IU Indianapolis ScholarWorks :: Browsing by Author "Dombrowski, Lynn"

Browsing by Author "Dombrowski, Lynn"

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A Model of Project Continuation in Game Jams and Hackathons
(2024-08) Faas, Travis Byron; Miller, Andrew; Dombrowski, Lynn; Brady, Erin; Hickey, Daniel
Game jams and hackathons are events where individuals design and build new technology prototypes in a short timeframe. Prototypes made at hackathons are often abandoned after the event and are never finished or used by their intended audiences. Though continued work on prototypes is not the only goal of hackathons, many expect that some hackathon projects will continue to be developed to fulfill the civic, educational, or entrepreneurial goals of hackathon organizers and attendees. To assist hackathon organizers in running hackathons that produce continued projects, I present in this document a model of project continuation in online hackathons and a tool that directs conversations that develops the necessary components of continuation. This model was developed through three studies: a design study that generated the design for a bot to be used in an online game jam that directs users in breaking the boundedness of their game concept, a deployment study where the bot was deployed and used in an online game jam, and a longitudinal study that followed the continuation practices of individuals who used the bot during the jam. In the presented continuation model, I highlight how recent personal interests generate an extended development context that reduces the boundedness of game jams and show how regular sharing and discussion of progress creates social investment in the success of projects that contributes to continuation intention and support. This continuation model requires a resting period post-hackathon, which sometimes generates conceptual continuation where a project is abandoned but the major project concepts are explored in later projects. Taking this idea of concept continuation further, I offer suggestions on how to gain continuation in hackathons by reducing their time-boundedness and making the events more permeable to allow for prior-existing projects to be accepted and further developed at these events.
Academic Accomplices: Practical Strategies for Research Justice
(ACM, 2019-06) Asad, Mariam; Dombrowski, Lynn; Costanza-Chock, Sasha; Erete, Sheena; Harrington, Christina; Human-Centered Computing, School of Informatics and Computing
This workshop brings together folks currently or interested in becoming academic accomplices, or scholars committed to leveraging resources and power to support the justice work of their community collaborators. Academic accomplices are necessary for research justice-research that materially challenges inequity-and owe it to community partners to challenge underlying oppressive structure and practices as perpetuated through academic research. The goal of this workshop is to discuss concrete strategies for challenging oppression through research methodologies, physical or institutional resources, and/or pedagogy. This workshop will generate practical strategies for research justice for DIS and HCI scholars.
aiDance: A Non-Invasive Approach in Designing AI-Based Feedback for Ballet Assessment and Learning
(2021-12) Trajkova, Milka; Cafaro, Francesco; Bolchini, Davide; Dombrowski, Lynn; Fusco, Judi; Hickey, Daniel; Magerko, Brian; Toenjes, John
Since its codified genesis in the 18th century, ballet training has largely been unchanged: it relies on tools that lack adequate support for both dancers and teachers. In particular, providing effective augmented feedback remains challenging as it can be limited, not always provided at the proper time, and highly subjective as it depends on the visual experience of an instructor. Designing a ballet assessment and learning tool with the aim of achieving a meaningful educational experience is an interdisciplinary challenge due to the fine motor movements and patterns of the art form. My work examines how we can effectively augment ballet learning in three phases using mixedmethod approaches. First, through my past professional experience as a ballet dancer, I explore how the design and in-lab evaluation of augmented visual and verbal feedback can improve the technical performance for novices and experts via remote learning. Second, I investigate the learning and teaching challenges that currently exist in traditional in-person training environments for dancers and teachers. Furthermore, I study the current technology use, reasons for non-use, and derive design requirements for future use. Lastly, I focus on how we can design aiDance, an AI-based feedback tool that attempts to represent an affordable and non-invasive approach that augments teachers’ abilities to facilitate assessment in the 21st century and pirouette towards the enhancement of learning. With this empirical work, I present insights that inform the HCI community at the intersection of dance and design in addressing the first steps towards the standardization of motor learning feedback.
Asymmetries in Online Job-Seeking: A Case Study of Muslim-American Women
(ACM, 2021-10) Afnan, Tanisha; Rabaan, Hawra; Jones, Kyle M. L.; Dombrowski, Lynn; Human-Centered Computing, School of Informatics and Computing
As job-seeking and recruiting processes transition into digital spaces, concerns about hiring discrimination in online spaces have developed. Historically, women of color, particularly those with marginalized religious identities, have more challenges in securing employment. We conducted 20 semi-structured interviews with Muslim-American women of color who had used online job platforms in the past two years to understand how they perceive digital hiring tools to be used in practice, how they navigate the US job market, and how hiring discrimination as a phenomenon is thought to relate to their intersecting social identities. Our findings allowed us to identify three major categories of asymmetries (i.e., the relationship between the computing algorithms' structures and their users' experiences): (1) process asymmetries, which is the lack of transparency in data collection processes of job applications; (2) information asymmetries, which refers to the asymmetry in data availability during online job-seeking; and (3) legacy asymmetries, which explains the cultural and historical factors impacting marginalized job applicants. We discuss design implications to support job seekers in identifying and securing positive employment outcomes.
Beyond cute: exploring user types and design opportunities of virtual reality pet games
(ACM, 2017-11) Lin, Chaolan; Dombrowski, Lynn; Faas, Travis; Brady, Erin; Human-Centered Computing, School of Informatics and Computing
Virtual pet games, such as handheld games like Tamagotchi or video games like Petz, provide players with artificial pet companions or entertaining pet-raising simulations. Prior research has found that virtual pets have the potential to promote learning, collaboration, and empathy among users. While virtual reality (VR) has become an increasingly popular game medium, litle is known about users' expectations regarding game avatars, gameplay, and environments for VR-enabled pet games. We surveyed 780 respondents in an online survey and interviewed 30 participants to understand users' motivation, preferences, and game behavior in pet games played on various medium, and their expectations for VR pet games. Based on our findings, we generated three user types that reflect users' preferences and gameplay styles in VR pet games. We use these types to highlight key design opportunities and recommendations for VR pet games.
Bottom-Up Organizing with Tools from On High: Understanding the Data Practices of Labor Organizers
(ACM, 2020-04) Khovanskaya, Vera; Sengers, Phoebe; Dombrowski, Lynn; Human-Centered Computing, School of Informatics and Computing
This paper provides insight into the use of data tools in the American labor movement by analyzing the practices of staff employed by unions to organize alongside union members. We interviewed 23 field-level staff organizers about how they use data tools to evaluate membership. We find that organizers work around and outside of these tools to develop access to data for union members and calibrate data representations to meet local needs. Organizers mediate between local and central versions of the data, and draw on their contextual knowledge to challenge campaign strategy. We argue that networked data tools can compound field organizers' lack of discretion, making it more difficult for unions to assess and act on the will of union membership. We show how the use of networked data tools can lead to less accurate data, and discuss how bottom-up approaches to data gathering can support more accurate membership assessments.
Computer-Supported Career Development in The Future of Work
(ACM, 2018-11) Hui, Julie; Gerber, Elizabeth M.; Dombrowski, Lynn; Gray, Mary L.; Marcus, Adam; Salehi, Niloufar; Human-Centered Computing, School of Informatics and Computing
As people increasingly work different jobs, the respon-sibility of building long-term career satisfaction and stability increasingly falls more on the workers rather than individual employers. With technologies playing a central role in how people choose and access employ-ment opportunities, it is necessary to understand how online technologies are shaping career development. We bring together leading human-computer interaction researchers, industry members, and community organ-izers, who have worked with systems and people across the socio-economic spectrum during the career devel-opment process. We will discuss research on the role of online technologies in career development, including but not limited to topics in crowd work, social media sites, and freelance work sites.
Course of Life: A Transformative Design Inquiry into the Modern Academic CV
(2023-08) Ganci, Aaron M.; Wheeler, Rachel; Dombrowski, Lynn; Hong, Youngbok; Haberski, Raymond J.
This project addresses the growing issue of burnout among U.S. higher education faculty. An inquiry into the causes of faculty burnout points to weaknesses within the American higher education system that have been exacerbated by a network of external and internal pressures. From the outside, institutions are being pressured to act more like corporations and embrace neoliberal values. At the same time, the societal pressure to democratize American institutions by asking them to become inclusive in their policies and practices is felt acutely in academia. These aims—productivity and inclusive democratization– are often in tension in academia, with overseeing bodies like trustees and legislatures prizing measurable, economic productivity, and faculty and administrative bodies prioritizing gender and racial inclusivity. There is one place where all these pressures play out: the academic CV. The CV is an ideal lens through which to examine these dynamics as it struggles to link faculty, administrators, universities, and funding agencies, in their attempt to convey both neoliberal and inclusive values. Many stakeholders trying to construct different narratives leads to an inherent tension and leaves no one satisfied. To make matters worse, the growing use of digital analytic software in place of traditional CVs has led to an imbalance, with neoliberal success indicators overshadowing inclusive ones. This disparity negatively impacts faculty wellbeing, especially faculty in underrepresented demographics, as their sense of personal achievement is diminished under these criteria and raises the question: how might the CV evolve to balance the needs of all of its stakeholders? Doing so may ease some of the tension within academic life and enhance faculty wellbeing. This study employs a transformative research design to explore whether the CV can be reformed to rebalance the tensions within academia. The mixed-method qualitative study draws on interviews and participatory co-design activities, and a constructive design process to explore divergent ways the CV might evolve to benefit faculty more. After evaluating the designs through transformative criteria, new insights are developed about the nature of modern academic work and spheres of action that can lead to faculty wellbeing.
Data-Driven Accountability: Examining and Reorienting the Mythologies of Data
(2020-05) Verma, Nitya; Dombrowski, Lynn; Bolchini, Davide; Young, Alyson; Seybold, Peter; Voida, Amy; Muller, Michael
In this work, I examine and design sociotechnical interventions for addressing limitations around data-driven accountability, particularly focusing on politically contentious and systemic social issues (i.e., police accountability). While organizations across sectors of society are scrambling to adopt data-driven technologies and practices, there are epistemological and ethical concerns around how data use influences decisionmaking and actionability. My work explores how stakeholders adopt and handle the challenges around being data-driven, advocating for ways HCI can mitigate such challenges. In this dissertation, I highlight three case studies that focus on data-driven, human-services organizations, which work with at-risk and marginalized populations. First, I examine the tools and practices of nonprofit workers and how they experience the mythologies associated with data use in their work. Second, I investigate how police officers are adopting data-driven technologies and practices, which highlights the challenges police contend with in addressing social criticisms around police accountability and marginalization. Finally, I conducted a case study with multiple stakeholders around police accountability to understand how systemic biases and politically charged spaces perceive and utilize data, as well as to develop the design space around how alternative futures of being data-driven could support more robust and inclusive accountability. I examine how participants situate the concepts of power, bias, and truth in the data-driven practices and technologies used by and around the police. With this empirical work, I present insights that inform the HCI community at the intersection of data design, practice, and policies in addressing systemic social issues.
Daughters of Men: Saudi Women's Sociotechnical Agency Practices in Addressing Domestic Abuse
(Association of Computing Engineering, 2020-12) Rabaan, Hawra; Young, Alyson L.; Dombrowski, Lynn; Human-Centered Computing, School of Informatics and Computing
While domestic abuse is an all too common experience for women worldwide, how people experience the abuse and their resources to deal with the abuse differ. In this qualitative, interview-based study, we examine Saudi women's domestic safety concerns living in Saudi Arabia and the United States. Based on non-Western Islamic feminist views of agency, we identify three key practices, focused on how women resist or deal with their domestic violence. For each practice, we highlight how interwoven cultural, religious, and political contexts impact Saudi women's ability to recognize and deal with domestic abuse. We attend to technology's role in enabling or hindering women's agency. These practices include: 1) recognizing abuse, where women identify abusive situations, 2) managing abuse, where women find ways to cope with ongoing or anticipated abuse within their constraints and resources, and 3) seeking non-abusive futures, where women decide how to mitigate the abuse or leave their abuser. Given domestic violence's complicated nature, we highlight several key design recommendations based on women's values.

Browsing by Author "Dombrowski, Lynn"

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