Andrea Wiggins – Assistant Professor

Featured Faculty: Andrea Wiggins – Assistant Professor

wiggins_andreaAndrea Wiggins is an Assistant Professor at Maryland’s iSchool and director of the Open Knowledge Lab at UMD. She received her PhD in Information Science & Technology from the Syracuse University School of Information Studies and was a postdoctoral fellow with DataONE, hosted by the Cornell Lab of Ornithology.

Can you tell us about your research?

Citizen science refers to research produced through collaborations between professionals and non-professionals, and it’s sometimes considered a type of crowdsourcing. Although it’s not really a new phenomenon, it has recently exploded in popularity because the Internet has revolutionized the ways that members of the public at large can participate in science.

I study how the design of projects themselves as well as their supporting technologies impacts engagement and knowledge production. For example, how do different processes for validating data impact the project outcomes? How does the design of participant experiences impact project sustainability? What tools and content support learning, and does that translate to better data and science outcomes? One way to describe this work is “research in service to practice” because our findings focus on pain points for practitioners, so our findings directly impact the way citizen science is being done almost immediately, which is incredibly rewarding.

What kind of students work on your projects?

We work with mixed methods to understand the design, experiences, and outcomes of citizen science, because it’s a rich and multi-faceted phenomenon to study. For example, in a recent paper, we used ethnographic methods and participant observation to direct our statistical analyses of collaborative data validation. More generally, we leverage interviews, fieldwork, and occasionally surveys to inform and explain our observations of in situ behavior, both in the field and online. So we’re happy to work with students who have skills or interests in statistics, content analysis, and field-based data collection. Anyone intrigued by citizen science is welcome to contact me by email to talk about opportunities for involvement.

What is one thing you love about the Human-Computer Interaction Lab?

I really enjoy the warmth of the community and the traditions that support constructive opportunities for students to level up on their research and science communication skills.

Yla Tausczik – Assistant Professor

Featured Faculty: Yla Tausczik – Assistant Professor

ylaYla Tausczik is an Assistant Professor in the iSchool at University of Maryland, College Park (UMD) in the area of Social Computing. She received her Ph.D from the University of Texas at Austin in Social and Personality Psychology and was also a postdoctoral fellow at the Carnegie Mellon Human Computer Interaction Institute.


We have only begun to explore the new forms of communication and collaboration which modern technology allows. Crowdsourcing directs large numbers of people toward solving a common problem. Using a variety of methods— e.g.,competitions, Q & A, forums —companies have created platforms to support crowd-based problem solving from mathematics to medicine, data science and R&D.

My students and I study a range of questions regarding crowd-based problem solving: Do crowds solve problems differently from small groups? In what ways do they perform better, or worse? How can we structure group communication to best coordinate a variety of efforts and expertise? This research advances our basic understanding of how people work together and can be applied to improve technological support for open science and open data.


Our work on crowd-based problem solving draws from both data science and social science, preparing our students with a strong toolkit of formal methods, from observation to experimentation. Online crowd-sourcing platforms provide rich archives of data on real-life problems; unlocking that data requires the use of tools like natural language processing, data mining and machine learning. On the other hand, lab and field experiments allow us to actively test alternative designs and potential interventions; finding meaningful results requires careful experimental design and statistical analysis.

I am happy to talk with any student who wants to become more involved in research. The best way to contact me is by email or during office hours.


The HCIL has great talks, which attract lively speakers, interesting research, and an engaged and inquisitive audience. In other words, it is a great intellectual atmosphere.