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Alexis Hiniker

Publications and source records attributed to Alexis Hiniker.

At least 19 recordsLinked to original sources
arXiv2026

Metaphors as Scaffolds: Spatial, Embodied, Fantastical, and Relational Framings for Youth Usable Privacy Design

Drawing on observations from three prior studies with youth aged 13--24, we examine how metaphor shapes the way young people reason about privacy and imagine privacy designs beyond settings panels. Spatial metaphors made complex permission structures feel like movement through rooms and the placing of objects within them. Embodied metaphors gave youth language for shared norms around presence, access, and intrusion. Fantastical metaphors turned privacy work into something playful and discoverable, prompting more generative and granular design ideas. Relational metaphors, however, exposed the same mechanism's downside: when a system feels like a loyal companion while data passes through an institution, youth may disclose more than they otherwise would. This provocation does not argue that some metaphors are good and others bad. It argues that metaphors meaningfully scaffold both the design process and the user experience of usable privacy, and that choosing one is an ethical decision about which norms a privacy interface makes easy to see, imagine, and act on.

cs.HC↗
arXiv2026

Social Understanding, Placeness, and Identity Alignment: A Design Framework for Friendship-Supportive Youth Social Media

We present a design framework for friendship-supportive youth social media, derived from a synthesis of five empirical studies with 331 youth participants (ages 13-25) using interviews, co-design, surveys, diary studies, and a field deployment. Iterative analysis of 209 design-relevant data points identified three pillars: Social Understanding (interaction norms, interaction cues and scaffolding, social accountability and governance), Placeness (third place and community, boundaries and personal spaces, shared presence), and Identity Alignment (identity currency, identity plurality, relational identity signals). The framework maps nine design spaces through which platforms can support the conditions under which youth friendships form, deepen, and are maintained. It offers a shared vocabulary for locating contributions, comparing design interventions, and identifying under-explored areas for future work.

cs.HC↗
arXiv2026

Sustainable Care: Designing Technologies That Support Children's Long-Term Engagement with Social Issues

Children today encounter social issues -- climate change, conflict, inequality -- through digital technologies, and the design of that encounter shapes whether young people move toward lasting civic engagement or toward anxiety and withdrawal. Much of the content children see is optimized for attention through fear and urgency, with few pathways toward meaningful action -- contributing to rising distress and disengagement among young people who care deeply but feel powerless to act. This full-day workshop introduces ``sustainable care'' as a design lens, asking how technology might support children's sustained engagement with social causes without contributing to empathic distress or burnout. We invite researchers and practitioners across child-computer interaction, games, education, and youth mental health to map this landscape together and develop a research agenda for the CCI community.

cs.HC↗
arXiv2026

"Everyone's using it, but no one is allowed to talk about it": College Students' Experiences Navigating the Higher Education Environment in a Generative AI World

Higher education students are increasingly using generative AI in their academic work. However, existing institutional practices have not yet adapted to this shift. Through semi-structured interviews with 23 college students, our study examines the environmental and social factors that influence students' use of AI. Findings show that institutional pressure factors like deadlines, exam cycles, and grading lead students to engage with AI even when they think it undermines their learning. Social influences, particularly peer micro-communities, establish de-facto AI norms regardless of official AI policies. Campus-wide ``AI shame'' is prevalent, often pushing AI use underground. Current institutional AI policies are perceived as generic, inconsistent, and confusing, resulting in routine noncompliance. Additionally, students develop value-based self-regulation strategies, but environmental pressures create a gap between students' intentions and their behaviors. Our findings show student AI use to be a situated practice, and we discuss implications for institutions, instructors, and system tool designers to effectively support student learning with AI.

cs.CY↗
arXiv2026

How College Students Use AI to Navigate Course Readings: Evidence from an Eight-Week Study

College students increasingly use AI chatbots to support academic reading, yet we lack granular understanding of how these interactions shape their reading experience and cognitive engagement. We conducted an eight-week longitudinal study with 15 undergraduates who used AI to support assigned readings in a course. We collected 838 prompts across 239 reading sessions and developed a coding schema categorizing prompts into four cognitive themes: Decoding, Comprehension, Reasoning, and Metacognition. Comprehension prompts dominated (59.6%), with Reasoning (29.8%), Metacognition (8.5%), and Decoding (2.1%) less frequent. Most sessions (72%) contained exactly three prompts, the required minimum of the reading assignment. Within sessions, students showed natural cognitive progression from comprehension toward reasoning, but this progression was truncated. Across eight weeks, students' engagement patterns remained stable, with substantial individual differences persisting throughout. Qualitative analysis revealed an intention-behavior gap: students recognized that effective prompting required effort but rarely applied this knowledge, with efficiency emerging as the primary driver. Students also strategically triaged their engagement based on interest and academic pressures, exhibiting a novel pattern of reading through AI rather than with it: using AI-generated summaries as primary material to filter which sections merited deeper attention. We discuss design implications for AI reading systems that scaffold sustained cognitive engagement.

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arXiv2025

SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agents

As LLM-based computer-use agents (CUAs) begin to autonomously interact with real-world interfaces, understanding their vulnerability to manipulative interface designs becomes increasingly critical. We introduce SusBench, an online benchmark for evaluating the susceptibility of CUAs to UI dark patterns, designs that aim to manipulate or deceive users into taking unintentional actions. Drawing nine common dark pattern types from existing taxonomies, we developed a method for constructing believable dark patterns on real-world consumer websites through code injections, and designed 313 evaluation tasks across 55 websites. Our study with 29 participants showed that humans perceived our dark pattern injections to be highly realistic, with the vast majority of participants not noticing that these had been injected by the research team. We evaluated five state-of-the-art CUAs on the benchmark. We found that both human participants and agents are particularly susceptible to the dark patterns of Preselection, Trick Wording, and Hidden Information, while being resilient to other overt dark patterns. Our findings inform the development of more trustworthy CUAs, their use as potential human proxies in evaluating deceptive designs, and the regulation of an online environment increasingly navigated by autonomous agents.

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arXiv2025

Toward Needs-Conscious Design: Co-Designing a Human-Centered Framework for AI-Mediated Communication

We introduce Needs-Conscious Design, a human-centered framework for AI-mediated communication that builds on the principles of Nonviolent Communication (NVC). We conducted an interview study with N=14 certified NVC trainers and a diary study and co-design with N=13 lay users of online communication technologies to understand how NVC might inform design that centers human relationships. We define three pillars of Needs-Conscious Design: Intentionality, Presence, and Receptiveness to Needs. Drawing on participant co-designs, we provide design concepts and illustrative examples for each of these pillars. We further describe a problematic emergent property of AI-mediated communication identified by participants, which we call Empathy Fog, and which is characterized by uncertainty over how much empathy, attention, and effort a user has actually invested via an AI-facilitated online interaction. Finally, because even well-intentioned designs may alter user behavior and process emotional data, we provide guiding questions for consentful Needs-Conscious Design, applying an affirmative consent framework used in social media contexts. Needs-Conscious Design offers a foundation for leveraging AI to facilitate human connection, rather than replacing or obscuring it.

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arXiv2025

Understanding Privacy Norms Around LLM-Based Chatbots: A Contextual Integrity Perspective

LLM-driven chatbots like ChatGPT have created large volumes of conversational data, but little is known about how user privacy expectations are evolving with this technology. We conduct a survey experiment with 300 US ChatGPT users to understand emerging privacy norms for sharing chatbot data. Our findings reveal a stark disconnect between user concerns and behavior: 82% of respondents rated chatbot conversations as sensitive or highly sensitive - more than email or social media posts - but nearly half reported discussing health topics and over one-third discussed personal finances with ChatGPT. Participants expressed strong privacy concerns (t(299) = 8.5, p < .01) and doubted their conversations would remain private (t(299) = -6.9, p < .01). Despite this, respondents uniformly rejected sharing personal data (search history, emails, device access) for improved services, even in exchange for premium features worth $200. To identify which factors influence appropriate chatbot data sharing, we presented participants with factorial vignettes manipulating seven contextual factors. Linear mixed models revealed that only the transmission factors such as informed consent, data anonymization, or the removal of personally identifiable information, significantly affected perceptions of appropriateness and concern for data access. Surprisingly, contextual factors including the recipient of the data (hospital vs. tech company), purpose (research vs. advertising), type of content, and geographic location did not show significant effects. Our results suggest that users apply consistent baseline privacy expectations to chatbot data, prioritizing procedural safeguards over recipient trustworthiness. This has important implications for emerging agentic AI systems that assume user willingness to integrate personal data across platforms.

cs.CY↗
arXiv2025

Supporting Students' Reading and Cognition with AI

With the rapid adoption of AI tools in learning contexts, it is vital to understand how these systems shape users' reading processes and cognitive engagement. We collected and analyzed text from 124 sessions with AI tools, in which students used these tools to support them as they read assigned readings for an undergraduate course. We categorized participants' prompts to AI according to Bloom's Taxonomy of educational objectives -- Remembering, Understanding, Applying, Analyzing, Evaluating. Our results show that ``Analyzing'' and ``Evaluating'' are more prevalent in users' second and third prompts within a single usage session, suggesting a shift toward higher-order thinking. However, in reviewing users' engagement with AI tools over several weeks, we found that users converge toward passive reading engagement over time. Based on these results, we propose design implications for future AI reading-support systems, including structured scaffolds for lower-level cognitive tasks (e.g., recalling terms) and proactive prompts that encourage higher-order thinking (e.g., analyzing, applying, evaluating). Additionally, we advocate for adaptive, human-in-the-loop features that allow students and instructors to tailor their reading experiences with AI, balancing efficiency with enriched cognitive engagement. Our paper expands the dialogue on integrating AI into academic reading, highlighting both its potential benefits and challenges.

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arXiv2025

Design for Hope: Cultivating Deliberate Hope in the Face of Complex Societal Challenges

Design has the potential to cultivate hope in the face of complex societal challenges. These challenges are often addressed through efforts aimed at harm reduction and prevention -- essential but sometimes limiting approaches that can unintentionally narrow our collective sense of what is possible. This one-day, in-person workshop builds on the first Positech Workshop at CSCW 2024 by offering practical ways to move beyond reactive problem-solving toward building capacity for proactive goal setting and generating pathways forward. We explore how collaborative and reflective design methodologies can help research communities navigate uncertainty, expand possibilities, and foster meaningful change. By connecting design thinking with hope theory, which frames hope as the interplay of ``goal-directed,'' ``pathways,'' and ``agentic'' thinking, we will examine how researchers might chart new directions in the face of complexity and constraint. Through hands-on activities including problem reframing, building a shared taxonomy of design methods that align with hope theory, and reflecting on what it means to sustain hopeful research trajectories, participants will develop strategies to embed a deliberately hopeful approach into their research.

cs.HC↗
arXiv2025

Trust-Enabled Privacy: Social Media Designs to Support Adolescent User Boundary Regulation

Adolescents heavily rely on social media to build and maintain close relationships, yet current platform designs often make self-disclosure feel risky or uncomfortable. Through a three-part study involving 19 teens aged 13-18, we identify key barriers to meaningful self-disclosure on social media. Our findings reveal that while these adolescents seek casual, frequent sharing to strengthen relationships, existing platform norms often discourage such interactions. Based on our co-design interview findings, we propose platform design ideas to foster a more dynamic and nuanced privacy experience for teen social media users. We then introduce \textbf{\textit{trust-enabled privacy}} as a framework that recognizes trust -- whether building or eroding -- as central to boundary regulation, and foregrounds the role of platform design in shaping the very norms and interaction patterns that influence how trust unfolds. When trust is supported, boundary regulation becomes more adaptive and empowering; when it erodes, users resort to self-censorship or disengagement. This work provides empirical insights and actionable guidelines for designing social media spaces where teens feel empowered to engage in meaningful relationship-building processes.

cs.HC↗
arXiv2025

Understanding Children's Avatar Making in Social Online Games

Social online games like Minecraft and Roblox have become increasingly integral to children's daily lives. Our study explores how children aged 8 to 13 create and customize avatars in these virtual environments. Through semi-structured interviews and gameplay observations with 48 participants, we investigate the motivations behind children's avatar-making. Our findings show that children's avatar creation is motivated by self-representation, experimenting with alter ego identities, fulfilling social needs, and improving in-game performance. In addition, designed monetization strategies play a role in shaping children's avatars. We identify the ''wardrobe effect,'' where children create multiple avatars but typically use only one favorite consistently. We discuss the impact of cultural consumerism and how social games can support children's identity exploration while balancing self-expression and social conformity. This work contributes to understanding how avatar shapes children's identity growth in social online games.

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arXiv2025

Social Media Should Feel Like Minecraft, Not Instagram: Youth Visions for Meaningful Social Connections through Fictional Inquiry

We conducted co-design workshops with 23 participants (ages 15--24) to explore how youth envision ideal remote social connection. Using Fictional Inquiry (FI) within a Harry Potter-inspired narrative, we found that youth perceive a disconnect between platforms labeled ``social media'' (like Instagram) and those where they actually experience meaningful connections (like Minecraft or Discord). Participants envisioned an immersive platform prioritizing meaningful social connection through presence and immersion, natural self-expression, intuitive spatial navigation leveraging physical-world norms, and playful, low-stakes opportunities for friendship development. We synthesize these visions into six themes articulating relational needs that current platforms systematically marginalize. The FI method proved effective in generating innovative ideas while empowering youth by fostering hope and agency over social media's future. Our findings challenge ``doom'' narratives by reframing social media's harms as outcomes of specific design choices, demonstrating how design research can reopen space for imagining more supportive forms of mediated connection.

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arXiv2025

Discord's Design Encourages "Third Place" Social Media Experiences

In light of the diminishing presence of physical third places -- informal gathering spaces essential for social connection -- this study explores how the social media platform Discord fosters third-place experiences. Drawing on Oldenburg's conceptual framework, we analyze how Discord's design elements support the creation of virtual third places that foster both dyadic and community-based relationships. Through 25 semi-structured interviews with active Discord users, we identified 21 design elements aligned with Oldenburg's third-place characteristics. These elements cluster around four core principles: providing themed spaces for repeated interactions, supporting user autonomy and customization, facilitating mutually engaging activities, and enabling casual, low-pressure interactions. This work contributes to understanding how intentional platform design can cultivate virtual spaces that support meaningful social connections. The findings have implications for designing future social technologies that can help address growing concerns about social isolation in an increasingly digital world.

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arXiv2024

The Engagement-Prolonging Designs Teens Encounter on Very Large Online Platforms

In the attention economy, online platforms are incentivized to design products that maximize user engagement, even when such practices conflict with users' best interests. We conducted a structured content analysis of all Very Large Online Platforms (VLOPs) to identify the designs these influential apps and sites use to capture attention and extend engagement. Specifically, we conducted this analysis posing as a teenager to identify the designs that young people are exposed to. We find that VLOPs use four strategies to extend teens' use: pressuring, enticing, trapping, and lulling them into spending more time online. We report on a hierarchical taxonomy organizing the 63 designs that fall under these categories. Applying this taxonomy to all 17 VLOPs, we identify 583 instances of engagement-prolonging designs, with social media platforms using twice as many as other VLOPs. We present three vignettes illustrating how these designs reinforce one another in practice. We further contribute a graphical dataset of videos illustrating these features in the wild.

cs.HC↗
arXiv2024

Creativity in the Age of AI: Evaluating the Impact of Generative AI on Design Outputs and Designers' Creative Thinking

As generative AI (GenAI) increasingly permeates design workflows, its impact on design outcomes and designers' creative capabilities warrants investigation. We conducted a within-subjects experiment where we asked participants to design advertisements both with and without GenAI support. Our results show that expert evaluators rated GenAI-supported designs as more creative and unconventional ("weird") despite no significant differences in visual appeal, brand alignment, or usefulness, which highlights the decoupling of novelty from usefulness-traditional dual components of creativity-in the context of GenAI usage. Moreover, while GenAI does not significantly enhance designers' overall creative thinking abilities, users were affected differently based on native language and prior AI exposure. Native English speakers experienced reduced relaxation when using AI, whereas designers new to GenAI exhibited gains in divergent thinking, such as idea fluency and flexibility. These findings underscore the variable impact of GenAI on different user groups, suggesting the potential for customized AI tools.

cs.HC↗
arXiv2024

Privacy as Social Norm: Systematically Reducing Dysfunctional Privacy Concerns on Social Media

Through co-design interviews ($N=19$) and a design evaluation survey (N=136) with U.S. teens ages 13-18, we investigated teens' privacy management on social media. Our study revealed that 28% of teens with public accounts and 15% with private accounts experience "dysfunctional fear," that is, fear that diminishes their quality of life or paralyzes them from taking necessary precautions. These fears fall into three categories: fear of uncontrolled audience reach, fear of online hostility, and fear of personal privacy missteps. While current approaches often emphasize individual vigilance and restrictive measures, our findings show this can paradoxically lead teens to either withdraw from beneficial social interactions or resign themselves to accept privacy violations, viewing them as inevitable. Drawing on teen input, we developed and evaluated ten design prototypes that emphasize empowerment over fear, system-wide explicit emphasis on privacy, clear privacy norms, and flexible controls. Survey results indicate teens perceive these approaches as effectively reducing privacy concerns while preserving social benefits. Our findings suggest that platforms will be more likely to protect teens' privacy and less likely to manufacture unnecessary fear if they include designs that minimize the impact on other users, have low trade-offs with existing features, require minimal user effort, and function independently of community behavior. Such designs include: 1) alerting users about potentially unintentional personal information disclosure and 2) following up on user reports.

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