Archive of Previously Funded Projects

  • Research notes on whiteboard


The College of Information Studies is elated to present the winners of the Research Improvement Grants (RIGs) Program! These projects are creating and disseminating high-impact research results to make the world a better place for all.

Designing and Evaluating a Conversational Agent for Mental Health Support​

  • Investigator: Yuting Liao
  • Title: Designing and Evaluating a Conversational Agent for Mental Health Support
  • Semester Awarded: Winter 2020
  • Amount Won: $1000,00

Many people with mental health issues face significant challenges getting the help they need.  Psychological counseling or psychiatry services could be a luxury expense for people under financial stress. 5.1 million American adults, including 2.8 million with severe mental illness, did not receive services because they could not afford the cost of care (Lipari, 2018). Beyond structural barriers, fear of being stigmatized also prevents people from seeking help for mental health concerns (Lannin et al., 2013). 
To expand the access to mental health services and to counteract the problems of stigma, there has been a burgeoning growth in internet-based and mobile applications for mental health interventions. However, these mediated interventions are characterized by relatively poor adoption and adherence (Donkin et al, 2013). More recently, text-based conversational agents, or chatbots, have gained traction as the new generation of e-therapy. Powered by natural language processing technique, these agents can engage clients in a therapeutic process using natural language as inputs and outputs. This human-AI environment offers a “judgment-free zone” for those clients who are concerned about stigma. When invoking anthropomorphism, the conversational AI has great potential to provide emotional support in a rapid-response capability.
Literature related to psychotherapeutic chatbots is rather sparse in both psychology and HCI literature. Recent psychology scholarship began to evaluate the efficacy of using conversational agents for mental health interventions (Fitzpatrick et al., 2017; Park et al., 2019). While confirming that chatbots provide an affordable and effective method to deliver therapy, this line of research has not thoroughly explained the underlying mechanism of why chatbot might be more accepted and engaging than other types of e-therapy. Therefore, the first goal of the study is to examine the socio-technical relationship through the lens of Technology Acceptance frameworks to evaluate factors related to the adoption and use of conversational agents for psychotherapeutic purposes. Moreover, previous research has not evaluated the therapeutic relationship between humans and anthropomorphic technology. Following the APA  guideline that states effective psychotherapies that do not mention the therapeutic relationship are “seriously incomplete and potentially misleading on both clinical and empirical grounds”(Ackerman et al., 2001), this study unpacks the human-agent therapeutic relationship by evaluating anthropomorphism and its impacts on people’s perceptions and interactions with chatbot.


Daybreak User Study

  • Investigator: Kristine Rogers
  • Title: Daybreak User Study
  • Semester Awarded: Winter 2020
  • Amount Won: $1000

Many users have topics that they follow over time, whether for personal or professional reasons. The user has an ongoing interest in understanding what changes are happening in their overall topic area. This information retrieval task, which I will refer to as the “change detection” task, involves showing the user the latest developments within subtopics on their ongoing topic of interest. While systems exist to answer ad hoc questions, or provide general overviews of events that are happening in the world, few systems appear to focus on meeting the standing information needs of users—including experts—who follow a specific topic over time.

As part of my dissertation research, I ran a survey on users’ sort order preferences in social media to understand how they prefer to have feeds organized for change detection and other use cases. I am building upon this previous study to design and implement a prototype search system, known as DAYBREAK, based upon user feedback. For this next stage, I will perform an in-person user study focused on DAYBREAK, to determine the extent to which the user is able to complete change detection tasks successfully.

Leveraging Transactive Memory Systems In Data Science Collaborations

  • Investigator: Joohee Choi
  • Title: Leveraging Transactive Memory Systems In Data Science Collaborations
  • Semester Awarded: Winter 2020
  • Amount Won: $1095.00

Data Scientist has been one of the most in-demand jobs for the last 5 years. Data scientists often work in teams due to the complexity of the job, which requires many different skills and a substantial amount of work. Despite the prominence of the job and the ubiquity of teamwork in data science, little is known about what makes a data science team successful. Although teamwork is often important for data science, it is more demanding than other forms of teamwork. Data science often requires interdisciplinary skills, such as domain expertise, data management expertise, statistical expertise, and programming expertise. This interdisciplinarity means that expertise must be pooled from individuals with very different skills. There is often a high degree of uncertainty involved in data science work (e.g. data scientists don’t know the best way to analyze the data ahead of time, problems arise during data analysis). This uncertainty makes dividing up roles difficult. Data science is rarely routine work in which a pre-planned sequence of tasks is completed one after another. Instead, data science often involves iterative work, in which individuals redo tasks multiple times as they gain a deeper understanding of the research question(s) and data. Iterative work may create a high degree of interdependence between tasks, also making it difficult to divide up roles.

In this study, I propose studying how technology can help Data Science collaboration for teams with interdisciplinary members. In particular, I will study how the members develop Transactive Memory System (TMS), a cognitive mechanism through which a group of individuals encode, store, and retrieve information and knowledge by knowing what others know (Wegner, 1987). Developing TMS is especially important for teams whose members are from multiple backgrounds.

Ethical Sensitivity in Training Data Curation Among Machine Learning Engineers

  • Investigator: Karen Boyd
  • Title: Ethical Sensitivity in Training Data Curation Among Machine Learning Engineers
  • Semester Awarded: Fall 2019
  • Amount Won: $1000

As machine learning (ML) techniques have become sophisticated and pervasive, ethical concerns have followed. Recent headlines have declared “Amazon scraps secret AI recruiting tool that showed bias against women,” “Google Photos labeled black people 'gorillas,'” and “U.S. charges Facebook with racial discrimination in targeted housing ads” (Dastin, 2018; Guyunn, 2015; Rana & Paul, 2019). Alongside journalists, researchers have verified algorithmic discrimination in outcomes and accuracy on the basis of age (Diaz et al., 2018), gender (Bolukbasi et al., 2016, Dastin, 2018), race (Sweeney, 2013; Mehrotra et al., 2017; Angwin, 2016), and the intersection of gender and race (Noble, 2018; Boulamwini & Gebru, 2018) across product types, including (for the above examples) text processing, search engines, facial recognition, ad delivery, and criminal risk estimates.

Fairness isn’t the only ethical implication of ML: concerns about privacy and accountability have also been raised as well. Anonymized training datasets released publicly have been reidentified (Srivatsa & Hicks, 2012; Narayanan & Shmatikov, 2007; Malin & Sweeney, 2004) and researchers, the popular press, and the courts are discussing algorithmic accountability and due process in big data (Crawford & Schultz, 2014; Angwin, 2016b; Wisconsin v. Loomis, 2016).

In response to ethical concerns, researchers have designed, tested, and published technical and practice-based interventions throughout the ML development process. Conferences like ACM’s Fairness Accountability and Transparency (FAT*) and Artificial Intelligence, Ethics, and Society (AIES) focus on fairness, accountability, and other values across ML techniques.

Despite all of this attention, we don’t yet know how interventions designed to promote ethical AI will be adopted by those who curate data and use them to train ML models. Will they help ML engineers find and address ethical concerns in their work? This project seeks to understand ML engineers’ ethical sensitivity-- their propensity to notice, analyze, and act on socially impactful aspects of their work. It will study ethical sensitivity during training data curation and will describe the effects of documents as practice-based ethics interventions in this early stage of ML development. It asks how ML engineers perceive, particularize, and judge ethical questions while exploring new training data, how context documents can intervene in perception and particularization, and whether one can create a document that can help engineers move from particularization to judgment.

Fashion in Computer and Information Sciences: Lifecycles, Drivers, and Consequences

  • Investigator: Ping Wang
  • Title: Fashion in Computer and Information Sciences: Lifecycles, Drivers, and Consequences
  • Semester Awarded: Fall 2019
  • Amount Won: $75

Do scientists and their institutions follow the hottest topics to study, just as teenagers chase fads and fashions? If so, what happens to these scientists and their institutions? This research project examines some of the important aspects of the fashion phenomenon in science. A science fashion is a transitory collective belief that a scientific topic (e.g., theory, concept, or method) is at the forefront of rational scientific progress. In the context of computer and information sciences (CIS), this project aims to (1) identify the evidence for the existence of fashion in science, and (2) assess the consequences of fashion on fashion-following scientists and science institutions.

This project will demonstrate the existence of fashion in CIS sciences and its consequences on scientists' careers and science institutions' reputation. Further, the study has the potential to recommend strategies for both scientists and scientific institutions on taking advantage of fashion in developing successful careers and promoting societally beneficial scientific agenda respectively.

Milk Expression Research Lab (MERL): Proof of concept and feasibility of an investigation into claimed versus actual breast pump specifications and performance

  • Investigator: Fiona Jardine
  • Title: Milk Expression Research Lab (MERL): Proof of concept and feasibility of an investigation into claimed versus actual breast pump specifications and performance
  • Semester Awarded: Fall 2019
  • Amount Won: $1,077.03

Human milk (HM) provides optimal nutrition for infants and the perfect version of milk for the first years of life. However, a variety of barriers to breastfeeding exist and, while the overwhelming majority of parents initiate breastfeeding at birth, most do not breastfeed for as long as they initially desired, despite the negative health and emotional consequences associated with early breastfeeding cessation. Exclusively pumping or expressing human milk (EPing; also EP, EPer), usually with an electric breast pump, may provide a solution for some of these problems while still providing most of the benefits of HM.

Currently, no rigorous or independent testing of breast pumps occurs: there is no verification of the information provided by manufacturers. Breast pump users have few places to turn for information about pumps, with those places often dominated by social media influencer reviews or non-independent/ sponsored representatives.

This research is multi-staged, ultimately culminating in the establishment of the Milk Expression Research Lab (MERL), whose mission will be to research all aspects of milk expression. The first major project (the “main project”) will be to investigate claimed versus actual breast pump specifications and performance. Different breast pumps will be subjected to the same protocol of testing, with this data being compared to publicly available information.

A pilot study will be conducted to demonstrate that a “Lactation Simulation Model” (LSM) is an appropriate tool to use in the main study. An LSM is a functional silicone breast model that allows for liquid to be expressed out of the nipples either by hand or with a pump. It is the only such device in the marketplace and has the potential to be a consistent model of milk expression in ways that a human breast could never be. However, the LSM has never been tested for long-term pumping use nor for consistency in its performance over time; therefore, the goal of the pilot study is to investigate the stability and durability of this device. 

Planning and Capacity Building for the Next Generation of CASCIPlanning and Capacity Building for the Next Generation of CASCI

  • Investigator: Wayne Lutters
  • Title: RIG-IM: Planning and Capacity Building for the Next Generation of CASCI
  • Semester Awarded: Fall 2019
  • Amount Won: $4,250

The Center for the Advanced Study of Communities and Information (CASCI) is a core scholarly community-building organization within the College of Information Studies. CASCI exists to facilitate research and education that advances our understanding of the technology, information, and organization approaches needed to realize the potential of 21st-century communities to support learning, facilitate innovation, transform science and scholarship, promote economic development, and enhance individual and civic well-being.

CASCI has experienced steady, modest growth for the past few years, with seminar attendance necessitating a move to a larger capacity room this academic year. The number of new faculty who have joined the iSchool in the past two years with a sociotechnical research focus has significantly expanded interest in the center. CASCI also routinely attracts participation across the iSchool and around campus (Education, Public Policy, Communications, MITH, etc.). This proposal is the first step to realizing a programmatic expansion and reputation enhancement for CASCI to become a center-point for all things sociotech on campus, in the region, and the nation.

Funding would raise the profile of the CASCI event and community within the iSchool, UMD in general, and regionally as an important venue for sociotechnical research and community building. It would foster broader collaboration with partner institutions, bringing interesting new ideas.

Helping Students Recognize How Their Implicit Biases Affect Technology Designs

  • Investigator: Bill Kules
  • Title: Helping Students Recognize How Their Implicit Biases Affect Technology Designs
  • Semester Awarded: Summer 2019
  • Amount Won: $500

UX designers and developers who build user-facing systems have the power to shape the experiences of those who interact with their products. Without meaning to these creators can produce systems that reflect their own unconscious social biases.

To date, computer science educators have primarily focused on how to help students learn programming skills more successfully with course material that is more relevant to the interests of diverse students and by adopting more inclusive teaching practices (Alvarado, Dodds & Libeskind-Hadas, 2012).

This research explores how education on recognizing and overcoming implicit bias taught alongside technical and design training could help students understand and care about the impact of the technology they create. To accomplish this, the researcher will attempt to help the students he'll interview address the way their own biases are reflected in their work. There is a developing body of scholarship about biases and their effect on technology design, including algorithmic bias (Hajian, Bonchi & Castillo, 2016), search engine bias (Otterbacher, Bates & Clough, 2017), robots (Bartneck, et al., 2018), as well as the impact on end-users (Lopez, et al., 2019). The focus on the classroom puts an emphasis on integrating ethics into the teaching of technology design and development.


Assessing the Value of an Online Repository of Local Resources for People Who Have Chronic Health Conditions

  • Investigator: Gagan Jindal
  • Title: Assessing the Value of an Online Repository of Local Resources for People Who Have Chronic Health Conditions
  • Semester Awarded: Spring 2019
  • Amount Won: $2,950

Drawing on an exploratory study involving 15 semi-structured in-depth interviews with individuals who have chronic health conditions, this study investigates their experiences searching for information on local resources to manage their health more effectively. The findings revealed important benefits and challenges of the various strategies these individuals use to find local resources, which include word of mouth communication through informal social networks, online exploratory searches, and social media use. This study also assesses the potential uptake, design, and implementation of an online health information system that would allow these individuals to crowdsource information on local resources in their communities.


New Ways to Fic: How Kpop Fans Are Using Social Media

  • Investigator: Shandra Morehouse
  • Title: New Ways to Fic: How Kpop Fans Are Using Social Media
  • Semester Awarded: Spring 2019
  • Amount Won: $212.60

This study focuses on K-pop fanfiction writers and how social media plays a role in their fan experience. Fanfiction writers are known for adopting new technologies and utilizing them to meet their needs (Versaphile). In the K-pop (Korean pop music) fandom, fanfiction authors have found innovative ways to use social media to enhance their storytelling.

This study describes a need for improved understanding of K-pop fanfiction published via social media platforms, to inform efforts to preserve K-pop fanfiction and social media in general. Most literature on fanfiction and social media has focused on other roles for social media: not as a platform for publishing fiction, but as a communication channel for the community more broadly. This study seeks to advance the understanding of fanfiction publishing.


Personal Tracking in Groups: Exploring Tracking Behavior in Sports Teams

  • Investigator: Pramod Chundury
  • Title: Personal Tracking in Groups: Exploring Tracking Behavior in Sports Teams
  • Semester Awarded: Spring 2019
  • Amount Won: $1,080

Personal informatics (PI) tools are predominantly tailored to an individual’s needs. However, PI has been shown to be socially motivated, embedded in interpersonal contexts, and oftentimes collaboratively conducted. In team sports, athletes have to grapple with their own goals while simultaneously managing team goals and expectations.

This study aims to further explore the potential opportunities in understanding self-tracking in a team sports context. The findings of this study will help the researcher map out the design space surrounding the various goals, needs, group dynamics and choice of tools that influence self-managing of an athlete’s sports performance.


Designing a Crowdsourced Repository of Local Resources for Individuals who have Chronic Health Conditions

  • Investigator: Gagan Jindal
  • Title: Designing a Crowdsourced Repository of Local Resources for Individuals who have Chronic Health Conditions
  • Semester Awarded: Spring 2019
  • Amount Won: $1,000

Self-management support is a critical component of effective chronic illness care. Individuals who have chronic health conditions often require intensive support to make sustainable long-term lifestyle changes to improve and maintain their health. While there is strong existing literature on the lifestyle and health decisions of the chronically ill, their information needs are understudied.

This study aims to address the problem of improving technologies so that patients with chronic disease have access to tools and resources to manage their health conditions. Conducting co-design sessions with the chronically ill is an important step toward designing a health information system. The development and testing of a crowdsourced system are important in meeting the needs of this community. This study aims to fill this gap by exploring both the resources and the presentation mode that will best benefit people living with chronic illness.



Understanding the Effect of Media in Dementia Attitudes

Understanding the Effect of Media in Dementia Attitudes
  •   Investigator: Himanshi Manglunia & Shruti Hegde
  • Title: Understanding the Effect of Media in Dementia Attitudes
  • Semester Awarded: Spring 2019
  • Amount Won: $1,000

Attitudes towards dementia have concrete impacts on the ability of people with dementia to maintain and create social connections with others, to engage in meaningful activity, and to receive appropriate and respectful care. The researchers seek to assess whether exposure to first-hand accounts of dementia affects college students’ attitudes towards and understanding of dementia when compared to news articles that people might typically encounter. This proposal aims to explore the potential effect of media on shaping people’s attributes towards those with dementia.


Infrastructure (or the lack thereof) for collective design: The case of community access to high-speed Internet in the city of Baltimore

  • Investigator: Joel Chan
  • Title: Infrastructure (or the lack thereof) for collective design: The case of community access to high-speed Internet in the city of Baltimore
  • Semester Awarded: Fall 2018
  • Amount Won: $900

Foundational research by Vanessa Frias-Martinez and Gerrit Knaap has revealed that in Baltimore, many residents live in neighborhoods that lack “Last Mile” connections to the Internet cable infrastructure, and consequently lack reliable access to high-speed Internet. This project intends to study how residents in Baltimore attempt to devise ways to gain access to reliable high-speed Internet. Chan hypothesizes that what is needed is a way for stakeholders to collectively design a solution that takes full advantage of all of the knowledge and resources that are distributed across groups: for example, technical experts know what is possible/expensive tech-wise, policymakers can pull the right strings, and community members know what’s possible to maintain. Nobody knows everything, everyone knows something, and if they don’t design together, they fail.


Electronic Health Record Implementation Findings at a Large, Suburban Health and Human Services Department

  • Investigator: Kenyon Crowley
  • Title: Electronic Health Record Implementation Findings at a Large, Suburban Health and Human Services Department
  • Semester Awarded: Fall 2018
  • Amount Won: $2,200

While most hospitals and outpatient clinics have made the transition to electronic health records (EHRs), this is not the case for public health departments. Public health departments, which are charged with promoting health and preventing illness for all people with relatively small budgets per capita, are actively seeking (and struggling) to adopt EHRs while faced with a variety of information management and technology adoption challenges. There is a dearth of empirical guidance from real-world studies of public health EHR adoption. Our article presents the first longitudinal analyses of an electronic health record (EHR) implementation across a large public health department and illuminates recommendations to improve the EHR adoption process.


Datafication of original records at the National Archives to expand the Global Journeys; Local Communities project’s records dataset

  • Investigator: Ken Heger
  • Title: Datafication of original records at the National Archives to expand the Global Journeys; Local Communities project’s records dataset
  • Semester Awarded: Fall 2018
  • Amount Won: $1,000

The Global Journeys; Local Communities Project identifies, digitizes, data files and indexes records documenting American citizens and their families who emigrated from the United States to live permanently abroad. It allows scholars to study migration of people, local communities overseas, and construct micro-biographies. The project is scoped to concentrate on the period 1865 – 1914 (from the Civil War to the First World War). The primary records the Project targets underwent three major filing scheme changes: 1865-1880; 1881-Mid-1907; Mid-1907-1914. Each period presents its own unique challenges; the second piece is complete and available for research; this proposal is to support expanding the dataset backward to the end of the American Civil War.


Balancing Personal and Public Regions on Social Media: Exploring What WeChat Moments Tells Us About Temporality

  • Investigator: Xiaoyun Huang
  • Title: Balancing Personal and Public Regions on Social Media: Exploring What WeChat Moments Tells Us About Temporality
  • Semester Awarded: Fall 2018
  • Amount Won: $954.75

In most systems, the digital footprints people leave behind are archived by default, whether it’s a message sent in Facebook’s Messenger app or every edit made on a Google Doc. Automatic archiving supports collaboration, provides backup or evidence when needed, helps people reminisce, and supports reflection. However, archiving also creates challenges for self-presentation on social media platforms, where long-forgotten posts can be resurfaced in unexpected ways that conflict with the user’s current self. Some social media platforms afford ephemerality rather than the more common persistence of content. Snapchat, for example, uses automatic deletion; however, many people think there is archival value in the posts they have produced. WeChat Moments, a social media platform popular among Chinese users, provides an interesting case study to examine this perspective.


Contributing to the review of research in education

  • Investigator: Philip Piety
  • Title: Contributing to the review of research in education
  • Semester Awarded: Fall 2018
  • Amount Won: $1,350

A prestigious, invited literature review paper is in progress, but the author and reviewers think it would be an even stronger paper with some more research into relevant literature. The goal of this chapter is to look across three related areas known as data-driven decision-making (DDDM), learning analytics (LA), and educational data mining (EDM) to understand how they relate in their varied impact on the work done in educational organizations from teaching to administrative and leadership work.


Designing Technology to Increase Adoption of Healthy Behaviors in Men in the Context of Light Food Consumption

  • Investigator: Diva Smriti
  • Title: Designing Technology to Increase Adoption of Healthy Behaviors in Men in the Context of Light Food Consumption
  • Semester Awarded: Fall 2018
  • Amount Won: $600

The general problem of rising obesity is widely understood as a health threat. Men participate in more risky behaviors which are deemed masculine, and are hesitant to adopt healthy behaviors which are deemed feminine. This stereotype has translated into technology as well as women being the majority of users. Thus, there is a need for self-monitoring applications and technologies to be more gender suited and designed according to what motivates each gender. This research aims to reduce this gender gap and help men in adopting healthy behaviors in the context of light food consumption (fiber, fat, fruit).


David and Goliath: Combining Smartwatches and Large Displays

  • Investigator: Niklas Elmqvist
  • Title: David and Goliath: Combining Smartwatches and Large Displays
  • Semester Awarded: Spring 2018
  • Amount Won: $545

Niklas Elmqvist explores the combination of smartwatches and a large interactive display, such as a touchscreen, to support visual data analysis. These two extremes of interactive surfaces are increasingly popular, but feature different characteristics—display and input modalities, personal/public use, performance, and portability. The touchscreen serves as the primary display that provides visualizations of a dataset, while the smartwatch can act as a user-specific storage for points of interests and parameter settings, as a mediator altering system reactions, or as a remote control.


Breastfeeding without nursing: The information behavior of those who exclusively pump human milk

  • Investigator: Fiona Jardine
  • Title: Breastfeeding without nursing: The information behavior of those who exclusively pump human milk
  • Semester Awarded: Spring 2018
  • Amount Won: $975

Human milk (HM) is regarded as optimal nutrition for infants and the perfect version of milk for the first years of life. However, there are barriers to providing HM by breastfeeding. Exclusively pumping (EP) may be the solution. Fiona Jardine uses online surveys to collect qualitative and quantitative data from exclusive pumpers (EPers). Jardine’s dissertation focuses on EPers’ information behavior surrounding feeding their child milk (HM and formula): their information needs, how they seek this information, where they ultimately find it, how useful that information is, whether and how they use it, and the effect of this information (or lack thereof).


PING: Examining Older Adults’ Response to Home-based, Voice-Controlled Reminders Through Proximity Sensing

  • Investigator: Yuhan Luo
  • Title: PING: Examining Older Adults’ Response to Home-based, Voice-Controlled Reminders Through Proximity Sensing
  • Semester Awarded: Spring 2018
  • Amount Won: $1,085.76

Older adults, who usually have home-bounded lifestyles, can use reminders on intelligent personal assistants (IPAs) such as Amazon Echo and Google Home for medication, exercise, shopping, and housekeeping. Yuhan Luo and her team aim to examine older adults’ response and acceptability to home-based, voice-controlled reminders compared to traditional digital reminders sent from mobile phones. They designed and developed two versions of PING (the name of their reminder system): one version built in Alexa skill and the other version built in Android app.


Replication Study of the Single Item Narcissism Scale

  • Investigator: Jennifer Golbeck
  • Title: Replication Study of the Single Item Narcissism Scale
  • Semester Awarded: Winter 2018
  • Amount Won: $1,000

Much of behavioral psychology is centered around standard psychological surveys, which are immensely helpful. In 2014, researchers released a Single Item Narcissism Scale (SINS), a 1-question “survey” that could measure narcissism as accurately as the more common 16- and 41-question surveys. Despite the excellent work and multiple studies by the initial researchers, the SINS has not been validated by outside researchers. Dr. Golbeck recruited a team of student volunteers to conduct a replication study of SINS, and hopes to continue this research.


Promoting Data Science for Accessibility with Publicly Available Datasets

  • Investigators: Mayanka Jha & Riya Chanduka
  • Title: Promoting Data Science for Accessibility with Publicly Available Datasets
  • Semester Awarded: Winter 2018
  • Amount Won: $1,000

With the explosion of machine learning and artificial intelligence (AI), several assistive technologies have emerged in the recent few years that enhance life experiences for people with disabilities. Much of the recent progress in these solutions is due to the availability of large collections of data (datasets). Because of the high costs of collecting and annotating datasets, researchers often make their resources publicly available. Public datasets attract, nurture, and challenge data scientists to work on specific problems, e.g., by creating problem-specific data science competitions. However, this approach has seen limited use in the field of accessibility. The project aims to promote data science for accessibility by increasing awareness on challenges of accessing datasets from users with disabilities and creating a repository with currently available resources.


Exploring the Use of Intelligent Personal Assistants by Older Adults

  • Investigator: Alisha Pradhan
  • Title: Exploring the Use of Intelligent Personal Assistants by Older Adults
  • Semester Awarded: Winter 2018
  • Amount Won: $970

Voice-controlled intelligent personal assistants (IPAs), such as Amazon Echo and Google Home, have introduced a new interaction paradigm into the mainstream. These devices provide a conversational interface in the home to allow users to ask for and save information (e.g., check weather, add to a shopping list), control smart home appliances, and perform a range of online actions (e.g., shopping, banking). The voice-based interaction provided by this technology has the potential to provide independence and autonomy for older adults who have limited experience of using digital technology. However, there is no research studying how older adults are using or want to use these devices.


StreamBED VR

  • Investigator: Alina Striner
  • Title: StreamBED VR
  • Semester Awarded: Winter 2018
  • Amount Won: $595

Citizen science monitoring of local watersheds is crucial for water conservation and activism. Both quantitative and qualitative metrics are used to evaluate stream habitats, however water biologists suggest that qualitative assessment tasks are too nuanced for citizen scientists to learn because they rely on background knowledge and past stream experiences. Citizen scientists have the potential to contribute to impactful scientific research, but because of poor training, often waste resources. This project explores whether multisensory information paired with virtual training can lead to learning and positive training of qualitative assessment skills. Effective training has the potential to improve citizen science data quality, decrease cost, and motivate citizen scientists to regularly participate in data collection.



  • Investigators: Mega Subramaniam & Kelly Hoffman
  • Title: ConnectedLib Open Access Publication
  • Semester Awarded: Winter 2018
  • Amount Won: $2,500

The article, titled “Using Technology to Support Equity and Inclusion in Youth Library Programming: Current Practices and Future Opportunities,” describes the findings of the first year of the three-year IMLS-funded ConnectedLib project. The goal of the project is to develop a suite of continuing education modules for public youth librarians interested in using connected learning principles to help youth develop 21st century skills. The ConnectedLib team hopes this article is as open and accessible as the project that generated it. Allowing this article to be open access increases awareness of the ConnectedLib project and resources, resulting in increased use and recognition by the library community. In addition, the findings reported in the article contribute to providing more equitable opportunities for non-dominant youth through public libraries.


Facilitating Health Information Disclosure Online through Privacy Protection

  • Investigator: Yuting Liao
  • Title: Facilitating Health Information Disclosure Online through Privacy Protection
  • Semester Awarded: Fall 2017
  • Amount Won: $960

Patient openness to sharing data is critical for the success of big data in healthcare. However, there is a tension between privacy and disclosure. Sharing one's health information online can be a rewarding yet risky behavior. The goals of the project are twofold: 1) to understand people's mental model regarding health-related privacy online and to evaluate its relationship with trust and disclosure management, and 2) to identify design solutions for privacy protection that will facilitate online health information disclosure, featuring a visual tool to ensure consent process.


Towards Identifying Values and Tensions in Designing a Historically-Sensitive Data Platform: A Case of Urban Renewal Documents

  • Investigators: Myeong Lee, Shiyun Chen & Yuheng Zhang
  • Title: Towards Identifying Values and Tensions in Designing a Historically-Sensitive Data Platform: A Case of Urban Renewal Documents
  • Semester Awarded: Fall 2017
  • Amount Won: $1,000

The urban renewal project was a national effort in the 1960s and 1970s to transform “blighted” neighborhoods into living spaces such as public housing and modern amenities with an emphasis on economic values. Families, businesses, and organizations of these neighborhoods, most of which were minority communities, were displaced. A large, high-quality, but unseen collection of urban renewal documents was found in a library archive of North Carolina and explored as a case study in an archival data platform project in 2009. This research project was re-initiated as part of a digital curation effort to make the historical documents easily searchable and navigational in favor of interactive user interfaces and relational databases.


Crowdsourcing community resources to help individuals manage chronic health conditions

  • Investigators: Gagan Jindal & Beth St. Jean
  • Title: Crowdsourcing community resources to help individuals manage chronic health conditions
  • Semester Awarded: Fall 2017
  • Amount Won: $700

Individuals with chronic health conditions often do not translate knowledge of appropriate health behaviors to manage their condition into active lifestyle changes. Community asset linkage has been one solution to help individuals locate resources in their communities that can help manage chronic health conditions. However, this linkage can be undeveloped, limited, or closed off. Crowdsourcing may be a solution to have an open-source, communal platform for people with chronic diseases to access information.


Engaging Middle School Students in a Drawing Activity to Elicit Their Mental Models of Google

  • Investigator: Beth St. Jean
  • Title: "There's a creepy guy on the other end at Google!": Engaging middle school students in a drawing activity to elicit their mental models of Google
  • Semester Awarded: Spring 2017
  • Amount Won: $3,000

Although youth are increasingly going online to fulfill their needs for information, many youth struggle with information and digital literacy skills, such as the abilities to conduct a search and assess the credibility of online information. In order to investigate youths’ conceptions of the Google search engine, a drawing activity was conducted with 26 HackHealth after-school program participants to elicit their mental models of Google. Overall, their drawings suggest a limited understanding of Google and the ways in which it actually works. However, an understanding of youth's’ conceptions of Google can enable educators to better tailor their digital literacy instruction efforts and can inform search engine developers and search engine interface designers in making the inner workings of the engine more transparent and their output more trustworthy to young users. With a better understanding of how Google works, young users will be better able to construct effective queries, assess search results, and ultimately find relevant and trustworthy information that will be of use to them.


Amplifying the International Research Network

  • Investigator: Ricardo Punzalan
  • Title: Amplifying the International Research Network for Assessing the Value and Impact of Digitized Ethnographic Archives
  • Semester Awarded: Spring 2017
  • Amount Won: $9,800

Dr. Punzalan has been actively pursuing research that to help libraries, archives, and museums better document and assess the impact of access to their digitized ethnographic archives. His sustained interaction with scholars, archivists, and members of Indigenous communities has generated interest in creating a network and mechanism for exchange of ideas and sharing of resources. This project aims to create a workshop with the following outcomes: creation of international network of scholars and archivists pursuing ethnographic impact research, identification and planning of collaborative research projects and funding opportunities, and a website that identifies collaborative projects, project participants, and resource sharing.


Participant Perspectives on Their Membership

  • Investigator: Brenna McNally
  • Title: Participant Perspectives on their Membership in an Intergenerational Participatory Design Team
  • Semester Awarded: Spring 2017
  • Amount Won: $516

Participatory Design (PD) gives users a voice in the design of technologies they are meant to use by including users in the technology design process. PD methods have been adapted for research with children to facilitate the creation of technologies that better meet children’s desires and expectations. While the benefits HCI practitioners receive from working with children in PD can include developing more child-centric interfaces, spending less time on testing after a technology is developed, and finding surprising new innovations, research is less clear on the participants’ perceptions of their involvement on PD teams—specifically, what do they gain from their participation?


Studying User Perceptions and Experiences with Algorithms
  Studying User Perceptions and Experiences with Algorithms

  • Investigator: Nicholas Proferes
  • Title: Studying User Perceptions and Experiences with Algorithms ICWSM Half-Day Workshop Proposal
  • Semester Awarded: Spring 2017
  • Amount Won: $2,240

From Facebook’s News Feed algorithm that shapes the posts and updates we see, to Spotify’s recommendation service that introduces us to new music that we might love, to dating site algorithms that attempt to match us with potential romantic partners, algorithms play an increasingly important role in shaping many aspects of our daily lives. We seek to bring together a community of researchers interested in taking a human-centered perspective on studying the experience of algorithms. This workshop sought to bring together a community of researchers interested in taking a human-centered perspective on studying the experience of algorithms.


Performing Play

  • Investigator: Anthony Pellicone
  • Title: Performing Play: Cultural Production on
  • Semester Awarded: Winter 2017
  • Amount Won: $460

Every day, millions of people log on to the website and watch others play games, a practice known as streaming. Briefly, a stream features live gameplay overlaid with a camera to capture the performer’s reactions, and a chat channel for the audience, facilitating social interaction relating to the stream’s content. Therefore, in streaming, participants are drawing together technological, social, and cultural competencies in order to produce a singular, cohesive experience. This work recognizes the complexity of this task, and conceptualizes streaming with a new theoretical construct: performing play.


Ethics Regulation in Social Computing Research

  • Investigator: Jessica Vitak
  • Title: Ethics Regulation in Social Computing Research: Examining the Role of Institutional Review Boards
  • Semester Awarded: Fall 2016
  • Amount Won: $1,300

The parallel rise of pervasive data collection platforms and computational methods for collecting, analyzing and drawing inferences from large quantities of user data has led to new insights into patterns of behavior by individuals, groups, and societies. At the same time, the methods employed to access these data have raised new questions about ethical research practices in this new technological milieu. This paper provides insights into the attitudes and practices of institutional review boards (IRBs)—i.e., the organizations that review and monitor human subjects research at U.S. universities—regarding their assessment of social computing research.


Advancing the Science of Citizen Science
  Advancing the Science of Citizen Science

  • Investigator: Andrea Wiggins
  • Title: Advancing the Science of Citizen Science
  • Semester Awarded: Fall 2016
  • Amount Won: $2,750

Citizen science is a form of collaboration that engages non-professionals as contributors to scientific research, typically through the processes of gathering, transforming or analyzing data. To date, research has documented examples of hugely successful citizen science projects, such as Zooniverse and eBird, but citizen science also includes hundreds of smaller projects and functionally similar digital humanities projects, operating from small-scale web platforms and in-person collaboration teams. The goal of this workshop was to to (i) bring together researchers studying citizen science to form a coherent map summarizing the theories, methodologies, and platforms that currently defines citizen science research, (ii) brainstorm a list of fundamental open questions and ways to tackle them, and (iii) form a multidisciplinary community to build synergies for further collaboration.


Outreach and Promotion for The Tessera

  • Investigator: Kari Kraus
  • Title: Outreach and Promotion for The Tessera: An Educational Alternate Reality Game
  • Semester Awarded: Fall 2016
  • Amount Won: $3,592.21

The Tessera ( is an educational Alternate Reality Game for teens aimed at advancing computational thinking and computer history awareness. The game is an interactive mystery in which players engage with the history of computing by interacting with famous persona-- including Ada Lovelace, Charles Babbage, Alan Turing, and Grace Hopper-- who influenced the development and growth of information technologies. A joint production between Brigham Young University, the University of Maryland, Tinder Transmedia, and the Computer History Museum in Mountain View California, the game is funded by the NSF’s Advancing Informal STEM Learning program.


Overseas Pension Project

  • Investigator: Ken Heger
  • Title: Overseas Pension Project
  • Semester Awarded: Spring 2016
  • Amount Won: $4,000

The Overseas Pension Project is a team of archivists, historians, genealogists, and information managers with a common mission: exploring data trapped within 200 year old archival documents. The team finds, digitizes, and links records documenting veterans and their family members receiving pensions for American military service who moved outside the United States. It concentrates on military service from the Revolutionary War until just prior to World War I. The project aims to release the rich genealogical and historical data contained within these digitized records for groups such as genealogists, historians, economists, sociologists, and healthcare professionals to use.