Priming is used as a way of increasing the diversity of proposals in end-user elicitation studies, but priming has not been investigated thoroughly in this context. We conduct a distributed end-user elicitation study with 167 participants, which had three priming groups: a no-priming control group, sci-fi priming, and a creative mindset group. We evaluated the gestures proposed by these groups in a distributed learnability and memorability study with 18 participants. We found that the user-elicited gestures from the sci-fi group were significantly faster to learn, requiring an average of 1.22 viewings to learn compared to 1.60 viewings required to learn the control gestures, and 1.56 viewings to learn the gestures elicited from the creative mindset group. In addition, both primed gesture groups had higher memorability with 80% of the sci-fi-primed gestures and 73% of the creative mindset group gestures were recalled correctly after one week without practice compared to 43% of the control group gestures.

End-user elicitation studies are a popular design method. Currently, such studies are usually confined to a lab, limiting the number and diversity of participants, and therefore the representativeness of their results. Furthermore, the quality of the results from such studies generally lacks any formal means of evaluation. In this paper, we address some of the limitations of elicitation studies through the creation of the Crowdlicit system along with the introduction of end-user identification studies, which are the reverse of elicitation studies. Crowdlicit is a new web-based system that enables researchers to conduct online and in-lab elicitation and identification studies. We used Crowdlicit to run a crowd-powered elicitation study based on Morris's "Web on the Wall" study (2012) with 78 participants, arriving at a set of symbols that included six new symbols different from Morris's. We evaluated the effectiveness of 49 symbols (43 from Morris and six from Crowdlicit) by conducting a crowd-powered identification study. We show that the Crowdlicit elicitation study resulted in a set of symbols that was significantly more identifiable than Morris's.

As many as 20% of English speakers have dyslexia, a language disability that impacts reading and spelling. Web search is an important modern literacy skill, yet the accessibility of this language-centric endeavor to people with dyslexia is largely unexplored. We interviewed ten adults with dyslexia and conducted an online survey with 81 dyslexic and 80 non-dyslexic adults, in which participants described challenges they face in various stages of web search (query formulation, search result triage, and information extraction). We also report the findings of an online study in which 174 adults with dyslexia and 172 without dyslexia rated the readability and relevance of sets of search query results. Our findings demonstrate differences in behaviors and preferences between dyslexic and non-dyslexic searchers, and indicate that factoring readability into search engine rankings and/or interfaces may benefit both dyslexic and non-dyslexic users.

Standards organizations, (e.g., the World Wide Web Consortium), are placing increased importance on the cognitive accessibility of online systems, including web search. Previous work has shown an association between query-document relevance judgments, and query-independent assessments of document readability. In this paper we study the lexical and aesthetic features of web documents that may underlie this relationship. Leveraging a data set consisting of relevance and readability judgments for 200 web pages as assessed by 174 adults with dyslexia and 172 adults without dyslexia, we answer the following research questions: (1) Which web page features are most associated with readability? (2) To what extent are these features also associated with relevance? And, (3) are any features associated with the differences in readability/relevance judgments observed between dyslexic and non-dyslexic populations? Our findings have implications for improving the cognitive accessibility of search systems and web documents.

End-user elicitation studies are a popular design method, but their data require substantial time and effort to analyze. In this paper, we present Crowdsensus, a crowd-powered tool that enables researchers to efficiently analyze the results of elicitation studies using subjective human judgment and automatic clustering algorithms. In addition to our own analysis, we asked six expert researchers with experience running and analyzing elicitation studies to analyze an end-user elicitation dataset of 10 functions for operating a web-browser, each with 43 voice commands elicited from end-users for a total of 430 voice commands. We used Crowdsensus to gather similarity judgments of these same 430 commands from 410 online crowd workers. The crowd outperformed the experts by arriving at the same results for seven of eight functions and resolving a function where the experts failed to agree. Also, using Crowdsensus was about four times faster than using experts.

Individuals who experience temporary, intermittent, or gradual changes in pointing ability may encounter frustrating experiences when using computer input devices. Personalized pointing systems that automatically assess changes in performance and provide individualized information and assistance may benefit these users. However, there has been little inquiry into this populations' expectations for interacting with these types of systems. We describe a participatory design process in which we used a technology probe to assess the information needs and expectations of 27 individuals who experience occasional changes in pointing ability, through interactions with and discussion regarding a high-fidelity personalized pointing prototype. Participants preferred notification and adaptation interactions that provided them with control and explanation of system actions, instead of abstract notifications and automatic adaptations. We describe how we applied these finding in the design of the PINATA system.

Detecting dyslexia is crucial so that people who have dyslexia can receive training to avoid associated high rates of academic failure. In this paper we present Dytective, a game designed to detect dyslexia. The results of a within-subjects experiment with 40 children (20 with dyslexia) show significant differences between groups who played Dytective. These differences suggest that Dytective could be used to help identify those likely to have dyslexia.

An increasing number of online communities support the open-source sharing of designs that can be built using rapid prototyping to construct physical objects. In this paper, we examine the designs and motivations for assistive technology found on Thingiverse.com, the largest of these communities at the time of this writing. We present results from a survey of all assistive technology that has been posted to Thingiverse since 2008 and a questionnaire distributed to the designers exploring their relationship with assistive technology and the motivation for creating these designs. The majority of these designs are intended to be manufactured on a 3D printer and include assistive devices and modifications for individuals with disabilities, older adults, and medication management. Many of these designs are created by the end-users themselves or on behalf of friends and loved ones. These designers frequently have no formal training or expertise in the creation of assistive technology. This paper discusses trends within this community as well as future opportunities and challenges.