College during COVID

Mental health of UW students during Spring 2020 varied tremendously: the challenges of online learning during the pandemic were entwined with social isolation, family demands and socioeconomic pressures. In this context, individual differences in coping mechanisms had a big impact. The findings of this paper underline the need for interventions oriented towards problem-focused coping and suggest opportunities for peer role modeling.

College from home during COVID-19: A mixed-methods study of heterogeneous experiences. Morris ME, Kuehn KS, Brown J, Nurius PS, Zhang H, Sefidgar YS, Xuhai X, Riskin EA, Dey A, Consolvo S, Mankoff JC. (2021) PLoS ONE 16(6): e0251580. (reported in UW News and the Hechtinger Report)

A lineplot showing anxiousness (Y axis, varying from 0 to 4) over time (X axis). Each student in the study is plotted as a different line over each day of the quarter. The plot overall looks very messy, but two things are clear; Every student has a very different trajectory from every other, with all of them going up and down multiple times. And the average, overall, shown is a fit line, is fairly low and slightly increasing (from about .75 to just under 1).
Heterogeneity in individuals’ levels of anxiety (reported in ESM). Individual trajectories of anxiety are shown in different line types and colors (dotted versus solid lines represent different participants). Although the mean level of anxiety is 1 on a scale of 0–4, the significant variation in responses invites examination of individuals and subgroups.

This mixed-method study examined the experiences of college students during the COVID-19 pandemic through surveys, experience sampling data collected over two academic quarters (Spring 2019 n1 = 253; Spring 2020 n2 = 147), and semi-structured interviews with 27 undergraduate students. 

There were no marked changes in mean levels of depressive symptoms, anxiety, stress, or loneliness between 2019 and 2020, or over the course of the Spring 2020 term. Students in both the 2019 and 2020 cohort who indicated psychosocial vulnerability at the initial assessment showed worse psychosocial functioning throughout the entire Spring term relative to other students. However, rates of distress increased faster in 2020 than in 2019 for these individuals. Across individuals, homogeneity of variance tests and multi-level models revealed significant heterogeneity, suggesting the need to examine not just means but the variations in individuals’ experiences. 

Thematic analysis of interviews characterizes these varied experiences, describing the contexts for students’ challenges and strategies. This analysis highlights the interweaving of psychosocial and academic distress: Challenges such as isolation from peers, lack of interactivity with instructors, and difficulty adjusting to family needs had both an emotional and academic toll. Strategies for adjusting to this new context included initiating remote study and hangout sessions with peers, as well as self-learning. In these and other strategies, students used technologies in different ways and for different purposes than they had previously. Supporting qualitative insight about adaptive responses were quantitative findings that students who used more problem-focused forms of coping reported fewer mental health symptoms over the course of the pandemic, even though they perceived their stress as more severe. 

Example quotes:

I like to build things and stuff like that. I like to see it in person and feel it. So the fact that everything was online…. I’m just basically reading all the time. I just couldn’t learn that way

Insomnia has been pretty hard for me . . .  I would spend a lot of time lying in bed not doing anything when I had a lot of homework to do the next day. So then I would become stressed about whether I’ll be able to finish that homework or not.”

“It was challenging … being independent and then being pushed back home. It’s a huge change because now you have more rules again”

For a few of my classes I feel like actually [I] was self-learning because sometimes it’s hard to sit through hours of lectures and watch it.”

I would initiate… we have a study group chat and every day I would be like ‘Hey I’m going to be on at this time starting at this time.’ So then I gave them time to all have the room open for Zoom and stuff. Okay and then any time after that they can join and then said I [would] wait like maybe 30 minutes or even an hour…. And then people join and then we work maybe … till midnight, a little bit past midnight

Megan Hofmann

Megan is a Phd Student at the Human Computer Interaction Institute at Carnegie Mellon Unviversity. She is advised by Prof. Jennifer Mankoff of the University of Washington and and Prof. Scott E. Hudson. She completed her bachelors in Computer Science at Colorado State University in 2017. She is an NSF Fellow, and a Center for Machine Learning and Health Fellow. During her Undergraduate degree Megan’s research was adviced by Dr. Jaime Ruiz and Prof. Amy Hurst.

Her research focuses on creating computer aided design and fabrication tools that expand the digital fabrication process with new materials. She uses participatory observation and participatory design methods to study assistive technology and digital fabrication among many stakeholder (people with disabilities, caregivers, and clinicians).

Visit Megan’s homepage at https://www.megan-hofmann.com/publications/.

Research

Some recent projects (see more)

Medical Making During COVID

The onset of COVID-19 led many makers to dive deeply into the potential applications of their work to help with the pandemic. Our group’s efforts on this front, all of which were collaborations with a variety of people from multiple universities, led me to this reflective talk about the additional work that is needed for us to take the next step towards democratizing fabrication.

https://www.youtube.com/watch?v=xfz7JDSyWXI&ab_channel=stanfordonline

This talk is based on a series of papers studying and working with people who make, including the following recent COVID-related papers:

Natasha Sidik

Natasha Ann Sidik is a Senior at the University of Washington majoring in Psychology with a Minor in Informatics. As an advocate for inclusivity, she centers most of her work on learning, normalizing, and sharing best practices around accessibility. 
Growing up in Indonesia and the US as a non-traditional student gave her many perspectives and allowed her to network with diverse groups of people. Under the make4all Lab, Natasha is currently working on research to help improve the experiences of students with disabilities at the University of Washington. Find more of her work at https://sidiknatasha.github.io/portfolio/.

Navigating Illness, Finding Place

Sylvia JanickiMatt Ziegler, Jennifer Mankoff:
Navigating Illness, Finding Place: Enhancing the Experience of Place for People Living with Chronic Illness. COMPASS 2021: 173-187

When chronic illness, such as Lyme disease, is viewed through a disability lens, equitable access to public spaces becomes an important area for consideration. Yet chronic illness is often viewed solely through an individualistic, medical model lens. We contribute to this field of study in four consecutive steps using Lyme disease as a case study: (1) we highlight urban design and planning literature to make the case for its relevance to chronic illness; (2) we explore the place-related impacts of living with chronic illness through an analysis of interviews with fourteen individuals living with Lyme disease; (3) we derive a set of design guidelines from our literature review and interviews that serve to support populations living with chronic illness; and (4) we present an interactive mapping prototype that applies our design guidelines to support individuals living with chronic illness in experiencing and navigating public and outdoor spaces.

https://youtu.be/mo8ZIeDXyGE?t=1297
(Left) Users can select accessibility qualities to filter the places shown on the map. (Right) Clicking on a place opens a popup window to see all of that place's coded accessibility qualities, pictures, reviews, and additional textual descriptions.

BLV Understanding of Visual Semantics


Venkatesh Potluri
Tadashi E. GrindelandJon E. Froehlich, Jennifer Mankoff: Examining Visual Semantic Understanding in Blind and Low-Vision Technology Users. CHI 2021: 35:1-35:14

Visual semantics provide spatial information like size, shape, and position, which are necessary to understand and efficiently use interfaces and documents. Yet little is known about whether blind and low-vision (BLV) technology users want to interact with visual affordances, and, if so, for which task scenarios. In this work, through semi-structured and task-based interviews, we explore preferences, interest levels, and use of visual semantics among BLV technology users across two device platforms (smartphones and laptops), and information seeking and interactions common in apps and web browsing. Findings show that participants could benefit from access to visual semantics for collaboration, navigation, and design. To learn this information, our participants used trial and error, sighted assistance, and features in existing screen reading technology like touch exploration. Finally, we found that missing information and inconsistent screen reader representations of user interfaces hinder learning. We discuss potential applications and future work to equip BLV users with necessary information to engage with visual semantics.

Interaction via Wireless Earbuds

Xuhai XuHaitian ShiXin YiWenjia LiuYukang YanYuanchun ShiAlex Mariakakis, Jennifer Mankoff, Anind K. Dey:
EarBuddy: Enabling On-Face Interaction via Wireless Earbuds. CHI 2020: 1-14

Past research regarding on-body interaction typically requires custom sensors, limiting their scalability and generalizability. We propose EarBuddy, a real-time system that leverages the microphone in commercial wireless earbuds to detect tapping and sliding gestures near the face and ears. We develop a design space to generate 27 valid gestures and conducted a user study (N=16) to select the eight gestures that were optimal for both human preference and microphone detectability. We collected a dataset on those eight gestures (N=20) and trained deep learning models for gesture detection and classification. Our optimized classifier achieved an accuracy of 95.3%. Finally, we conducted a user study (N=12) to evaluate EarBuddy’s usability. Our results show that EarBuddy can facilitate novel interaction and that users feel very positively about the system. EarBuddy provides a new eyes-free, socially acceptable input method that is compatible with commercial wireless earbuds and has the potential for scalability and generalizability

Yuna Liu

Yuna Liu is a second-year undergraduate majoring in Mathematics and Applied Mathematics. She is interested in simulation and mathematical modelling, and hopes to go to graduate school to study related fields. Yuna is currently on a UW EXP project that focuses on systematic review about the generalizability of passive sensing for health & well-being.

Brian Lee

My name is Brian Lee and I am a Junior at the University of Washington studying computer science.
I am passionate about human computer interaction and accessibility in technology, and I am learning to build applications that can have an impact on everyone, not just a select few.
Currently, I am working with Kelly on the Sensing project, building a Samsung SmartWatch and Android phone app to allow people with chronic illnesses to tag and track sensor data throughout their day.

Aadi Jain

I am an avid software enthusiast with keen interest and experience in a wide array of software domains ranging from full stack to low level embedded programming. Currently, a Junior here at the Paul G Allen Institute at UW pursuing Computer Science. I am working on the Sensing App under the supervision of Kelly Mack at the Make4All lab.