Artificial intelligence (AI) systems are increasingly prevalent in youths’ lives, despite documentation and concern of potential algorithmic harm. With responsible AI (RAI) efforts aiming to address harms, youth are largely overlooked as contributors, despite being stakeholders of AI. This paper explores perspectives on challenges, barriers, and opportunities of youth participation in responsibly creating AI. Through workshops with 16 teens and 11 parents, as well as interviews with 8 AI practitioners, we find that while all groups recognize the value of youth perspectives, the opinions of those not directly paying for AI are not prioritized. Many parents were optimistic about their youths’ ability to contribute, while youth showed a desire to contribute, coupled with an awareness of their strengths and limitations. Practitioners saw the potential of youth to contribute but not necessarily as empowered decision makers in RAI processes. We offer insights on involving youth in RAI, balancing protection with agency.

Creativity tools are a cornerstone of HCI, with systems for video, music, writing, and design deeply embedded in modern creative practice. Yet one key element of these systems remains undertheorized: the role of activity traces. Activity traces are the records of creator data, including artifact iterations, annotations, or reference materials, produced over the course of a creative process. To examine how activity traces are leveraged, we reviewed 133 creativity systems from major HCI venues. We structure our findings through a Living Framework for Trace Awareness, which captures both the characteristics of trace data and how systems engage with their temporal features. This framework offers the first systematic account of activity trace usage in creativity tools. We highlight overlooked assumptions about creator data in feature design and position activity traces as a core design material for shaping the next generation of creativity support systems.

In recent years, Posthuman HCI research has started exploring noticing as a method for design research that shifts focus away from anthropocentric views to embrace more entangled ecological perspectives. Through an autoethnographic freediving practice incorporating underwater photography and microphenomenological reflection, we notice how freediving can reshape our perceptions of and connections to the ocean. In this pictorial, we present freediving as a method for transcorporeal interconnectedness, which, through breathwork and sensory immersion, fosters a deeper understanding of more-than-human interactions, ultimately reflecting on designing for ecological awareness.

Background music plays a crucial role in social media videos, yet finding the right music remains a challenge for video creators.These creators, often not music experts, struggle to describe their musical goals and compare options.AI text-to-music generation presents an opportunity to address these challenges by allowing users to generate music through text prompts; however, these models often require musical expertise and are difficult to control.In this paper, we explore how to incorporate music generation into video editing workflows.A formative study with video creators revealed challenges in articulating and iterating on musical preferences, as creators described music as "vibes" rather than with explicit musical vocabulary.Guided by these insights, we developed a creative assistant for music generation using editable vibe-based recommendations and structured refinement of music output.A user study showed that the assistant supports exploration, while direct prompting is more effective for precise goals.Our findings offer design recommendations for AI music tools for video creators.

Members of historically marginalized communities do not have equal access to formal health resources. Inequality in access to care leads to increased health disparity, meaning there is a gap in health between segments of the population. These inequalities affect members of marginalized communities physically, mentally, and emotionally. In this research we present the design of Bloomwood Stories: Block Party, a digital, visual novel game as an informal health resource that incorporates Bandura's self-efficacy design framework to improve player health knowledge. We discuss key design decisions for the player character (PC), non-player characters (NPCs), as well as lessons learned in designing for self-efficacy and designing for representation.

Artificial intelligence (AI) is ubiquitous in K-12 youths' everyday lives. However, it has become increasingly well-documented that AI can cause harm by reflecting and amplifying societal biases. While many youth are not currently empowered to engage in broader responsible AI discourse and processes, there is great potential. Foundational to engaging in critical conversations is ability to critique AI. We present the RAD framework, designed to scaffold critique of AI in three steps: Recognize (harms of AI), Analyze (societal aspects of AI harms), and Deliberate (what more responsible AI could be). We ran a workshop study with racially diverse middle school girls (N = 21) to investigate its effectiveness. We found that through being scaffolded with the framework, the youth could articulate biases that they saw in an AI scenario and consider how biases may impact different stakeholders. They then could contemplate how different stakeholders had varying amounts of power in the AI scenario and what that meant in terms of creating more responsible AI systems and processes. After participating in the study, the youth felt more strongly about voicing their opinions about AI with others. The RAD framework and activities work toward emboldening youths' engagement in critical discourse about AI.

This pictorial presents Echo of the Abyss (EotA), a Virtual Reality (VR) experience that immerses users in a simulated deep-sea dive. EotA aims to foster a sense of connection and curiosity towards marine ecosystems by allowing players to embody a diver, guided by aquatic animals, in a safe and contemplative virtual environment. The design leverages theories from HCI, ecopsychology, and hydrocommons to promote environmental stewardship and emotional engagement with the ocean. EotA's narrative and interaction strategies are intended to overcome barriers to accessing blue spaces, providing transformative experiences that nurture empathy and ecological consciousness. Early pilot studies confirm that EotA aesthetic feel, interaction design and game mechanics can enhance human connection with remote ecosystems; further studies will investigate the long-term impact of VR experiences in Ocean conservation.

This paper explores new ways to support blind and low vision (BLV) game stream participants. Prior work on game-aware streaming systems has focused on the potential for viewer interaction and personalization for sighted viewers, but how such systems impact interaction and personalization for BLV viewers remains largely unexplored. Most streaming experiences have significant visual information but no non-visual or sensemaking alternatives, which can exclude BLV viewers from understanding and interacting with the streaming experience. Building on the pre-existing system MARS, we developed a design probe that makes game data available to stream viewers in personalizable visual and non-visual formats. We use this probe to investigate the needs of BLV game stream viewers through qualitative interviews and live prototype testing sessions on Twitch. In addition to the technical contributions of our probe, our work addresses how game-aware streaming technologies can align with the needs and motivations of BLV viewers, and paves the way for novel designs in future iterations of game-aware streaming technologies.

Although the significance of Mental Health (MH) is becoming increasingly more accepted worldwide, the level of MH Literacy (MHL) remains low. Individuals often find it uncomfortable to discuss this crucial topic. Unwillingness to discuss MH can be a result of the stigma surrounding the topic which results in misconceptions, discrimination, and reluctance to seek help or talk openly about MH challenges. Educating individuals about MH and encouraging open discussions are key to reducing stigma. Games have proven their effectiveness for diverse learning purposes. Our goal in this paper is to assess the potential of games and digital displays for MHL education and stigma reduction by incorporating MH educational content into a mobile game with different learning strategies and a large public display to create a community. We compare the pre and post-MHL of users before and after playing our game and the results show an improvement in the MHL of participants. Our paper contributes to game design approaches by identifying mechanisms for educating individuals about MH and our results indicate that the game helps reduce stigma through the use of large displays.

Research on live streaming systems that incorporate real-time data, such as game or viewer data, have been a topic of HCI research for some time. Despite the potential of data-driven game streaming interfaces, translating this research into practice faces two key challenges. First, the design space afforded by data-driven game streaming systems is not yet well understood, making it difficult to identify how designs might meet users' existing and potential needs. Second, adoption of these systems relies on engagement with the entire streaming ecosystem, which includes developers, streamers, moderators, and viewers, rather than with just one group. Through a two-phase design study, we investigate the expectations, desires, and experiences of streaming stakeholders, shedding light on how data-driven game streaming systems can meet their needs. Building upon these insights and drawing upon previous research, we propose a design framework aimed at analyzing and generating data-driven game streaming designs, thereby moving toward formalizing the design and development of such systems.

Artificial intelligence (AI) literacy is especially important for those who may not be well-represented in technology design. We worked with ten Black girls in fifth and sixth grade from a predominantly Black school to understand their perceptions around fair and accountable AI and how they can have an empowered role in the creation of AI. Thematic analysis of discussions and activity artifacts from a summer camp and after-school session revealed a number of findings around how Black girls: perceive AI, primarily consider fairness as niceness and equality (but may need support considering other notions, such as equity), consider accountability, and envision a just future. We also discuss how the learners can be positioned as decision-making designers in creating AI technology, as well as how AI literacy learning experiences can be empowering.

We explore the future of synchronous, multiplayer mobile AR gaming through our game V-Light, which extends current mobile AR game capacities using edge computing. Mobile AR games are currently limited by on-board processing power, while offloading operations to the cloud introduces high latency costs. This is a critical issue for games needing real-time response to player input. V-Light demonstrates how mobile AR games can leverage the power of edge computing, bringing computational resources closer to the user, keeping latency low and bandwidth high. We share our development toolkit, analyze the design and development of V-Light through the lens of an existing model for shared-world mobile AR, and demonstrate that edge computing can provide a “time machine” that lets game designers prototype mobile AR games for devices that do not yet exist.

Families and youth often interact with artificial intelligence (AI) and are stakeholders in technology. However, while AI can enhance interactions with technology, it is well-known that AI can also be biased and cause harm. Therefore, AI literacy is important, such that users understand both some technical components (e.g., training data, what is and is not AI and why), as well as ethical aspects (e.g., bias in society reflected in AI-powered technology) in order to make informed and empowered decisions about interacting with technologies. AI learning opportunities are scarce, and few leverage informal intergenerational learning as an opportunity for youth to engage with topics in AI and ethics. Games are an underexplored yet promising route for intergenerational play and learning for families and youth without much prior exposure to computing or AI. This talk highlights how and why games are particularly fitting to support families in gaining AI literacy through (1) games as an educational tool to build stronger mental models of AI, (2) intergenerational play as a way to scaffold adults and children in having a dialogue about more complex ethical considerations of AI, and (3) position families in roles of influence, where they may be empowered as techno-social change agents. We believe that games can help fill a gap by making AI literacy, an important family matter, accessible to a range of adult and youth learners.

Children interact frequently with artificial intelligence (AI) in their everyday lives. Their understanding of AI technology, however, is often very limited. AI literacy is vital to make informed and empowered decisions about engaging with technology. The ability to imagine future technology designs and applications is a core competency of AI literacy, but few studies have used booklets, a well-studied design fiction tool, as a technique with children in imagining future AI. We explored how a booklet-based design fiction method can support AI literacy with fifth graders (N = 7) from marginalized backgrounds. We describe two benefits of using booklets to create AI design fiction with children in our educational workshop: (1) grounding abstract AI concepts, (2) prolong post session dialogues. This work contributes a new type of scaffolded activity that supports youth learners in AI education.

We present MARS (Metadata Augmented Real-time Streaming), a system that enables game-aware streaming interfaces for Twitch. Current streaming interfaces provide a video stream of gameplay and a chat channel for conversation, but do not allow viewers to interact with game content independently from the steamer or other viewers. With MARS, a Unity game’s metadata is rendered in real-time onto a Twitch viewer’s interface. The metadata can then power viewer-side interfaces that are aware of the streamer’s game activity and provide new capacities for viewers. Use cases include providing contextual information (e.g. clicking on a unit to learn more), improving accessibility (e.g. slowing down text presentation speed), and supporting novel stream-based game designs (e.g. asymmetric designs where the viewers know more than the streamer). We share the details of MARS’ architecture and capabilities in this paper, and showcase a working prototype for each of our three proposed use cases.

The Internet-of-Things (IoT) promises to enhance everyday objects with computing, but rarely enables directly authoring or composing that behavior. Lightweight IoT approaches attach identifiers (e.g., RFID tags) to objects to enable networked services. Typically these tags are passive, and so, depend on activity recognition and predefined context. This limits interaction to invoking predetermined behavior. Instead, this work presents The IoT Codex: a lightweight approach to customizing everyday objects with IoT by enabling interactive attachable IDs (aIDs) to compose software-supported behavior in situ. This work contributes 1) paper engineering techniques to construct aIDs that embody state, and 2) a tangible, end user programming (EUP) language for customizing IoT within symbolic and idiosyncratic contexts. Here, we provide preliminary validation of our approach with an empirically informed design space, sample applications, and a small co-design workshop. In doing so, we offer preliminary evidence for tangible, end user programming to enable meaningful control over IoT services.

Recent developments in explainable AI (XAI) aim to improve the transparency of black-box models. However, empirically evaluating the interpretability of these XAI techniques is still an open challenge. The most common evaluation method is algorithmic performance, but such an approach may not accurately represent how interpretable these techniques are to people. A less common but growing evaluation strategy is to leverage crowd-workers to provide feedback on multiple XAI techniques to compare them. However, these tasks often feel like work and may limit participation. We propose a novel, playful, human-centered method for evaluating XAI techniques: a Game With a Purpose (GWAP), Eye into AI, that allows researchers to collect human evaluations of XAI at scale. We provide an empirical study demonstrating how our GWAP supports evaluating and comparing the agreement between three popular XAI techniques (LIME, Grad-CAM, and Feature Visualization) and humans, as well as evaluating and comparing the interpretability of those three XAI techniques applied to a deep learning model for image classification. The data collected from Eye into AI offers convincing evidence that GWAPs can be used to evaluate and compare XAI techniques. Eye into AI is available to the public: https://dig.cmu.edu/eyeintoai/.

Youth regularly use technology driven by artificial intelligence (AI). However, it is increasingly well-known that AI can cause harm on small and large scales, especially for those underrepresented in tech fields. Recently, users have played active roles in surfacing and mitigating harm from algorithmic bias. Despite being frequent users of AI, youth have been under-explored as potential contributors and stakeholders to the future of AI. We consider three notions that may be at the root of youth facing barriers to playing an active role in responsible AI, which are youth (1) cannot understand the technical aspects of AI, (2) cannot understand the ethical issues around AI, and (3) need protection from serious topics related to bias and injustice. In this study, we worked with youth (N = 30) in first through twelfth grade and parents (N = 6) to explore how youth can be part of identifying algorithmic bias and designing future systems to address problematic technology behavior. We found that youth are capable of identifying and articulating algorithmic bias, often in great detail. Participants suggested different ways users could give feedback for AI that reflects their values of diversity and inclusion. Youth who may have less experience with computing or exposure to societal structures can be supported by peers or adults with more of this knowledge, leading to critical conversations about fairer AI. This work illustrates youths' insights, suggesting that they should be integrated in building a future of responsible AI.

Creating technology products using codesign techniques often results in higher end-user engagement compared to expert-driven designs. Codesign sessions are typically structured in flexible and informal ways to achieve equal design partnerships, especially in adult-child interactions. This generally leads to better design output, however, it may also increase the enactment of socially constructed stereotypes and biases in ways that negatively affect the experiences of racial minorities and girls/women in design spaces. We codesigned a video game with a K-5 afterschool program located in a working-class, rural, predominantly white county over 20 weeks. We uncover ways that the codesign process and different activity types can create a permissive environment for enacting behaviors that are harmful to minorities. We discuss ways to manage and restructure codesign programs to be more conducive for children and adults from diverse backgrounds, ultimately leading to healthier design partnerships.

Reducing uncertainty around the nature of racist interactions is one of the key motivations driving individual behaviors for coping with those incidents. However, there are few appropriate technologies to support BIPOC (Black, Indigenous, People of Color) in engaging in social uncertainty reduction around this vulnerable, sensitive topic. This paper reports on an exploratory design study investigating how social technology might facilitate uncertainty reduction through three “provotypes” - provocative prototypes of user-generated speculative design concepts. U.S.-based participants engaged with the provotypes through an interactive fiction to explore their usefulness in the context of a racist microaggression. Results showed that engaging the provotypes through interactive fiction facilitated complex and productive interactions and critiques. This work contributes a novel method for conducting exploratory design, remote user studies using interactive fiction as well as priorities, tensions, and further information what role, if any, technology might play in managing racist interactions.

In this paper we share academic game development challenges from the digital game Bloomwood Stories: Block Party [4]. We introduce the main characteristics of our game, as well as the theories it is based on and its transformational goals. We then describe our game development process, which took place over nearly two years, and what each of its phases included. During this process, we observed many problems of structural misalignment between game development and academia. We therefore share the challenges we observed in this area, strategies we used to address them, and ideas for how teams might mitigate these challenges in the future. Finally, we share our vision of opportunities that arise from developing games in academic contexts, and how the two institutional contexts can come to complement one another.

Youth regularly interface with AI technology that leverages supervised machine learning. However, it is well-known that biased training data can result in harmful algorithmic bias. Thus, it is important that youth and families understand training data in machine learning. We present Data Detectives, a child-friendly tabletop card game about training data. Based on three research-based design principles: low-stakes experimentation to support curiosity, games facilitating conversation, and tangible and embodied learning for abstract concepts, the game supports learning the high-level mechanics of training data in supervised machine learning, as well as practicing critical discussion of training data related to algorithmic bias. Contributing to AI literacy opportunities, this game aims to facilitate playful peer-peer and child-parent learning.

Training AI systems requires large datasets. While there are a range of existing methods for collecting such data, such as paid work on crowdsourcing platforms, the strengths and weaknesses of each method leads us to believe that new, complementary methods are needed. The Polyphonic project contributes a novel method for collecting real-world data by piggybacking on game streaming communities such as Twitch, which capture over a trillion minutes of viewer attention a year. By embedding activities within the sociotechnical context of the stream, we can leverage some of this attention for data collection and processing. In this paper, we describe the design and implementation of a proof-of-concept system for collecting home audio data. We conducted a field study in four live streams and found that our proof-of-concept effectively supports data capture. We also contribute further design insights about stream-based data collection systems.

We present an autobiographical design journey exploring the experience of returning to long-term single player games. Continuing progress from a previously saved game, particularly when substantial time has passed, is an understudied area in games research. To begin our exploration in this domain, we investigated what the return experience is like first-hand. By returning to four long-term single player games played extensively in the past, we revealed a phenomenon we call The Pivot Point, a ‘eureka’ moment in return gameplay. The pivot point anchors our design explorations, where we created prototypes to leverage the pivot point in reconnecting with the experience. These return experiences and subsequent prototyping iterations inform our understanding of how to design better returns to gameplay, which can benefit both producers and consumers of long-term single player games.

Live streaming sites such as Twitch offer new ways for remote audiences to engage with and affect gameplay. While research has considered how audiences interact with games, HCI lacks clear demarcations of the potential design spaces for audience participation. This paper introduces and validates a theme map of audience participation in game live streaming for student designers. This map is a lens that reveals relationships among themes and sub-themes of Agency, Pacing, and Community—to explore, reflect upon, describe, and make sense of emerging, complex design spaces. We are the first to articulate such a lens, and to provide a reflective tool to support future research and education. To create the map, we perform a thematic analysis of design process documents of a course on audience participation for Twitch, using this analysis to visually coordinate relationships between important themes. To help student designers analyze and reflect on existing experiences, we supplement the theme map with a set of mapping procedures. We validate the applicability of our map with a second set of student designers, who found the map useful as a comparative and reflective tool.

Ranging from subtle to overt, unintentional to systemic, navigating racism is additional everyday work for many people. Yet the needs of people who experience racism have been overlooked as a fertile ground for better technology. Through a series of workshops we call Foundational Fiction, we engaged BIPOC (Black, Indigenous, People of Color) in participatory design to identify qualities of technology that can support people coping before, during, and after a racist interaction. Participants developed storyboards for digital tools that offer advice, predict consequences, identify racist remarks and intervene, educate both targets and perpetrators about interpersonal and systemic racism, and more. In the paper we present our workshop method utilizing interactive fiction, participants’ design concepts, prevalent themes (reducing uncertainty and offering comfort), and we provide critical analysis of the complexity of technology in these contexts. This work identifies specific opportunities for exploring anti-racist social tools.

Adaptive Collaborative Learning Support (ACLS) systems improve collaboration and learning for students over individual work or collaboration with non-adaptive support. However, many ACLS systems are ill-suited for rural contexts where students often need multiple kinds of support to complete tasks, may speak languages unsupported by the system, and require more than pre-assigned tutor-tutee student pairs for more equitable learning. We designed an intervention that fosters more equitable help-seeking by automatically detecting student struggles and prompts them to seek help from specific peers that can help. We conducted a mixed-methods experimental study with 98 K-3 students in a rural village in Tanzania over a one-month period, evaluating how the system affects student interactions, system engagement, and student learning. Our intervention increased student interactions by almost 4 times compared to the control condition, increased domain knowledge interactions, and propelled students to engage in more cognitively challenging activities.

AI-enabled decision support systems have repeatedly failed in real world applications despite the underlying model operating as designed. Often this was because the system was used in an unexpected manner. Our goal is to enable better prediction of how systems will be used prior to their implementation as well as to improve existing designs, by taking human behavior into account. There are several challenges to collecting such data. Not having access to an existing prediction engine requires the simulation of such a system's behavior. This simulation must include not just the behavior of the underlying model but also the context in which the decision will be made in the real world. Additionally, collecting statistically valid samples requires that test subjects make repeated choices under slightly varied conditions. Unfortunately, in such repetitious conditions fatigue can quickly set in. Games provide us the ability to address both of these challenges by providing both systems context and narrative context. Systems context can be used to convey some or all of the information the player needs to make a decision in the game environment itself, which can help avoid the onset of fatigue. Narrative context can provide a broader environment within which the simulated system operates, adding a sense of progress, showing the effect of decisions, adding perceived social norms, and setting incentives and stakes. This broader environment can further prevent player fatigue while replicating many of the external factors that might affect choices in the real world. In this paper we describe the design of the Human-AI Decision Evaluation System (HADES), a test harness capable of interfacing with a game environment, simulating the behavior of an AI-enabled decision support system, and collecting the results of human decision making based upon such a system's predictions. Additionally, we present an analysis of data collected by HADES while interfaced with a visual novel game focused on software cyber-risk assessment.

Over 2 million people across the United States are living with aphasia, the loss of language due to acquired brain injury. Aphasia is an invisible disability that may come with negative consequences for communication, community participation, and quality of life. Game-based rehabilitation is a promising solution to address unmet long-term recovery and psychosocial needs for people with aphasia. In this paper, we describe a participatory game design process that engages people with aphasia (PwA) in the creation of three hybrid digital-analog games. We detail methods for facilitating collaboration across language barriers and divergent professional expertise based on interviews and participant observations throughout our iterative design process. We also contribute a set of design principles synthesized from aphasia rehabilitation research, interviews and community data. We conclude with recommendations for pursuing community-empowered aphasia game design for this underserved population based on reflection from our co-design experience.

Most American girls are not meeting physical activity guidelines, placing them at risk for adverse health consequences. In response, our team developed Frolic, an evidence-based mobile application to address this problem through play. Frolic uses a socio-ecological framework and behavioral design principles to address barriers and social norms that are specific to girls. Parents are leveraged as important sources of support and motivation, with key design elements to help girls initiate play, adapt to the space, and play independently. The current paper contributes design principles for creating socio-ecological activity games for girls. In addition, we contribute the design of Frolic itself, a game constructed according to these guidelines, and outline future intervention studies with the app itself. Finally, we provide the perspectives of professional game designers and health experts on our work and interpretative insights for game designers and researchers who hope to work in this space.

A major reason why people don't use security tools online is that they perceive them as difficult and challenging, resulting in the lack of self-efficacy. Previous research has looked at improving user security attitude and practices through a variety of interventions, including transformational games. These games, targeted at improving security attitude and promoting change through gameplay, offer a new perspective on cybersecurity education. In this research we present the design and evaluation of Hacked Time, a desktop game that uses an integrative approach that incorporates Bandura's self-efficacy design framework to improve player self-efficacy. Using a randomized control trial (n=178), we demonstrate that our game is effective in improving player's security attitude and self-efficacy for using cybersecurity tools. We discuss how our design pattern can serve as an exemplar to enhance player self-efficacy in other fields.

By leveraging approaches from other disciplines, designers can expand the boundaries of interaction design to tackle complex socio-technical problems. To address the challenges of networked social justice movements, we developed a workshop for designers and social justice activists based in Viewpoints and Composition, a philosophy and set of techniques for the theatre. Building on other experience prototyping and somatic methods, the workshop leads participants through the design of a hypothetical internet-enabled social justice campaign, encouraging them to imagine the felt-experience of networked social justice movement building in a socio-spatial context. We conclude with insights from the workshop and plans to further develop these techniques.

Feedback is a key element of project-based learning, but only if students reflect on and learn from the feedback they receive. Students often struggle to deeply engage with feedback, whether due to lack of confidence, time, or skill. This work seeks to identify challenges that make reflecting on feedback difficult for students, and to design possible solutions for supporting reflection. Through observing two university game design courses, our research found that without concrete reflection strategies, students tended to be attracted to feedback that looks useful, but does not necessarily them move forward. When we introduced three different reflection scaffolds to support students, we found that the most effective approach promoted interactive learning by allowing time for self-reflection before team reflection, offering time limits, providing activities for feedback prioritization, helping teams align their goals, and equalizing team member participation. We present design guidelines for future systems to support reflection on feedback.

There has been a great deal of research regarding the ways that people conceptualize and interact with places they call "home." This work has been extended to virtual reality primarily in the context of design tools. Here, we explore the idea of a hybrid virtual-physical home that uses virtual space to supplement an existing physical home. We identify variation in the spatial context of place attachment to homes. A user study (N = 25) revealed the expectations and needs these groups have for virtual home spaces, including security, familiarity, and community. We prototyped and playtested three virtual rooms, and identified design features that supported feelings of home. Finally, we present challenges to designing home-like VR environments that can shape future research in this area. As virtual reality grows increasingly accessible, these findings will inform the design of virtual spaces.

A sleep deficit has far-reaching consequences, but for many people, healthy sleep is not a priority or a possibility. We explore the potential for "sleepy games" as a genre of transformational games. To explore this design space, we prototyped nine games through an iterative design process. Based on analysis of design decisions and the games as artifacts, we identify seven design challenges for sleepy games: agency and control; physiological and mental arousal; intervention timing; social embeddedness; multisensory experience; vulnerability; and identity and values. We expand on three games with playtesting to show how these design challenges unfold for players in practice, show the impact on players' lives, and discuss sleepy games as creative, social, and situated practices.

In the course of every member's integration into an online community, a decision must be made to participate for the first time. The challenges of effective recruitment, management, and retention of new users have been extensively explored in social computing research. However, little work has looked at in-the-moment factors that lead users to decide to participate instead of "lurk", conditions which can be shaped to draw new users in at crucial moments. In this work we analyze 183 million messages scraped from chatrooms on the livestreaming platform Twitch in order to understand differences between first-time participants' and regulars' behaviors and to identify conditions that encourage first-time participation. We find that presence of diverse types of users increases likelihood of new participation, with effects depending on the size of the community. We also find that information-seeking behaviors in first-time participation are negatively associated with retention in the short and medium term.

While the majority of research in chatbot design has focused on creating chatbots that engage with users one-on-one, less work has focused on the design of conversational agents for online communities. In this paper we present results from a three week test of a social chatbot in an established online community. During this study, the chatbot "grew up" from "birth" through its teenage years, engaging with community members and "learning" vocabulary from their conversations. We discuss the design of this chatbot, how users' interactions with it evolved over the course of the study, and how it impacted the community as a whole. We discuss how we addressed challenges in developing a chatbot whose vocabulary could be shaped by users, and conclude with implications for the role of machine learning in social interactions in online communities and potential future directions for design of community-based chatbots.

The Internet-of-things (IoT) embeds computing in everyday objects, but has largely focused on new devices while ignoring the home's many existing possessions. We present a field study with 10 American families to understand how these possessions could be included in the smart home through upcycling. We describe three patterns for how families collaborate around home responsibilities; we explore families' mental models of home that may be in tension with existing IoT systems; and we identify ways that families can more easily imagine a smart home that includes their existing possessions. These insights can help us design an upcycled approach to IoT that supports users in reconfiguring objects (and social roles as mediated by objects) in a way that is sensitive to what will be displaced, discarded, or made obsolete. Our findings inform the design of future lightweight systems for the upcycled home.

Over 35% of Americans belong to racial minority groups. Racism targeting these individuals results in a range of harmful physical, psychological, and practical consequences. The present work aims to shed light on the current sense-making and support-seeking practices exhibited by targets of racism, as well as to identify the core needs and barriers that future socio-technical interventions could potentially address. The long-term goal of this work is to understand how CSCW researchers and designers could best support members of marginalized groups to make sense of and to seek support for experiences with racism. Narrative episode interviews with targets of racism revealed a number of key entry points for intervention. For example, participants' personal stories confirmed that uncertainty, both about the nature and consequences of the experience of racism, is a key motivator for support-seeking. In addition, despite the need for support, participants largely do not trust public forms of social media for support-seeking. We discuss how participants' accounts of the complex labor involved in determining who "gets it" in identifying potential supporters, and in navigating the complexities of trust and agency in sharing their experiences, present clear implications for the design of new socio-technical platforms for members of racial minority groups.

Augmented reality (AR) games have been growing in popularity in recent years. However, current AR games offer limited opportunities for a synchronous multiplayer experience. This paper introduces a model for designing AR experiences in which players inhabit a shared, real-time augmented environment and can engage in synchronous and collaborative interactions with other players. We explored the development of this model through the creation of Brick, a two-player mobile AR game at the room scale. We refined Brick over multiple rounds of iteration, and we used our playtests to investigate a range of issues involved in designing shared-world AR games. Our findings suggest that there are five major categories of interactions in a shared-world AR system: single-player, intrapersonal, multiplayer, interpersonal, and environmental. We believe that this model can support the development of collaborative AR games and new forms of social gameplay.

Peer feedback is essential for learning in project-based disciplines. However, students often need guidance when acting as either a feedback provider or a feedback receiver, both to gain from peer feedback and to criticize their peers' work. This paper explores how to more effectively scaffold this exchange such that peers more deeply engage in the feedback process. Within a game design course, we introduced different processes for feedback receivers to write questions to guide peer feedback. Feedback receivers wrote four main types of guiding questions: improve, share, brainstorm, critique. We found that "improve'' questions tended to lead to better feedback (more specific, critical, and actionable) than other question types, but feedback receivers wrote improve questions least often. We offer insights on how best to scaffold the question-writing process to facilitate peer feedback exchange.

Chatbots have grown as a space for research and development in recent years due both to the realization of their commercial potential and to advancements in language processing that have facilitated more natural conversations. However, nearly all chatbots to date have been designed for dyadic, one-on-one communication with users. In this paper we present a comprehensive review of research on chatbots supplemented by a review of commercial and independent chatbots. We argue that chatbots' social roles and conversational capabilities beyond dyadic interactions have been underexplored, and that expansion into this design space could support richer social interactions in online communities and help address the longstanding challenges of maintaining, moderating, and growing these communities. In order to identify opportunities beyond dyadic interactions, we used research-through-design methods to generate more than 400 concepts for new social chatbots, and we present seven categories that emerged from analysis of these ideas.

The internet-of-things (IoT) carries substantial costs by urging households to replace their possessions with new, internet connected versions of everyday objects. Beyond financial, these costs include waste, work to arrange and orchestrate objects to suit households, and that of acquiring new skills. Upcycling domestic objects could offer households greater discretion and control over these costs by supporting the ability to tailor IoT to the home. To understand how households might do this, we conducted a home study with 10 diverse American households over 7 days to surface the approaches families are likely to use when tailoring IoT to their existing possessions. We asked family members to enact their process using endowed sticker props---IoT Stickers---to modify objects in their home. We develop a framework of how families make light weight modifications of domestic possessions, summarize trends of their object modifications, and describe the burdens such a system could impose.

Idle games are a recent minimalist gaming phenomenon in which the game is left running with little player interaction. We deepen understanding of idle games and their characteristics by developing a taxonomy and identifying game features. This paper examines 66 idle games using a grounded theory approach to analyze play, game mechanics, rewards, interactivity, progress rate, and user interface. To establish a clearly bounded definition of idle games, we analyzed 10 non-idle games with the same approach. We discuss how idle games move players from playing to planning, how they question dominant assumptions about gameplay, and their unusual use of resources such as player attention and computer cycles. Our work illuminates opportunities for the design of idle games, suggests design implications, and provides a framework for researchers to clearly articulate questions about this genre.

In the physical world, teammates develop situation awareness about each other's location, status, and actions through cues such as gaze direction and ambient noise. To support situation awareness, distributed multiplayer games provide awareness cues - information that games automatically make available to players to support cooperative gameplay. The design of awareness cues can be extremely complex, impacting how players experience games and work with teammates. Despite the importance of awareness cues, designers have little beyond experiential knowledge to guide their design. In this work, we describe a design framework for awareness cues, providing insight into what information they provide, how they communicate this information, and how design choices can impact play experience. Our research, based on a grounded theory analysis of current games, is the first to provide a characterization of awareness cues, providing a palette for game designers to improve design practice and a starting point for deeper research into collaborative play.

Curiosity is a critical skill that spurs learning, but is often found to decline with age and schooling. Recent research has shown that peer interaction may serve a special role in inducing curiosity through increased uncertainty and conceptual conflicts, since peers have similar authority in knowledge. For a virtual agent to stimulate curiosity, it should be able to generate curiosity-eliciting verbal behaviors such as hypothesis verbalization and argumentation, in the manner that simulates peer-like cognitive and behavioral abilities. In this paper, we design and implement a virtual peer that can carry out key curiosity-eliciting science talk during a dialog-based multi-party board game. We propose a child-centered and data-driven approach to simulate the latent reasoning process of young children and age-appropriate language during open-ended game play. In particular, we use a combination of child knowledge-graph construction and child-child interaction driven modeling to generate game appropriate behaviors that are compatible with 9-14 year old children. Encouraging human evaluation of the generated behaviors and generalizability of the generation framework to other tasks opens up new directions in incorporating open-endedness and science talk in virtual agents that will make them truly play a peer role in learning.

Women remain underrepresented in many fields in computer science, particularly at higher levels. In academia, success and promotion are influenced by a researcher's publication record. In many fields, including computer science, multi-author papers are the norm. Evidence from other fields shows that author order norms can influence the assignment of credit. We conduct interviews of students and faculty in human-computer interaction (HCI) and machine learning (ML) to determine factors related to assignment of author order in collaborative publication. The outcomes of these interviews then informed metrics of interest for a bibliometric analysis of gender and collaboration in research papers published from 1996 to 2016 in three top HCI and ML conferences. Based on our findings, we make recommendations for assignment of credit in multi-author papers and interpretation of author order, particularly in regard to how this area affects women.

Bots, or programs designed to engage in social spaces and perform automated tasks, are typically understood as automated tools or as social "chatbots." In this paper, we consider their place alongside users in the emerging social ecosystem of audience participation platforms, through the application of Structural Role Theory. We perform a large-scale analysis of activity levels of user-designed bots on Twitch, finding that they communicate at a much greater rate than any other type of user. We build on a classification scheme derived from prior literature on bot functionalities to identify the roles bots play on Twitch, how these roles vary across different types of Twitch communities, and how users engage with them and vice versa. We conclude with a discussion of what roles are missing and where opportunities lie to re-conceptualize and re-design bots as social actors who help communities grow and evolve.

Games for health (G4H) aim to improve health outcomes and encourage behavior change. While existing theoretical frameworks describe features of both games and health interventions, there has been limited systematic investigation into how disciplinary and interdisciplinary stakeholders understand design features in G4H. We recruited 18 experts from the fields of game design, behavioral health, and games for health, and prompted them with 16 sample games. Applying methods including open card sorting and triading, we elicited themes and features (e.g., real-world interaction, game mechanics) around G4H. We found evidence of conceptual differences suggesting that a G4H perspective is not simply the sum of game and health perspectives. At the same time, we found evidence of convergence in stakeholder views, including areas where game experts provided insights about health and vice versa. We discuss how this work can be applied to provide conceptual tools, improve the G4H design process, and guide approaches to encoding G4H-related data for large-scale empirical analysis.

Audience Participation Games challenge traditional assumptions about gameplay by blurring the line between audience and player, allowing audience members to impact gameplay in a meaningful way. Their recent rise in popularity has created new opportunities for game research and development. To better understand this design space, we developed several versions of two prototype games as design probes. We livestreamed them to an online audience in order to develop a framework for audience motivations and participation styles, to explore ways in which mechanics can affect audience members' sense of agency, and to identify promising design spaces. Our results show the breadth of opportunities and challenges that designers face in creating engaging Audience Participation Games.

Peer feedback is a central activity for project-based design education. The prevalence of devices carried by students and the emergence of novel peer feedback systems enables the possibility of collecting and sharing feedback immediately between students during class. However, pen and paper is thought to be more familiar, less distracting for students, and easier for instructors to implement and manage. To evaluate the efficacy of in-class digital feedback systems, we conducted a within-subjects study with 73 students during two weeks of a game design course. After short student presentations, while instructors provided verbal feedback, peers provided feedback either on paper or through a device. The study found that both methods yielded comments of similar quality and quantity, but the digital approach provided additional ways for students to participate and required less effort from the instructors. While both methods produced similar behaviors, students held inaccurate perceptions about their behavior with each method. We discuss design implications for technologies to support in-class feedback exchange.

Making MOOCs accessible to English Language Learners (ELLs) requires that students understand the language of instruction, and that instructional strategies address their unique learning challenges. Through the analysis of clickstream log data gathered from two MOOC courses deployed on Coursera, Introduction to Psychology and Statistical Thermodynamics, we show that ELL students exhibit distinct struggle behaviors in video portions without visual aids e.g., narrations without slides. Our findings challenge widely accepted multimedia design principles such as the split attention effect, provide insights into designing MOOC videos, and emphasize the need for adaptivity to increase MOOC access for ELLs.

Peer feedback systems enable students to get feedback without substantially burdening the instructor. However, current systems typically ask students to provide feedback after class; this introduces challenges for ensuring relevant, timely, diverse, and sufficient amounts of feedback, and reduces time available for student reflection. This paper explores the current landscape of peer feedback tools and introduces a novel system for in-class peer review called PeerPresents where students can quickly exchange feed-back on projects without being burdened by additional work outside of class. Through an exploratory study with Google docs and a preliminary evaluation of PeerPresents, we find students can receive immediate, copious, and diverse peer feedback through a structured in-class activity. Students also described the feedback they received as helpful and reported that they gave more feedback than without using the system. These early results demonstrate the potential benefits of in-class peer feedback systems.

Although xMOOCs are not designed to directly engage students via social media platforms, some students in these courses join MOOC-associated Facebook groups. This study explores the prevalence of Facebook groups associated with courses from MITx and HarvardX, the geographic distribution of students in such groups as compared to the courses at large, and the extent to which such groups are location and/or language homophilous. Results suggests that a non-trivial number of MOOC students engage in Facebook groups, that learners from a number of non-U.S. locations are disproportionately likely to participate in such groups, and that the groups display both location and language homophily. These findings have implications for how MOOCs and social media platforms can support learners from non-English speaking contexts.

Open access and low cost make Massively Open Online Courses (MOOCs) an attractive learning platform for students all over the world. However, the majority of MOOCs are deployed in English, which can pose an accessibility problem for students with English as a Second Language (ESL). In order to design appropriate interventions for ESL speakers, it is important to correctly identify these students using a method that is scalable to the high number of MOOC enrollees. Our findings suggest that a new metric, browser language preference, may be better than the commonly-used IP address for inferring whether or not a student is ESL.

Massive Open Online Courses (MOOCs) have the potential to bridge education and literacy gaps by offering high quality, free courses to anyone with an Internet connection. MOOCs in their present state, however, may be relatively inaccessible to non-native English speakers, as a majority of MOOC content is in the English language. While a potential solution is to translate all MOOC content into all languages, it is not known whether this solution will satisfy the learning goals of all English as a Second Language (ESL) speakers. Through a series of interviews, we investigate ESL speakers' motivations for taking MOOCs and other online courses. Our findings show that ESL speakers have a variety of motivations for taking online courses that are not captured in current surveys, which implies that current one-size-fits-all approaches to increasing MOOC accessibility for learners with a first language other than English may not be effective. Rather, offering learners individualized tools based on their motivation and needs may be more effective.

Existing datasets tell us only a partial story about the contextual factors that impact learners in Massive Online Open Courses (MOOCs). Information about race/ethnicity, education, and income helps us understand socioeconomic status, but such data is notoriously difficult to collect in an international context. Extant MOOC studies have not paid due attention to socioeconomic variables; they have either taken a U.S.-centric approach, ignored important country-specific dimensions of variables, or failed to ask about certain variables altogether, such as race/ethnicity. During a qualitative study of 24 self-regulated learners from population groups underrepresented in MOOCs, we piloted a short U.S.-centric demographic questionnaire. Preliminary results suggest that a large-scale survey designed for both cross-national and country-specific analyses would provide valuable information to MOOC researchers.