From Reflection to Repair: A Scoping Review of Dataset Documentation ToolsDataset documentation is widely recognized as essential for the responsible development of automated systems. Despite growing efforts to support documentation through different kinds of artifacts, little is known about the motivations shaping documentation tool design or the factors hindering their adoption. We present a systematic review supported by mixed-methods analysis of 59 dataset documentation publications to examine the motivations behind building documentation tools, how authors conceptualize documentation practices, and how these tools connect to existing systems, regulations, and cultural norms. Our analysis shows four persistent patterns in dataset documentation conceptualization that potentially impede adoption and standardization: unclear operationalizations of documentation’s value, decontextualized designs, unaddressed labor demands, and a tendency to treat integration as future work. Building on these findings, we propose a shift in Responsible AI tool design toward institutional rather than individual solutions, and outline actions the HCI community can take to enable sustainable documentation practices.2026PRPedro Reynolds-Cuéllar et al.Robotics and AI InstituteExplainable AI (XAI)Research Ethics & Open ScienceAI-Assisted Decision-Making & AutomationCHI
Academics’ Reflections on Delivering Hybrid Lessons Through the Analytical Language of Seams and PatchworkThis paper presents insights from a series of interviews with academics at a public university in Ecuador, exploring their experiences in transitioning to synchronous hybrid teaching during the COVID-19 pandemic. This study reveals the challenges faced by academics in navigating the cultural, infrastructural, and technological seams present in the delivery of hybrid lessons in a country in the Global South. The findings provide empirical evidence of the invisible work undertaken by academics to address these challenges, the importance of providing adequate supports for academics when adopting hybrid learning, and the role of student agency in these settings. Finally, we reflect on the implications of deploying hybrid learning for academics' pedagogical practice. By applying the analytical language of seams and patchwork, the study sheds light on the complexities of hybrid learning implementation in a context marked by socio-economic and technological constraints.2025RARonny Andrade et al.Enhancing LearningCSCW
The Hidden Workload: Student Data Work in Multimodal Algorithmic EvaluationsAs algorithmic systems increasingly mediate human activities across diverse domains, they shift more responsibility for data collection onto users, fundamentally altering the nature of data work. This paper examines the implications of this shift by investigating student-led data collection and automated feedback interpretation using a mobile, multimodal learning analytics (MMLA) tool designed to coach oral presentation skills. Our findings reveal that while this user-controlled data collection provides greater flexibility, it also imposes speculative efforts, compelling students to adjust behaviors to meet assumed standards of "good data" even when such changes are unwarranted. The study highlights the often-overlooked informal data work of managing socio-material aspects of data collection, emphasizing the need for MMLA tools that offer adaptive support and guidance. These insights extend to algorithmic system design in educational and professional contexts, advocating for systems that balance user autonomy with workload-minimizing guidance to achieve equitable accountability.2025GMGonzalo Gabriel Méndez et al.Improving Data CollectionCSCW
Emerging Data Practices: Data Work in the Era of Large Language ModelsData is one of the foundational aspects of making Artificial Intelligence (AI) work as intended. As large language models (LLMs) become the epicenter of AI, it is crucial to understand better how the datasets that maintain such models are created. The emergent nature of LLMs makes it critical to understand the challenges practitioners developing Gen AI technologies face to design alternatives for better responding to Gen AI's ethical issues. In this paper, we provide such understanding by reporting on 25 interviews with practitioners who handle data in three distinct development stages of different LLMs. Our contributions are (1) empirical evidence of how uncertainty, data practices, and reliance mechanisms change across LLMs' development cycle; (2) how the unique qualities of LLMs impact data practices and their implications for the future of Gen AI technologies; and (3) provide three opportunities for HCI researchers interested in supporting practitioners developing Gen AI technologies.2025AGAdriana Alvarado Garcia et al.IBM Research, Responsible Tech ResearchGenerative AI (Text, Image, Music, Video)AI Ethics, Fairness & AccountabilityAlgorithmic Fairness & BiasCHI
Politics of the Past: Understanding the Role of Memory, Postmemory, and Remembrance in Navigating the History of Migrant FamiliesThe importance of history as an HCI method has been gaining increasing attention in HCI literature. However, the mainstream historical sources (books, documentaries, etc.) and methods often risk (re)producing western colonial biases potentially providing a narrow one-sided perspective on history and detaching “sanitized facts” from people’s emotional accounts. While oral history and similar alternative methods are often used as a countermeasure, their applicability has remained underexplored in HCI, especially in a sensitive context, such as migration. We build on the rich body of social science work on collective memory to introduce a complementary way of navigating the past of the migrant families, and also reveal the corresponding challenges to advance this literature. Our interview study with 17 migrant families highlights how the politics of remembrance, family dynamics, and postmemory shape the past stories of migrant families. We discuss how these findings inform the HCI literature on migration, design, and postcolonial computing.2024NCNabila Chowdhury et al.University of TorontoCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Developing Countries & HCI for Development (HCI4D)User Research Methods (Interviews, Surveys, Observation)CHI
Bitacora: A Toolkit for Supporting NonProfits to Critically Reflect on Social Media Data UseIn this paper, we describe the design and evaluation of the toolkit Bitacora, addressed to practitioners working in non-profit organizations interested in integrating Twitter data into their work. The toolkit responds to the call to maintain the locality of data by promoting a qualitative and contextualized approach to analyzing Twitter data. We assessed the toolkit's effectiveness in guiding practitioners to search, collect, and be critical when analyzing data from Twitter. We evaluated the toolkit with ten practitioners from three non-profit organizations of different aims and sizes in Mexico. The assessment surfaced tensions between the assumptions embedded in the toolkit's design and practitioners' expectations, needs, and backgrounds. We show that practitioners navigated these tensions in some cases by developing strategies and, in others, questioning the appropriateness of using Twitter data to inform their work. We conclude with recommendations for researchers who developed tools for non-profit organizations to inform humanitarian action.2024AGAdriana Alvarado Garcia et al.IBM ResearchContent Moderation & Platform GovernanceActivism & Political ParticipationCHI
Mobilizing Social Media Data: Reflections of a Researcher Mediating between Data and OrganizationThis paper examines the practices involved in mobilizing social media data from their site of production to the institutional context of non-profit organizations. We report on nine months of fieldwork with a transnational and intergovernmental organization using social media data to understand the role of grassroots initiatives in Mexico, in the unique context of the COVID-19 pandemic. We show how different stakeholders negotiate the definition of problems to be addressed with social media data, the collective creation of ground-truth, and the limitations involved in the process of extracting value from data. The meanings of social media data are not defined in advance; instead, they are contingent on the practices and needs of the organization that seeks to extract insights from the analysis. We conclude with a list of reflections and questions for researchers who mediate in the mobilization of social media data into non-profit organizations to inform humanitarian action.2023AGAdriana Alvarado Garcia et al.IBM Research, Georgia Institute of TechnologySocial Platform Design & User BehaviorCommunity Engagement & Civic TechnologyCHI
Pair-Up: Prototyping Human-AI Co-orchestration of Dynamic Transitions between Individual and Collaborative Learning in the ClassroomEnabling students to dynamically transition between individual and collaborative learning activities has great potential to support better learning. We explore how technology can support teachers in orchestrating dynamic transitions during class. Working with five teachers and 199 students over 22 class sessions, we conducted classroom-based prototyping of a co-orchestration technology ecosystem that supports the dynamic pairing of students working with intelligent tutoring systems. Using mixed-methods data analysis, we study the resulting observed classroom dynamics, and how teachers and students perceived and experienced dynamic transitions as supported by our technology. We discover a potential tension between teachers' and students' preferred level of control: students prefer a degree of control over the dynamic transitions that teachers are hesitant to grant. Our study reveals design implications and challenges for future human-AI co-orchestration in classroom use, bringing us closer to realizing the vision of highly-personalized smart classrooms that address the unique needs of each student.2023KYKexin Bella Yang et al.Carnegie Mellon UniversityIntelligent Tutoring Systems & Learning AnalyticsCollaborative Learning & Peer TeachingContext-Aware ComputingCHI
Para Cima y Pa’ Abajo: Building Bridges Between HCI Research in Latin America and in the Global NorthThe Human-computer Interaction (HCI) community has the opportunity to foster the integration of research practices across the Global South and North to begin overcoming colonial relationships. In this paper, we focus on the case of Latin America (LATAM), where initiatives to increase the representation of HCI practitioners lack a consolidated understanding of the practices they employ, the factors that influence them, and the challenges that practitioners face. To address this knowledge gap, we employ a mixed-methods approach, comprising a survey (66 respondents) and in-depth interviews (19 interviewees). Our analyses characterize a set of research perspectives on how HCI is practiced in/about LATAM; a set of driving forces and tensions with a heavy reliance on diasporic dynamics; and a set of professional demands and associated structural limitations. We also offer a roadmap towards building connections across HCI communities, in an attempt to rebuild HCI as a pluriverse.2023PRPedro Reynolds-Cuéllar et al.MITInclusive DesignDeveloping Countries & HCI for Development (HCI4D)CHI
From Data to Insights: A Layered Storytelling Approach for Multimodal Learning AnalyticsSignificant progress to integrate and analyse multimodal data has been carried out in the last years. Yet, little research has tackled the challenge of visualising and supporting the sensemaking of multimodal data to inform teaching and learning. It is naïve to expect that simply by rendering multiple data streams visually, a teacher or learner will be able to make sense of them. This paper introduces an approach to unravel the complexity of multimodal data by organising it into meaningful layers that explain critical insights to teachers and students. The approach is illustrated through the design of two data storytelling prototypes in the context of nursing simulation. Two authentic studies with educators and students identified the potential of the approach to create learning analytics interfaces that communicate insights on team performance, as well as concerns in terms of accountability and automated insights discovery.2020RMRoberto Martinez-Maldonado et al.Monash UniversityTime-Series & Network Graph VisualizationData StorytellingIntelligent Tutoring Systems & Learning AnalyticsCHI