D. Scott McCrickard

Neelma Bhatti, Timothy L. Stelter, D. Scott McCrickard

Children in a large number of international and cross-cultural families in and outside of the US learn and speak more than one language. However, parents often struggle to acquaint their young children with their local language if the child spends majority of time at home and with their spoken language if they go to daycare or school. By reviewing relevant literature about the role of screen media content in young children's language learning, and interviewing a subset of parents raising multilingual children, we explore the potential of designing conversational user interfaces which can double as an assistive language aid.We present a preliminary list of objectives to guide the the design of conversational user interfaces dialogue for young children's bilingual language acquisition.

Taha Hassan, Bob Edmison, Timothy Stelter et al.

Trust in a recommendation system (RS) is often algorithmically incorporated using implicit or explicit feedback of user-perceived trustworthy social neighbors, and evaluated using user-reported trustworthiness of recommended items. However, real-life recommendation settings can feature group disparities in trust, power, and prerogatives. Our study examines a complementary view of trust which relies on the editorial power relationships and attitudes of all stakeholders in the RS application domain. We devise a simple, first-principles metric of editorial authority, i.e., user preferences for recommendation sourcing, veto power, and incorporating user feedback, such that one RS user group confers trust upon another by ceding or assigning editorial authority. In a mixed-methods study at Virginia Tech, we surveyed faculty, teaching assistants, and students about their preferences of editorial authority, and hypothesis-tested its relationship with trust in algorithms for a hypothetical `Suggested Readings' RS. We discover that higher RS editorial authority assigned to students is linked to the relative trust the course staff allocates to RS algorithm and students. We also observe that course staff favors higher control for the RS algorithm in sourcing and updating the recommendations long-term. Using content analysis, we discuss frequent staff-recommended student editorial roles and highlight their frequent rationales, such as perceived expertise, scaling the learning environment, professional curriculum needs, and learner disengagement. We argue that our analyses highlight critical user preferences to help detect editorial power asymmetry and identify RS use-cases for supporting teaching and research

Lindah Kotut, Timothy L. Stelter, Michael Horning et al.

There is an increased sensitivity by people about how companies collect information about them, and how this information is packaged, used and sold. This perceived lack of control is highlighted by the helplessness of users of various platforms in managing or halting what data is collected from/about them. In a future where users have wrested control of their data and have the autonomy to decide what information is collected, how it is used and most importantly, how much it is worth, a new market emerges. This design fiction considers possible steps prescient companies would take to meet these demands, such as providing third-party subscription platforms offering personal data trade as a service. These services would provide a means for transparent transactions that preserve an owner's control over their data; allowing them to individually make decisions about what data they avail for sale, and the amount of compensation they would accept in trade.

Taha Hassan, D. Scott McCrickard

The prevalence of misinformation on online social media has tangible empirical connections to increasing political polarization and partisan antipathy in the United States. Ranking algorithms for social recommendation often encode broad assumptions about network structure (like homophily) and group cognition (like, social action is largely imitative). Assumptions like these can be naïve and exclusionary in the era of fake news and ideological uniformity towards the political poles. We examine these assumptions with aid from the user-centric framework of trustworthiness in social recommendation. The constituent dimensions of trustworthiness (diversity, transparency, explainability, disruption) highlight new opportunities for discouraging dogmatization and building decision-aware, transparent news recommender systems.

Shuo Niu, D. Scott McCrickard, Steve Harrison

Themed collocated events, such as conferences, workshops, and seminars, invite people with related life experiences to connect with each other. In this era when people record lives through the Internet, individual experiences exist in different forms of digital contents. People share digital life records during collocated events, such as sharing blogs they wrote, Twitter posts they forwarded, and books they have read. However, connecting experiences during collocated events are challenging. Not only one is blind to the large contents of others, identifying related experiential items depends on how well experiences are retrieved. The collection of personal contents from all participants forms a valuable group repository, from which connections between experiences can be mined. Visualizing same or related experiences inspire conversations and support social exchange. Common topics in group content also help participants generate new perspectives about the collocated group. Advances in machine learning and data visualization provide automated approaches to process large data and enable interactions with data repositories. This position paper promotes the idea of event mining: how to utilize state-of-the-art data processing and visualization techniques to design event mining systems for connecting experiences during collocated activities. We discuss empirical and constructive problems in this design space, and our preliminary study of deploying a tabletop-based system, BlogCloud, which supports experience re-visitation and exchange with machine-learning and data visualization.

Lindah Kotut, Michael Horning, Derek Haqq et al.

This paper compares the needs of groups and communities in outdoor settings, seeking to identify subtle but important differences in the ways that their needs can be supported. We first examine the questions of who uses technology in outdoor settings, what their technological uses and needs are, and what conflicts exist between different trail users regarding technology use and experience. We then consider selected categories of people to understand their distinct needs when acting as groups and as communities. We conclude that it is important to explore the tensions between groups and communities to identify design opportunities.

Lindah Kotut, Michael Horning, Steve Harrison et al.

This paper examines the question of who technology users on the trail are, what their technological uses and needs are, and what conflicts exist between different trail users regarding technology use and experience, toward understanding how experiences of trail users contribute to designers. We argue that exploring these tensions provide opportunities for design that can be used to both mitigate conflicts and improve community on the trail.