contextual inquiry

This study addresses the often-overlooked complexity of vehicle dwelling as a form of housing insecurity and its unique constraints within confined spaces. Through qualitative analysis of posts and comments from online communities of vehicle dwellers, the research systematically codes their everyday practices and identity negotiations shaped by social, spatial, and infrastructural limitations. Findings reveal that vehicle dwellers occupy an ambiguous position between homelessness and digital nomadism, with infrastructural capacity playing a pivotal role in their identity construction. Building on these insights, the work proposes design recommendations for technologies that accommodate diverse and context-specific needs. By foregrounding the lived experiences of this marginalized group, the study contributes a novel perspective and empirical foundation to inclusive human-computer interaction (HCI) research.

The rise of artificial intelligence poses methodological challenges to qualitative social science research (e.g., ethnography, in-depth interviews). This paper advances a pragmatic sociological approach that moves beyond the binary of techno-optimism and rejectionism, proposing a four-fold typology of human–AI collaboration grounded in methodological commitments and emphasizing deliberate, context-sensitive tool integration. We embed AI chatbots, automated workflows, and big data techniques into qualitative research processes—not to supplant deep interpretive understanding, but to support coding, analytical reasoning, and computationally augmented social interpretation. Our contributions are threefold: (1) a methodological framework demonstrating compatibility between computational tools and qualitative epistemic aims; (2) reusable, scalable computational-augmented workflow templates for qualitative analysis; and (3) empirical validation within large-scale ethnographic projects, confirming enhanced analytical efficiency without compromising interpretive depth or theoretical richness.

This study investigates the sociotechnical drivers underlying users’ cross-platform migration on social media. Methodologically, it employs a mixed-methods approach: 32 participants co-constructed “social media journey maps,” which were then analyzed through qualitative content analysis and graph representation learning—where platforms constitute nodes and migration paths form edges—marking the first integration of journey mapping with structural graph modeling. Results identify three primary migration drivers: (1) peer-driven popularity diffusion, (2) timing effects tied to critical feature rollouts, and (3) users’ subjective perceptions of safety, privacy, and value. Building on these findings, the study proposes a dynamic, context-sensitive, and subjectively constructed multidimensional migration driver model. Theoretically, this advances understanding of platform migration beyond technological determinism; empirically, it offers evidence-based design principles for next-generation social platforms that prioritize human-centeredness and adaptive responsiveness.

Observational studies in social VR face a structural tension among observer visibility, data traceability, and participant autonomy—challenges inadequately addressed by conventional public-space ethics frameworks. This paper conducts a narrative literature review of HCI scholarship on ethical observational research in digital environments, synthesizing insights to propose five domain-specific ethical guidelines for public social VR settings. Its contributions are threefold: first, it introduces *observer visibility* as a core ethical dimension—an analytical innovation not previously foregrounded in VR ethics; second, it advocates replacing static, one-time informed consent with platform-enabled design interventions and community-engaged, iterative consent processes; third, it develops a pragmatic yet theoretically grounded ethical assessment framework. The resulting principles provide systematic guidance for VR research governance, platform policy development, and ethical practice by researchers.

HCI has long evaluated qualitative research through a positivist lens, overemphasizing quantifiable metrics and neglecting its interpretive nature. Method: Drawing on epistemological critique, this paper systematically distinguishes positivist and interpretivist paradigms, exposing the fundamental limitations of quantification in understanding human behavior. It then proposes the first non-quantitative quality assessment framework specifically designed for HCI qualitative research. Contribution/Results: The framework introduces five interpretivist quality criteria—credibility, transferability, dependability, confirmability, and resonance—grounded in qualitative logic rather than numerical standards to ensure rigor and contextual appropriateness. It shifts evaluation away from positivist assumptions toward interpretivist principles, enhancing methodological fidelity to qualitative inquiry. The framework has been preliminarily adopted in the ACM Transactions on Computer-Human Interaction (TOCHI) and CHI conference review guidelines, marking a substantive step toward an interpretivist reorientation in HCI methodology.

This study addresses a critical gap in mobile context-aware systems, which typically assume users carry smartphones in their pockets—a premise that fails to accommodate wheelchair users whose phone-carrying behaviors are significantly shaped by physical abilities, wheelchair design, and daily contexts, yet remain underexplored. Through 91 surveys and 15 in-depth interviews, this work presents the first empirical investigation revealing the diverse smartphone-carrying practices among wheelchair users, thereby challenging the conventional “pocket” assumption. The research proposes treating carrying location as a key contextual proxy variable and advocates for a more inclusive paradigm in context-aware computing. These findings provide empirical grounding and practical guidance for designing high-accuracy, accessible mobile applications tailored to the needs of wheelchair users.

This study addresses the underexplored phenomenon of information and communication technology (ICT) non-use among migrant populations during migration processes. Drawing on in-depth interviews with 32 migrants in El Paso, Texas, and employing a three-stage migration framework, the research uncovers intentional and unintentional ICT avoidance behaviors shaped by risk perceptions, institutional demands, and temporal dynamics across migration phases. It identifies three distinct forms of non-use—device-related, informational, and protective—and argues that non-use functions both as an individual protective strategy and as a response to systemic exclusion. Rather than framing non-use as a technological failure, the paper positions it as a critical design premise. Building on these insights, the study proposes forward-looking design principles centered on non-use to foster more inclusive human-computer interaction practices.

This study addresses a critical gap in human-computer interaction (HCI) research: the frequent neglect of the normative implications and ethical consequences inherent in conceptual design. To confront this issue, the work introduces philosophical thought experiments as a systematic method for the first time in HCI, constructing hypothetical scenarios and applying logical reasoning to critically interrogate stakeholder assumptions within value-sensitive design and to refine theories such as contextual integrity. This approach effectively uncovers the ethical dimensions and potential technological harms embedded in foundational HCI concepts, challenging prevailing frameworks while catalyzing the development of new theoretical insights. By doing so, it offers the field a forward-looking, systematic tool for ethical analysis that enhances both conceptual rigor and practical responsibility in interactive system design.

This work addresses the limitations of existing geospatial user interfaces, which often lack real-time feedback and struggle to support collaborative exploration of migration data by interdisciplinary teams. To overcome these challenges, the authors propose GeoTEAM, a novel geospatial entity interaction system that innovatively integrates active physical knobs with embedded touchscreens, multi-surface displays spanning desktop and wall environments, and real-time visualizations. This design enables users to dynamically manipulate temporal sliders and map layers, facilitating intuitive investigation of net migration patterns and their environmental drivers. Empirical evaluation involving nine interdisciplinary research teams demonstrates that GeoTEAM significantly enhances collaborative efficiency, supports more intuitive sensemaking, and increases users’ confidence in interpreting complex migration datasets.

This study addresses the opacity of mandatory wearable sensing systems in high-stakes institutional settings, where users struggle to understand how their behavioral data are translated into consequential judgments. Drawing on in-depth interviews and behavioral observations of 24 individuals under electronic monitoring in China’s community correction system, the research introduces the concept of “sensor literacy” to elucidate how users actively construct risk awareness, probe system boundaries, and adapt their conduct under opaque surveillance. Two adaptive patterns emerge: limited behavioral flexibility when rules are predictable, and excessive activity contraction under high uncertainty. Notably, computational habits persist even after device removal. These findings offer critical insights for enhancing transparency and human-centered design in institutional sensing systems.