuss the implications of these patterns for the design of Human-AI collaborative UX analysis tools to better pinpoint UX problems.