Improving mobile keyboard typing speed increases in value as more tasks move to a mobile setting. Autocorrect is a powerful way to reduce the time it takes to manually fix typing errors, which results in typing speed increase. However, recent user studies of autocorrect uncovered an unexplored side-effect: participants’ aversion to typing errors despite autocorrect. We present the first computational model of typing on keyboards with autocorrect, which enables precise study of expert typists’ aversion to typing errors on such keyboards. Unlike empirical typing studies that last days, our model evaluates the effects of typists’ aversion to typing errors for any autocorrect accuracy in seconds. We show that typists’ aversion to typing errors adds a self-imposed limit on upper bound typing speeds, which decreases the value of highly accurate autocorrect. Our findings motivate future designs of keyboards with autocorrect that reduce typists’ aversion to typing errors to increase typing speeds.
The Limits of Expert Text Entry Speed on Mobile Keyboards with Autocorrect Nikola Banovic, Ticha Sethapakdi, Yasasvi Hari, Anind K. Dey, Jennifer Mankoff. Mobile HCI 2019.
An example mobile device with a soft keyboard: A) text entry area, which in our study contained study progress, the current phrase to transcribe, and an area for transcribed characters, B) automatically suggested words, and C) a miniQWERTY soft keyboard with autocorrect.
Knitting creates complex, soft objects with unique and controllable texture properties that can be used to create interactive objects. However, little work addresses the challenges of using knitted textures. We present KnitPick: a pipeline for interpreting pre-existing hand-knitting texture patterns into a directed-graph representation of knittable structures (KnitGraphs) which can be output to machine and hand-knitting instructions. Using KnitPick, we contribute a measured and photographed data set of 300 knitted textures. Based on findings from this data set, we contribute two algorithms for manipulating KnitGraphs. KnitCarving shapes a graph while respecting a texture, and KnitPatching combines graphs with disparate textures while maintaining a consistent shape. Using these algorithms and textures in our data set we are able to create three Knitting based interactions: roll, tug, and slide. KnitPick is the first system to bridge the gap between hand- and machine-knitting when creating complex knitted textures.
A deeper understanding of how discrimination impacts psychological health and well-being of students would allow us to better protect individuals at risk and support those who encounter discrimination. While the link between discrimination and diminished psychological and physical well-being is well established, existing research largely focuses on chronic discrimination and long-term outcomes. A better understanding of the short-term behavioral correlates of discrimination events could help us to concretely quantify the experience, which in turn could support policy and intervention design. In this paper we specifically examine, for the first time, what behaviors change and in what ways in relation to discrimination. We use actively-reported and passively-measured markers of health and well-being in a sample of 209 first-year college students over the course of two academic quarters. We examine changes in indicators of psychological state in relation to reports of unfair treatment in terms of five categories of behaviors: physical activity, phone usage, social interaction, mobility, and sleep. We find that students who encounter unfair treatment become more physically active, interact more with their phone in the morning, make more calls in the evening, and spend more time in bed on the day of the event. Some of these patterns continue the next day.
Passively-sensed Behavioral Correlates of Discrimination Events in College Students. Yasaman S. Sefidgar, Woosuk Seo, Kevin S. Kuehn, Tim Althoff, Anne Browning, Eve Ann Riskin, Paula S. Nurius, Anind K Dey, Jennifer Mankoff. CSCW 2019, To Appear
Design in the Public Square: Supporting Cooperative Assistive Technology Design Through Public Mixed-Ability Collaboration (CSCW 2019)
Mark. S. Baldwin, Sen H Hirano, Jennifer Mankoff, Gillian Hayes
From the white cane to the smartphone, technology has been an effective tool for broadening blind and low vision participation in a sighted world. In the face of this increased participation, individuals with visual impairments remain on the periphery of most sight-first activities. In this paper, we describe a multi-month public-facing co-design engagement with an organization that supports blind and low vision outrigger paddling. Using a mixed-ability design team, we developed an inexpensive cooperative outrigger paddling system, called DEVICE, that shares control between sighted and visually impaired paddlers. The results suggest that public design, a DIY (do-it-yourself) stance, and attentiveness to shared physical experiences, represent key strategies for creating assistive technologies that support shared experiences.
Access technology (AT) has the potential to increase autonomy, and improve millions of people’s ability to live independently. This potential is currently under-realized because the expertise needed to create the right AT is in short supply and the custom nature of AT makes it difficult to deliver inexpensively. Yet computers’ flexibility and exponentially increasing power have revolutionized and democratized access technologies. In addition, by studying access technology, we can gain valuable insights into the future of all user interface technology.
In this course we will focus on two primary domains for access technologies: Access to the world (first half of the class) and Access to computers (second half of class). Students will start the course by learning some basic physical computing capabilities so that they have the tools to build novel access technologies. We will focus on creating AT using sensors and actuators that can be controlled/sensed with a mobile device. The largest project in the class will be an open ended opportunity to explore access technology in more depth.
WebAim.org — WebAIM has long been a leader in providing information and tutorials on making the Web accessible. A great source where you can read about accessibility issues, making content accessible, etc.
Solo Assignment: Make An Accessible Web Page (due for in-class grading on 11/18)
Week 9 (11/25; 11/27): Screen Readers
Building screen reader (NVDA, … )
Building accessible app (work with screen reader)
Paradigms for Nonvisual Input
Optical Character Recognition
Audio Description for Video
Test each others’ accessible pages
Mid-project Reports (Requirements TBD)
Week 10 (12/2): Other Computer Accessibility Challenges
Low Bandwidth Input
Volunteer Activity due
Interesting topics to consider (e.g. from Jeff’s class)
Wireless Analytics for 3D Printed Objects: Vikram Iyer, Justin Chan, Ian Culhane, Jennifer Mankoff, Shyam Gollakota UIST, Oct. 2018 [PDF]
We created a wireless physical analytics system works with commonly available conductive plastic filaments. Our design can enable various data capture and wireless physical analytics capabilities for 3D printed objects, without the need for electronics.
We make three key contributions:
(1) We demonstrate room scale backscatter communication and sensing using conductive plastic filaments.
(2) We introduce the first backscatter designs that detect a variety of bi-directional motions and support linear and rotational movements. An example is shown below
(3) As shown in the image below, we enable data capture and storage for later retrieval when outside the range of the wireless coverage, using a ratchet and gear system.
We validate our approach by wirelessly detecting the opening and closing of a pill bottle, capturing the joint angles of a 3D printed e-NABLE prosthetic hand, and an insulin pen that can store information to track its use outside the range of a wireless receiver.
The absence of tactile cues such as keys and buttons makes touchscreens difficult to navigate for people with visual impairments. Increasing tactile feedback and tangible interaction on touchscreens can improve their accessibility. However, prior solutions have either required hardware customization or provided limited functionality with static overlays. In addition, the investigation of tactile solutions for large touchscreens may not address the challenges on mobile devices. We therefore present Interactiles, a low-cost, portable, and unpowered system that enhances tactile interaction on Android touchscreen phones. Interactiles consists of 3D-printed hardware interfaces and software that maps interaction with that hardware to manipulation of a mobile app. The system is compatible with the built-in screen reader without requiring modification of existing mobile apps. We describe the design and implementation of Interactiles, and we evaluate its improvement in task performance and the user experience it enables with people who are blind or have low vision.
XiaoyiZhang, TracyTran, YuqianSun, IanCulhane, ShobhitJain, JamesFogarty, JenniferMankoff:Interactiles: 3D Printed Tactile Interfaces to Enhance Mobile Touchscreen Accessibility. ASSETS 2018: To Appear[PDF]
Web user interfaces today leverage many common GUI design patterns, including navigation bars and menus (hierarchical structure), tabular content presentation, and scrolling. These visual-spatial cues enhance the interaction experience of sighted users. However, the linear nature of screen translation tools currently available to blind users make it difficult to understand or navigate these structures. We introduce Spatial Region Interaction Techniques (SPRITEs) for nonvisual access: a novel method for navigating two-dimensional structures using the keyboard surface. SPRITEs 1) preserve spatial layout, 2) enable bimanual interaction, and 3) improve the end user experience. We used a series of design probes to explore different methods for keyboard surface interaction. Our evaluation of SPRITEs shows that three times as many participants were able to complete spatial tasks with SPRITEs than with their preferred current technology.
Audio-only interfaces, facilitated through text-to-speech screen reading software, have been the primary mode of computer interaction for blind and low-vision computer users for more than four decades. During this time, the advances that have made visual interfaces faster and easier to use, from direct manipulation to skeuomorphic design, have not been paralleled in nonvisual computing environments. The screen reader–dependent community is left with no alternatives to engage with our rapidly advancing technological infrastructure. In this article, we describe our efforts to understand the problems that exist with audio-only interfaces. Based on observing screen reader use for 4 months at a computer training school for blind and low-vision adults, we identify three problem areas within audio-only interfaces: ephemerality, linear interaction, and unidirectional communication. We then evaluated a multimodal approach to computer interaction called the Tangible Desktop that addresses these problems by moving semantic information from the auditory to the tactile channel. Our evaluation demonstrated that among novice screen reader users, Tangible Desktop improved task completion times by an average of 6 minutes when compared to traditional audio-only computer systems.
Average task completion time comparison between the participant system and experimental system grouped by technology
Task completion time comparison between the participant system and experimental system for screen reader users. Study system is faster in all cases. Completion times are total elapsed time, so we have not included error bars.
The physical icons used in the Tangible Desktop. Each icon is a small cube that has an RFID tag embedded inside and a tactilely distinct rubber crown.
A picture of the Tangible Desktop in its standard arrangement. The Tangible Taskbar sits to the left of the laptop while a user engages with the thumb of the Tangible Scrollbar.
Examples of the different hand positions used by study participants.
Kim, J., Guo, A., Yeh, T., Hudson, S. E., & Mankoff, J. (2017, June). Understanding Uncertainty in Measurement and Accommodating its Impact in 3D Modeling and Printing. In Proceedings of the 2017 Conference on Designing Interactive Systems (pp. 1067-1078). ACM.
3D printing enables everyday users to augment objects around them with personalized adaptations. There has been a proliferation of 3D models available on sharing platforms supporting this. If a model is parametric, a novice modeler can obtain a custom model simply by entering a few parameters (e.g., in the Customizer tool on Thingiverse.com). In theory, such custom models could fit any real world object one intends to augment. But in practice, a printed model seldom fits on the first try; multiple iterations are often necessary, wasting a considerable amount of time and material. We argue that parameterization or scaling alone is not sufficient for customizability, because users must correctly measure an object to specify parameters.
In a study of attempts to measure length, angle, and diameter, we demonstrate measurement errors as a significant (yet often overlooked) factor that adversely impacts the adaptation of 3D models to existing objects, requiring increased iteration. Images taken from our study are shown below.
Edge of phone is curved, and length difficult to measure
Ruler is bent, introducing error
Bulb is not correctly lined up with ruler
We argue for a new design principle—accommodating measurement uncertainty—that designers as well as novices should begin to consider. We offer two strategies—modular joint and, buffer insertion—to help designers to build models that are robust to measurement uncertainty. Examples shown below.