Intelligent voice assistants (IVAs) have the potential to facilitate health information tasks among older adults and caregivers. However, when adopting these tools, older adults face a significant challenge balancing needs for support versus values, such as privacy and control. This paper explores older adults' expectations of IVAs that support collaborative health information tasks. We conducted semi-structured interviews with ten older adult-informal caregiver dyads and nine older adults who collaborate with formal caregivers to manage their health (n=29). To identify factors that influence supportive and non-supportive interactions in caregiving relationships, we use an existing model to examine collaborative care experiences within older adult-caregiver dynamics and perceptions of emerging IVAs that support similar activities. We learned that expectations of emerging IVA interactions overlap with those within human caregiving relationships. We discuss implications for designing IVAs for collaborative health information tasks that address needs for control, trust, transparency, and personability and the need to further explore designing for support versus care.

In this innovative practice full paper, we address the equity gap for neurodivergent and situationally limited engineering or computing learners by identifying the spectrum of factors that impact learning and acknowledging the fluctuations of learner function. Educators have shown a growing interest in identifying learners' cognitive abilities and learning preferences to measure their impact on academic achievement. These needs, however, are often addressed via one-size-fits-all approaches leaving the burden on disabled students to self-advocate or tolerate inadequately conducive conditions for their learning. Emerging frameworks guide the support of a neurodiverse learner population in curriculum and assessment activities through instructional approaches, such as online education. However, the application of these frameworks is disaggregated, and the technology interventions recommended for the online learning environment remain insubstantially supportive resulting in disparity, particularly for those with undisclosed learning or developmental disabilities and situational limitations. In this article, we integrate a neurodivergent perspective through secondary research of around 100 articles to introduce a comprehensive Guiding Empowerment Model involving key cognitive and situational factors that contextualize day-to-day experiences affecting learner ability. We illustrate the model by synthesizing common formations of these factors to facilitate three sample student profiles that highlight fluctuating user perceptions and explore initially evident actionable user problems in functioning. We use this model to evaluate sample learning platform features and other supportive technology solutions that potentially address the needs of the neurodiverse learner population represented in the learner profiles. The proposed approach augments frameworks such as Universal Design for Learning to consider factors including various sensory processing differences, social connection challenges, and environmental limitations. We suggest that by applying the model through technology-enabled features such as customizable task management, guided varied content access, and guided multi-modal collaboration, major learning barriers of neurodivergent and situationally limited learners will be removed to activate the successful pursuit of their academic goals.

Texting relies on screen-centric prompts designed for sighted users, still posing significant barriers to people who are blind and visually impaired (BVI). Can we re-imagine texting untethered from a visual display? In an interview study, 20 BVI adults shared situations surrounding their texting practices, recurrent topics of conversations, and challenges. Informed by these insights, we introduce TextFlow , a mixed-initiative context-aware system that generates entirely auditory message options relevant to the users’ location, activity, and time of the day. Users can browse and select suggested aural messages using finger-taps supported by an off-the-shelf finger-worn device without having to hold or attend to a mobile screen. In an evaluative study, 10 BVI participants successfully interacted with TextFlow to browse and send messages in screen-free mode. The experiential response of the users shed light on the importance of bypassing the phone and accessing rapidly controllable messages at their fingertips while preserving privacy and accuracy with respect to speech or screen-based input. We discuss how non-visual access to proactive, contextual messaging can support the blind in a variety of daily scenarios.

Texting relies on screen-centric prompts designed for sighted users, still posing significant barriers to people who are blind and visually impaired (BVI). Can we re-imagine texting untethered from a visual display? In an interview study, 20 BVI adults shared situations surrounding their texting practices, recurrent topics of conversations, and challenges. Informed by these insights, we introduce TextFlow: a mixed-initiative context-aware system that generates entirely auditory message options relevant to the users’ location, activity, and time of the day. Users can browse and select suggested aural messages using finger-taps supported by an off-the-shelf finger-worn device, without having to hold or attend to a mobile screen. In an evaluative study, 10 BVI participants successfully interacted with TextFlow to browse and send messages in screen-free mode. The experiential response of the users shed light on the importance of bypassing the phone and accessing rapidly controllable messages at their fingertips while preserving privacy and accuracy with respect to speech or screen-based input. We discuss how non-visual access to proactive, contextual messaging can support the blind in a variety of daily scenarios.

The creative sketching partner (CSP) is a proof of concept intelligent interface to inspire designers while sketching in response to a specified design task. With this interactive system we are studying the effect of an AI model of visual and conceptual similarity for selecting the Al's sketch response as an inspiration to the current state of the user's sketch. Specifically, we are interested in the user's behavior and response to an AI partner when engaged in a design task. By developing deep learning models of the sketches from a large-scale dataset, the user can control the amount of visual and conceptual similarity of the AI response when requesting inspiration from the CSP. We conducted a study with 50 design students to examine the participants' interaction behavior and their self reports. The participants' behavior maps into clusters that are co-related with three types of design creativity: combinatorial, exploratory, and transformational. Our findings demonstrate that the tool can facilitate ideation and overcome design fixation. In addition, analysis suggests that inspiration related to conceptual similarity is more associated with transformational creativity and inspiration related to visual similarity occurs more frequently during the detailed stages of design and is more prevalent with combinatorial creativity.

This paper presents and evaluates a new method for inspiring creativity in a co-creative design system. The method uses a computational model of aconceptual shift based on clustering of deep features from a database of sketches. The co-creative sketching tool maps a user's sketch to a sketch of a distinct category that has high, medium, or low visual and semantic similarity. We hypothesize that the degree of similarity between the user's and the system's sketches is associated with a range of cognitive models of creativity in a design context. We report on the findings of an empirical study that analyzes different design scenarios in which the user sketches in response to a proposed conceptual shift. The findings show that how similar the computational agent's sketch is to the user's original sketch is related to the presence of three types of design creativity in the user's response: combinatorial, exploratory, and transformational.