The Impact of COVID-19 Remote Learning on Students with Disabilities

Han Zhang, Margaret E. Morris, Paula S. Nurius, Kelly Mack, Jennifer Brown, Kevin S. Kuehn, Yasaman S. Sefidgar, Xuhai Xu, Eve A. Riskin, Anind K. Dey and Jennifer Mankoff. Impact of Online Learning in the Context of COVID-19 on Undergraduates with Disabilities and Mental Health Concerns. Transactions on Accessible Computing. Accepted, April 12th, 2022.

The COVID-19 pandemic upended college education and the experiences of students due to the rapid and uneven shift to online
learning. This study examined the experiences of students with disabilities with online learning, with a consideration of surrounding
stressors such as financial pressures. In a mixed method approach, we compared 28 undergraduate students with disabilities(including
mental health concerns) to their peers during 2020, to assess differences and similarities in their educational concerns, stress levels and
COVID-19 related adversities. We found that students with disabilities entered the Spring quarter of 2020 with significantly higher
concerns about classes going online, and reported more recent negative life events than other students. These differences between the
two groups diminished three months later with the exception of recent negative life events. For a fuller understanding of students’
experiences, we conducted qualitative analysis of open ended interviews. We examined both positive and negative experiences with
online learning among students with disabilities and mental health concerns. Online learning enabled greater access–
e.g., reducing the need for travel to campus–alongside ways in which online learning impeded academic engagement–e.g., reducing
interpersonal interaction. Learning systems need to continue to meet the diverse and dynamic needs of students with disabilities.

Anticipate and Adjust

Kelly MackEmma McDonnellVenkatesh PotluriMaggie XuJailyn ZabalaJeffrey Bigham, Jennifer Mankoff, Cynthia L. Bennett:
Anticipate and Adjust: Cultivating Access in Human-Centered Methods. CHI 2022: 603:1-603:18 [pdf] [Plain Language Summary]

“Human-centered research” must make sure that research practices are accessible for both participants and researchers with disabilities. Yet, people rarely discuss how to make common methods accessible. We interviewed 17 accessibility experts who were researchers or community organizers about their practices. Our findings emphasize the importance of considering accessibility at all stages of the research process and across different dimensions of studies like communication, materials, time, and space. We explore how technology or processes could reflect a norm of accessibility and offer a practical structure for planning accessible research.

Maptimizer

Megan HofmannKelly MackJessica BirchfieldJerry CaoAutumn G. HughesShriya KurpadKathryn J. LumEmily WarnockAnat CaspiScott E. Hudson, Jennifer Mankoff:
Maptimizer: Using Optimization to Tailor Tactile Maps to Users Needs. CHI 2022: 592:1-592:15 [pdf]

Tactile maps can help people who are blind or have low vision navigate and familiarize themselves with unfamiliar locations. Ideally, tactile maps are created by considering an individual’s unique needs and abilities because of their limited space for representation. However, significant customization is not supported by existing tools for generating tactile maps. We present the Maptimizer system which generates tactile maps that are customized to a user’s preferences and requirements, while making simplified and easy to read tactile maps. Maptimizer uses a two stage optimization process to pair representations with geographic information and tune those representations to present that information more clearly. In a user study with six blind/low-vision participants, Maptimizer helped participants more successfully and efficiently identify locations of interest in unknown areas. These results demonstrate the utility of optimization techniques and generative design in complex accessibility domains that require significant customization by the end user.

A system diagram showing the maptimizer data flow setup. The inputs are geography sets, representations options, and user preferences. Geography types and representation options are paired and tuned using an optimizer. The output is a tactile map.

Computational Design of Knit Templates

We present an interactive design system for knitting that allows users to create template patterns that can be fabricated using an industrial knitting machine. Our interactive design tool is novel in that it allows direct control of key knitting design axes we have identified in our formative study and does so consistently across the variations of an input parametric template geometry. This is achieved with two key technical advances. First, we present an interactive meshing tool that lets users build a coarse quadrilateral mesh that adheres to their knit design guidelines. This solution ensures consistency across the parameter space for further customization over shape variations and avoids helices, promoting knittability. Second, we lift and formalize low-level machine knitting constraints to the level of this coarse quad mesh. This enables us to not only guarantee hand- and machine-knittability, but also provides automatic design assistance through auto-completion and suggestions. We show the capabilities through a set of fabricated examples that illustrate the effectiveness of our approach in creating a wide variety of objects and interactively exploring the space of design variations.

Benjamin JonesYuxuan MeiHaisen ZhaoTaylor Gotfrid, Jennifer Mankoff, Adriana Schulz:
Computational Design of Knit Templates. ACM Trans. Graph. 41(2): 16:1-16:16 (2022)

Four pink knit dresses mounted on four mannekins. each showing different styles of neckline and skirt. Behind each dress is the pattern used to create that dress. The shape of the quads in the pattern demonstrate their relationship to typical knitting patterns -- for example a collar knit in the round has quads that narrow as they go up.

Our interactive design system helps users explore key design axes for knitting to generate highly customized patterns from input shape templates; e.g., a seamless yoke dress with princess-cut apparent seams (a), and drop shoulder dresses with textures on the arms and skirt (b–d). The output of our system is a knit pattern template that lets users vary the shape while preserving the design, for example, creating a child’s dress with short sleeves (d) that matches an adult dress (b), or varying skirt texture and angle, and sleeve knitting direction (c). The system guarantees that all results and variations are machine knittable.

A diagram showing four differently shaped duck faces (a) which all have the same mesh, which can react easily to different shapes by adjusting quad shapes. The final product of a duck with a short, and a long, snout, is shown knitted in lavendar at the right.

Overview of our framework. (a) Triangle meshes from a parametric template (the system deals with a single mesh at a time). (b) Input triangle mesh with user annotations of composition, layout, and direction guidelines. (c) Generated quad mesh patches, which are consistent across template variations. (d) Quad mesh annotated for knitting the body tube in the round using short rows to curve the tube. Blue lines indicate seams. The same design applies to all template variations (two shown here). (e) Duck knit with short rows. (f ) Quad mesh annotated with different textures and orientations; the body is knit as seamed sheets with decreases. (g) Duck knit with textures and a large head from template (f ).

TypeOut: Just-in-Time Self-Affirmation for Reducing Phone Use

Smartphone overuse is related to a variety of issues such as lack of sleep and anxiety. We explore the application of Self-Affirmation Theory on smartphone overuse intervention in a just-in-time manner. We present TypeOut, a just-in-time intervention technique that integrates two components: an in-situ typing-based unlock process to improve user engagement, and self-affirmation-based typing content to enhance effectiveness. We hypothesize that the integration of typing and self-affirmation content can better reduce smartphone overuse. We conducted a 10-week within-subject field experiment (N=54) and compared TypeOut against two baselines: one only showing the self-affirmation content (a common notification-based intervention), and one only requiring typing non-semantic content (a state-of-the-art method). TypeOut reduces app usage by over 50%, and both app opening frequency and usage duration by over 25%, all significantly outperforming baselines. TypeOut can potentially be used in other domains where an intervention may benefit from integrating self-affirmation exercises with an engaging just-in-time mechanism.

Typeout: Leveraging just-in-time self-affirmation for smartphone overuse reduction. Xuhai Xu, Tianyuan Zou, Xiao Han, Yanzhang Li, Ruolin Wang, Tianyi Yuan, Yuntao Wang, Yuanchun Shi, Jennifer Mankoff,and Anind K. Dey. 2022. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ’22). ACM, New York, NY, USA.

What Do We Mean by “Accessibility Research”?

Accessibility research has grown substantially in the past few decades, yet there has been no literature review of the field. To understand current and historical trends, we created and analyzed a dataset of accessibility papers appearing at CHI and ASSETS since ASSETS’ founding in 1994. Our findings highlight areas that have received disproportionate attention and those that are underserved— for example, over 43% of papers in the past 10 years are on accessibility for blind and low vision people. We also capture common study characteristics, such as the roles of disabled and nondisabled participants as well as sample sizes (e.g., a median of 13 for participant groups with disabilities and older adults). We close by critically reflecting on gaps in the literature and offering guidance for future work in the field.

What Do We Mean by “Accessibility Research”? A Literature Survey of Accessibility Papers in CHI and ASSETS from 1994 to 2019. Kelly Mack, Emma McDonnell, Dhruv Jain, Lucy Lu Wang, Jon E. Froehlich, and Leah Findlater In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 371, 1–18.

Designing Tools for High-Quality Alt Text Authoring

Alternative (alt) text is a description of a digital images so that someone who is blind or low vision or otherwise uses a screen reader to understand image content. Little work examines what it is like to write alt text for an image. We created interface designs to support writing and providing feedback about alt text and tested them with people who write alt text and people who use alt text. Our results suggest that authoring interfaces that support authors in choosing what to include in their descriptions result in higher quality alt text. The feedback interfaces highlighted considerable diferences in the perceptions of authors and SRUs regarding “high-quality” alt text. We discuss the implications of these results on applications that support alt text.

Designing Tools for High-Quality Alt Text Authoring. Kelly Mack, Edward Cutrell, Bongshin Lee, and Meredith Ringel Morris. In The 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’21). Association for Computing Machinery, New York, NY, USA, Article 23, 1–14.

Mixed Abilities and Varied Experiences in a Virtual Summer Internship


The COVID-19 pandemic forced many people to convert their daily work lives to a “virtual” format where everyone connected remotely from their home, which affected the accessibility of work environments. We the authors, full time and intern members of an accessibility-focused team at Microsoft Research, reflect on our virtual work experiences as a team consisting of members with a variety of abilities, positions, and seniority during the summer intern season. We reflect on our summer experiences, noting the successful strategies we used to promote access and the areas in which we could have further improved access.

Mixed Abilities and Varied Experiences: a group autoethnography of a virtual summer internship. Kelly Mack, Maitraye Das, Dhruv Jain, Danielle Bragg, John Tang, Andrew Begel, Erin Beneteau, Josh Urban Davis, Abraham Glasser, Joon Sung Park, and Venkatesh Potluri. In The 23rd International ACM SIGACCESS Conference on Computers and Accessibility, pp. 1-13. 2021.

Anticipate and Adjust: Cultivating Access in Human-Centered Methods

In order for “human-centered research” to include all humans, we need to make sure that research practices are accessible for both participants and researchers with disabilities. Yet, people rarely discuss how to make common methods accessible. We interviewed 17 accessibility experts who were researchers or community organizers about their practices. Our findings emphasize the importance of considering accessibility at all stages of the research process and across different dimensions of studies like communication, materials, time, and space. We explore how technology or processes could reflect a norm of accessibility and offer a practical structure for planning accessible research.

Anticipate and Adjust: Cultivating Access in Human-Centered Methods. Kelly Mac, Emma J. McDonnell, Venkatesh Potluri, Maggie Xu, Jailyn Zabala, Jeffrey P. Bigham, Jennifer Mankoff, and Cynthia L. Bennett. CHI 2022

Practices and Needs of Mobile Sensing Researchers

Passive mobile sensing for the purpose of human state modeling is a fast-growing area. It has been applied to solve a wide range of behavior-related problems, including physical and mental health monitoring, affective computing, activity recognition, routine modeling, etc. However, in spite of the emerging literature that has investigated a wide range of application scenarios, there is little work focusing on the lessons learned by researchers, and on guidance for researchers to this approach. How do researchers conduct these types of research studies? Is there any established common practice when applying mobile sensing across different application areas? What are the pain points and needs that they frequently encounter? Answering these questions is an important step in the maturing of this growing sub-field of ubiquitous computing, and can benefit a wide range of audiences. It can serve to educate researchers who have growing interests in this area but have little to no previous experience. Intermediate researchers may also find the results interesting and helpful for reference to improve their skills. Moreover, it can further shed light on the design guidelines for a future toolkit that could facilitate research processes being used. In this paper, we fill this gap and answer these questions by conducting semi-structured interviews with ten experienced researchers from four countries to understand their practices and pain points when conducting their research. Our results reveal a common pipeline that researchers have adopted, and identify major challenges that do not appear in published work but that researchers often encounter. Based on the results of our interviews, we discuss practical suggestions for novice researchers and high-level design principles for a toolkit that can accelerate passive mobile sensing research.

Understanding practices and needs of researchers in human state modeling by passive mobile sensing. Xu, Xuhai, Jennifer Mankoff, and Anind K. Dey. CCF Transactions on Pervasive Computing and Interaction (2021): 1-23.