Online financial scams represent a long-standing and serious threat for which people seek help. We present a study to understand people’s in situ motivations for engaging with scams and the help needs they express before, during, and after encountering a scam. We identify the main emotions scammers exploited (e.g., fear, hope) and characterize how they did so. We examine factors—such as financial insecurity and legal precarity—which elevate people’s risk of engaging with specific scams and experiencing harm. We indicate when people sought help and describe their help-seeking needs and emotions at different stages of the scam. We discuss how these needs could be met through the design of contextually-specific prevention, diagnostic, mitigation, and recovery interventions.

A growing body of qualitative research has identified contextual risk factors that elevate people’s chances of experiencing digital-safety attacks. However, the lack of quantitative data on the population-level distribution of these risk factors prevents policymakers and tech companies from developing targeted, evidence-based interventions to improve digital safety. To address this gap, we surveyed 5,001 adults in the United States to analyze: (1) the frequency of and relationship between digital-safety attacks (e.g., scams, harassment, account hacking), and (2) how these attacks align with 10 contextual risk factors. Nearly half of our respondents identify as resource constrained, which significantly correlates with higher likelihood of experiencing four common attacks. We also present qualitative insights to expand our understanding of the factors beyond the existing literature (e.g., “prominence” included high-visibility roles in local communities). This study provides the first large-scale quantitative analysis correlating digital-safety attacks with contextual risk factors and demographics.

Creating information technologies intended for broad use that allow everyone to participate safely online—which we refer to as inclusive digital safety —requires understanding and addressing the digital-safety needs of a diverse range of users who face elevated risk of technology-facilitated attacks or disproportionate harm from such attacks—i.e., at-risk users . This article draws from more than 9 years of our work at Google to understand and support the digital safety of at-risk users—including survivors of intimate partner abuse, people involved with political campaigns, content creators, youth, and more—in technology intended for broad use. Among our learnings is that designing for inclusive digital safety across widely varied user needs and dynamic contexts is a wicked problem with no “correct” solution. Given this, we describe frameworks and design principles we have developed to help make at-risk research findings practically applicable to technologies intended for broad use and lessons we have learned about communicating them to practitioners.

Research involving at-risk users—that is, users who are more likely to experience a digital attack or to be disproportionately affected when harm from such an attack occurs—can pose significant safety challenges to both users and researchers. Nevertheless, pursuing research in computer security & privacy (S&P) is crucial to understanding how to meet the digital-safety needs of at-risk users and to design safer technology for all. To standardize and bolster safer research involving such users, we offer an analysis of 196 academic works to elicit 14 research risks and 36 safety practices used by a growing community of researchers. We pair this inconsistent set of reported safety practices with oral histories from 12 domain experts to contribute scaffolded and consolidated pragmatic guidance that researchers can use to plan, execute, and share safer digital-safety research involving at-risk users. We conclude by suggesting areas for future research regarding the reporting, study, and funding of at-risk user research.

At-risk users are people who experience risk factors that augment or amplify their chances of being digitally attacked and/or suffering disproportionate harms. In this systematization work, we present a framework for reasoning about at-risk users based on a wide-ranging meta-analysis of 95 papers. Across the varied populations that we examined (e.g., children, activists, people with disabilities), we identified 10 unifying contextual risk factors —such as marginalization and access to a sensitive resource —that augment or amplify digital-safety risks and their resulting harms. We also identified technical and non-technical practices that at-risk users adopt to attempt to protect themselves from digital-safety risks. We use this framework to discuss barriers that limit at-risk users’ ability or willingness to take protective actions. We believe that researchers and technology creators can use our framework to identify and shape research investments to benefit at-risk users, and to guide technology design to better support at-risk users.

South Asia faces one of the largest gender gaps online globally, and online safety is one of the main barriers to gender-equitable Internet access [GSMA, 2015]. To better understand the gendered risks and coping practices online in South Asia, we present a qualitative study of the online abuse experiences and coping practices of 199 people who identified as women and 6 NGO staff from India, Pakistan, and Bangladesh, using a feminist analysis. We found that a majority of our participants regularly contended with online abuse, experiencing three major abuse types: cyberstalking, impersonation, and personal content leakages. Consequences of abuse included emotional harm, reputation damage, and physical and sexual violence. Participants coped through informal channels rather than through technological protections or law enforcement. Altogether, our findings point to opportunities for designs, policies, and algorithms to improve women's safety online in South Asia.

Addressing digital security and privacy issues can be particularly difficult for users who face challenging circumstances. We performed semi-structured interviews with residents and staff at 4 transitional homeless shelters in the U.S. San Francisco Bay Area (n=15 residents, 3 staff) to explore their digital security and privacy challenges. Based on these interviews, we outline four tough times themes --- challenges experienced by our financially insecure participants that impacted their digital security and privacy --- which included: (1) limited financial resources, (2) limited access to reliable devices and Internet, (3) untrusted relationships, and (4) ongoing stress. We provide examples of how each theme impacts digital security and privacy practices and needs. We then use these themes to provide a framework outlining opportunities for technology creators to better support users facing security and privacy challenges related to financial insecurity.

We present a qualitative study of the digital privacy and security motivations, practices, and challenges of survivors of intimate partner abuse (IPA). This paper provides a framework for organizing survivors' technology practices and challenges into three phases: physical control, escape, and life apart. This three-phase framework combines technology practices with three phases of abuse to provide an empirically sound method for technology creators to consider how survivors of IPA can leverage new and existing technologies. Overall, our results suggest that the usability of and control over privacy and security functions should be or continue to be high priorities for technology creators seeking ways to better support survivors of IPA.

Many technologies assume a single user will use an account or device. But account and device sharing situations (when 2+ people use a single device or account) may arise during everyday life. We present results from a multiple-methods study of device and account sharing practices among household members and their relations. Among our findings are that device and account sharing was common, and mobile phones were often shared despite being considered "personal" devices. Based on our study results, we organize sharing practices into a taxonomy of six sharing types--distinct patterns of what, why, and how people shared. We also present two themes that cut across sharing types: that (1) trust in sharees and (2) convenience highly influenced sharing practices. Based on these findings, we discuss implications for study and technology design.

Research on small team collaboration repeatedly shows that 'distance matters'. More recent work has refined this concept of distance to develop geographic dispersion measures to explain the negative effects that team configuration has on productivity and interaction. Dispersion measures explain why teams distributed across multiple time zones, or across multiple sites, have more coordination difficulties than collocated teams with a single remote member. Although larger online communities are increasingly used in enterprises, few studies have examined the effects of dispersion on community behavior. We studied 1206 online enterprise communities (OECs), each using a set of collaborative tools. We present new data showing counter-intuitively that OEC dispersion does not affect content generation or contribution inequality, even when restricting community size to those that most resemble small teams (with 3-12 members). We found that previously documented negative effects of geographic dispersion seem to be reduced in enterprise communities regardless of size. Our results provide additional support to prior case studies suggesting that online communities can mitigate geographic dispersion by providing resources that support coordination and resource sharing.

Recent research has developed analytics that threaten online self-presentation and privacy by automatically generating profiles of individuals' most personal traits-their personality, values, motivations, and so on. But we know little about people's reactions to personal traits profiles of themselves, or what influences their decisions to share such profiles. We present an early qualitative study of people's reactions to a working hyper-personal analytics system. The system lets them see their personality and values profile derived from their own social media text. Our results reveal a paradox. Participants found their personal traits profiles creepily accurate and did not like sharing them in many situations. However, they felt pressured by the social risks of not sharing and showed signs of learned helplessness, leading them to share despite their misgivings. Further, they felt unqualified to significantly modify their profile contents due to a surprising trust in the "expert" algorithm. We explore design implications for hyper-personal analytics systems that consider the needs and preferences of the people being profiled, suggesting ways to enhance the control they feel and the benefits they reap.

In online communities, satisfied members are essential to community success, since they are more likely to contribute and consume content, engage with other members, and feel committed to the community. However, it is difficult for community leaders to know, on an on-going basis, whether members are satisfied. In this paper, we explore the relationship between member satisfaction and language use within content posted in workplace online communities. We hope to find patterns of language use that are associated with satisfied members. We employ linguistic analysis based on LIWC, and a survey to directly measure member satisfaction in 142 workplace communities. We contribute a better understanding of how members interact in effective workplace communities, and show that linguistic analysis could be a useful part of future methods to automatically assess community member satisfaction.

Online communities are successful only if they achieve their goals, but there has been little direct study of goals. We analyze novel data characterizing the goals of enterprise online communities, assessing the importance of goals for leaders, how goals influence member perceptions of community value, and how goals relate to success measures proposed in the literature. We find that most communities have multiple goals and common goals are learning, reuse of resources, collaboration, networking, influencing change, and innovation. Leaders and members agree that all of these goals are important, but their perceptions of success on goals do not align with each other, or with commonly used behavioral success measures. We conclude that simple behavioral measures and leader perceptions are not good success metrics, and propose alternatives based on specific goals members and leaders judge most important.

Online communities serve various important functions, but many fail to thrive. Research on community success has traditionally focused on internal factors. In contrast, we take an ecological view to understand how the success of a community is influenced by other communities. We measured a community's relationship with other communities - its "niche" - through four dimensions: topic overlap, shared members, content linking, and shared offline organizational affiliation. We used a mixed-method approach, combining the quantitative analysis of 9495 online enterprise communities and interviews with community members. Our results show that too little or too much overlap in topic with other communities causes a community's activity to suffer. We also show that this main result is moderated in predictable ways by whether the community shares members with, links to content in, or shares an organizational affiliation with other communities. These findings provide new insight on community success, guiding online community designers on how to effectively position their community in relation to others.

Most studies of social tools examine usage of each tool in isolation. Instead, we explore how online communities (a) combine multiple social tools, and (b) use social tools together with external tools. Based on interviews with community leaders and quantitative analysis of 128 online community spaces, we explored the combined use of six social software tools--wikis, blogs, forums, social bookmarks, social file repositories, and task-management tools. We contribute a detailed characterization of how enterprise online communities combine multiple social tools, adding to our understanding of community behaviors: Communities combine social tools to curate and organize complex information spaces. When combined, each tool is used for limited "core" functions; thus 'social' features are not always leveraged for every tool. Leaders and members divide labor by tool boundaries. Our results suggest that an important overlooked aspect of social media concerns how different tools can be effectively combined. While most prior work on communities emphasizes end user content, we identify additional important design activities where community participants curate and organize pre-existing content from multiple tools to serve their community needs.

Online communities are increasingly being deployed in enterprises to increase productivity and share expertise. Community leaders are critical for fostering successful communities, but existing technologies rarely support leaders directly, both because of a lack of clear data about leader needs, and because existing tools are member- rather than leader-centric. We present the evidence-based design and evaluation of a novel tool for community leaders, Community Insights (CI). CI provides actionable analytics that help community leaders foster healthy communities, providing value to both members and the organization. We describe empirical and system contributions derived from a long-term deployment of CI to leaders of 470 communities over 10 months. Empirical contributions include new data showing: (a) which metrics are most useful for leaders to assess community health, (b) the need for and how to design actionable metrics, (c) the need for and how to design contextualized analytics to support sensemaking about community data. These findings motivate a novel community system that provides leaders with useful, actionable and contextualized analytics.

Online communities are important in enterprises, helping workers to build skills and collaborate. Despite their unique and critical role fostering successful communities, community leaders have little direct support in existing technologies. We introduce CommunityCompare, an interactive visual analytic system to enable leaders to make sense of their community's activity with comparisons. Composed of a parallel coordinates plot, various control widgets, and a preview of example posts from communities, the system supports comparisons with hundreds of related communities on multiple metrics and the ability to learn by example. We motivate and inform the system design with formative interviews of community leaders. From additional interviews, a field deployment, and surveys of leaders, we show how the system enabled leaders to assess community performance in the context of other comparable communities, learn about community dynamics through data exploration, and identify examples of top performing communities from which to learn. We conclude by discussing how our system and design lessons generalize.

Finding the right person to ask for help is a difficult task within a large enterprise. While there are a few studies detailing practices for finding an expert often in the context of an expertise locator system, there are fewer studies on workplace practices and challenges for finding a person who can help, especially independent of any particular technology. We conducted a two-part study of helper-finding activities with 36 enterprise workers, representing different job roles and levels of experience. First, we present a taxonomy of workplace helper-finding needs that involves tasks, topics, and helper selection criteria, developed by analyzing two weeks of participant diaries describing helper-finding problems. Second, we present the results of follow-up interviews with each participant, focusing on helper-finding challenges in the workplace. Finally, we present design implications for systems aimed at supporting helper-finding in the workplace.

Collaboration personas are a tool that can be used to design for groups. Prior work posits that collaboration personas can improve tool adoption by helping designers create collaboration tools that are better targeted to the goals, needs, and interactions between members of collaborative groups. We present a comparative study of design and user experience practitioners who used both collaboration personas and individual personas. Participants conducted a cognitive walkthrough and provided redesign suggestions for a collaboration tool. Our results show that the focus of the cognitive walkthrough and redesign task differed, with collaboration personas showing more group focus. Collaboration personas led to a more complete discussion, as indicated by a greater amount of time spent on the task compared to individual personas. Despite prior experience and training with individual personas, collaboration personas were preferred and better supported the task, since they focused on groups of people and their interactions.

Personas are a critical method for orienting design and development teams to user experience. Prior work has noted challenges in justifying them to developers. In contrast, it has been assumed that designers and user experience professionals - whose goal is to focus designs on targeted users - will readily exploit personas. This paper examines that assumption. We present the first study of how experienced user-centered design (UCD) practitioners with prior experience deploying personas, use and perceive personas in industrial software design. We identify limits to the persona approach in the context studied. Practitioners used personas almost exclusively for communication, but not for design. Participants identified four problems with personas, finding them abstract, impersonal, misleading and distracting. Our findings argue for a new approach to persona deployment and construction. Personas cannot replace immersion in actual user data. And rather than focusing on creating engaging personas, it is critical to avoid persona attributes that mislead or distract.

There is a growing body of research into the adoption and use of social software in enterprises. However, less is known about how groups, such as communities, use and appropriate these technologies, and the implications for community structures. In a study of 188 very active online enterprise communities, we found systematic differences in size, demographics and participation, aligned with differences in community types. Different types of communities differed in their appropriation of social software tools to create and use shared resources, and build relationships. We propose implications for design of community support features, services for potential community members, and organizations looking to derive value from online groups.

Expertise selection is the process of choosing an expert from a list of recommended people. This is an important and nuanced step in expertise location that has not received a great deal of attention. Through a lab-based, controlled investigation with 35 enterprise workers, we found that presenting additional information about each recommended person in a search result list led the participants to make quicker and better-informed selections. These results focus attention on a currently understudied aspect of expertise location--expertise selection--that could greatly improve the usefulness of supporting systems. We also asked participants to rate the type of information that might be most useful for expertise selection on a paper prototype containing 36 types of potentially helpful information. We identified sixteen types of this information that may be most useful for various expertise selection tasks.

New enterprise tools (wikis, team spaces, social tags) offer potential benefits for enterprise collaboration, providing shared resources to organize work. However, a vast amount of collaboration still takes place by email. But email is problematic for collaboration because information may be distributed across multiple messages in an overloaded inbox. Email also increases workload as each individual has to manage their own versions of collaborative materials. We present a novel system, Topika that integrates email with collaboration tools. It allows users to continue to use email while also enjoying the benefits of these dedicated tools. When a user composes an email Topika analyzes the message and suggests relevant shared spaces (e.g., wiki pages) within the user's collaboration tools. This allows her to post the email to those spaces. An evaluation of Topika's suggestion algorithm shows that it performs well at accurately suggesting shared spaces.

The success of social computing has generated a host of workplace collaboration tools. However, adoption of these tools by entire groups is a major problem. One reason for the adoption problem is a lack of methods for considering collaborative groups in technology design. Even when designing collaboration tools, designers often employ methods that focus on individuals. This leads to tools that are not well targeted at the groups who will use them. To solve this problem, we propose the notion of collaboration personas, which are empirically derived descriptions of hypothetical groups, including details that inform the design of collaboration tools. Collaboration personas differ from individual personas in having (1) multiple, inter-related individuals playing specific roles; (2) a focus on collective goals and elaboration of individual goals that affect the collective goal; and (3) new attributes that characterize collaborative aspects of the group's work. We contrast collaboration personas with other design approaches and provide examples of how they can be used to design new collaborative tools that better meet the needs of typical groups.

We all spend time every day looking for information in our email, yet we know little about this refinding process. Some users expend considerable preparatory effort creating complex folder structures to promote effective refinding. However modern email clients provide alternative opportunistic methods for access, such as search and threading, that promise to reduce the need to manually prepare. To compare these different refinding strategies, we instrumented a modern email client that supports search, folders, tagging and threading. We carried out a field study of 345 long-term users who conducted over 85,000 refinding actions. Our data support opportunistic access. People who create complex folders indeed rely on these for retrieval, but these preparatory behaviors are inefficient and do not improve retrieval success. In contrast, both search and threading promote more effective finding. We present design implications: current search-based clients ignore scrolling, the most prevalent refinding behavior, and threading approaches need to be extended.

In this paper we feature a set of research projects done at several IBM Research laboratories across the world. The work featured here focuses on the topic of smart social collaboration, which studies, designs, and develops social collaboration principles and technologies that can help customize and enhance existing social collaboration tools to suit specific user needs, including cultural, business, and personal needs.

Knowledge workers expend considerable effort managing fragmentation, characterized by constant switching among digital artifacts, when executing work activities. Activity-centric computing (ACC) systems attempt to address this problem by organizing activity-related artifacts together. But are ACC systems effective at reducing fragmentation? In this paper, we present a two-part study of workers using Lotus Activities, an ACC system deployed for over two years in a large company. First, we surveyed workers to understand the ecology of workplace tools they use for various tasks. Second, we interviewed 22 Lotus Activities users to investigate how this ACC tool fits amongst their ecology of existing collaboration tools and affects work fragmentation. Our results indicate that Lotus Activities works in concert with certain other tools to successfully ease fragmentation for a specific type of activity. We identify design characteristics that contribute to this result.

Modern enterprises are replete with numerous online processes. Many must be performed frequently and are tedious, while others are done less frequently yet are complex or hard to remember. We present interviews with knowledge workers that reveal a need for mechanisms to automate the execution of and to share knowledge about these processes. In response, we have developed the CoScripter system (formerly Koala [11]), a collaborative scripting environment for recording, automating, and sharing web-based processes. We have deployed CoScripter within a large corporation for more than 10 months. Through usage log analysis and interviews with users, we show that CoScripter has addressed many user automation and sharing needs, to the extent that more than 50 employees have voluntarily incorporated it into their work practice. We also present ways people have used CoScripter and general issues for tools that support automation and sharing of how-to knowledge.

Over the past decade and a half, corporations and academies have invested considerable time and money in the realization of ubiquitous computing. Yet design approaches that yield ecologically valid understandings of ubiquitous computing systems, which can help designers make design decisions based on how systems perform in the context of actual experience, remain rare. The central question underlying this article is, What barriers stand in the way of real-world, ecologically valid design for ubicomp? Using a literature survey and interviews with 28 developers, we illustrate how issues of sensing and scale cause ubicomp systems to resist iteration, prototype creation, and ecologically valid evaluation. In particular, we found that developers have difficulty creating prototypes that are both robust enough for realistic use and able to handle ambiguity and error and that they struggle to gather useful data from evaluations because critical events occur infrequently, because the level of use necessary to evaluate the system is difficult to maintain, or because the evaluation itself interferes with use of the system. We outline pitfalls for developers to avoid as well as practical solutions, and we draw on our results to outline research challenges for the future. Crucially, we do not argue for particular processes, sets of metrics, or intended outcomes, but rather we focus on prototyping tools and evaluation methods that support realistic use in realistic settings that can be selected according to the needs and goals of a particular developer or researcher.

Peripheral displays are an important class of ubiquitous computing applications. However, the field has suffered from a lack of clear, consistent terminology surrounding peripheral display research. We present an Activity Theory analysis of peripheral displays in order to establish common terminology and meaning for peripheral displays. We also present an Activity Theory-based approach for designing and evaluating peripheral displays

Peripheral displays are an important class of applications that improve our ability to multitask. Increased knowledge on how to design and evaluate glanceable peripheral displays can lead to better support for multitasking. We will contribute a set of guidelines for designing glanceable peripheral displays, using the wealth of abstraction techniques (e.g., change detection, feature extraction), design variables (e.g., color, shape), and design characteristics (e.g., dimensionality, symbolism) available. We will contribute an evaluation framework that clearly defines peripheral displays, metrics for evaluating their success, and guidelines for selecting evaluation methods. These contributions will improve peripheral displays that enable users to manage multiple tasks through low-effort monitoring.

Information workers often have to balance many tasks and interruptions. In this work, we explore peripheral display techniques that improve multitasking efficiency by helping users maintain task flow, know when to resume tasks, and more easily reacquire tasks. Specifically, we compare two types of abstraction that provide different task information: semantic content extraction, which displays only the most relevant content in a window, and change detection, which signals when a change has occurred in a window (all de-signed as modifications to Scalable Fabric [17]). Results from our user study suggest that semantic content extraction improves multitasking performance more so than either change detection or our base case of scaling. Results also show that semantic content extraction provides significant benefits to task flow, resumption timing, and reacquisition. We discuss the implication of these findings on the design of peripheral interfaces that support multitasking.

Sounds such as co-workers chatting nearby or a dripping faucet help us maintain awareness of and respond to our surroundings. Without a tool that communicates ambient sounds in a non-auditory manner, maintaining this awareness is difficult for people who are deaf. We present an iterative investigation of peripheral, visual displays of ambient sounds. Our major contributions are: (1) a rich understanding of what ambient sounds are useful to people who are deaf, (2) a set of visual and functional requirements for a peripheral sound display, based on feedback from people who are deaf, (3) lab-based evaluations investigating the characteristics of four prototypes, and (4) a set of design guidelines for successful ambient audio displays, based on a comparison of four implemented prototypes and user feedback. Our work provides valuable information about the sound awareness needs of the deaf and can help to inform further design of such applications.

Sounds constantly occur around us, keeping us aware of our surroundings. People who are deaf have difficulty maintaining an awareness of these ambient sounds. We present an investigation of peripheral, visual displays to help people who are deaf maintain an awareness of sounds in the environment. Our contribution is twofold. First, we present a set of visual design preferences and functional requirements for peripheral visualizations of non-speech audio that will help improve future applications. Visual design preferences include ease of interpretation, glance-ability, and appropriate distractions. Functional requirements include the ability to identify what sound occurred, view a history of displayed sounds, customize the information that is shown, and determine the accuracy of displayed information. Second, we designed, implemented, and evaluated two fully functioning prototypes that embody these preferences and requirements, serving as examples for future designers and furthering progress toward understanding how to best provide peripheral audio awareness for the deaf.

Advances in location-enhanced technology are making it easier for us to be located by others. These new technologies present a difficult privacy tradeoff, as disclosing one's location to another person or service could be risky, yet valuable. To explore whether and what users are willing to disclose about their location to social relations, we conducted a three-phased formative study. Our results show that the most important factors were who was requesting, why the requester wanted the participant's location, and what level of detail would be most useful to the requester. After determining these, participants were typically willing to disclose either the most useful detail or nothing about their location. From our findings, we reflect on the decision process for location disclosure. With these results, we hope to influence the design of future location-enhanced applications and services.

Traditionally, computer interfaces have been confined to conventional displays and focused activities. However, as displays become embedded throughout our environment and daily lives, increasing numbers of them must operate on the periphery of our attention. Peripheral displays can allow a person to be aware of information while she is attending to some other primary task or activity. We present the Peripheral Displays Toolkit (PTK), a toolkit that provides structured support for managing user attention in the development of peripheral displays. Our goal is to enable designers to explore different approaches to managing user attention. The PTK supports three issues specific to conveying information on the periphery of human attention. These issues are abstraction of raw input, rules for assigning notification levels to input, and transitions for updating a display when input arrives. Our contribution is the investigation of issues specific to attention in peripheral display design and a toolkit that encapsulates support for these issues. We describe our toolkit architecture and present five sample peripheral displays demonstrating our toolkit's capabilities.

This paper describes the visual analysis tool WebQuilt, a web usability logging and visualization system that helps web design teams record and analyze usability tests. The logging portion of WebQuilt unobtrusively gathers clickstream data as users complete specified tasks. This data is then aggregated and presented as an interactive graph, where nodes of the graph are images of the web pages visited, and arrows are the transitions between pages. To aid analysis of the gathered usability test data, the WebQuilt visualization provides filtering capabilities and semantic zooming, allowing the designer to understand the test results at the gestalt view of the entire graph, and then drill down to sub-paths and single pages. The visualization highlights important usability issues, such as pages where users spent a lot of time, pages where users get off track during the task, navigation patterns, and exit pages, all within the context of a specific task. WebQuilt is designed to conduct remote usability testing on a variety of Internet-enabled devices and provide a way to identify potential usability problems when the tester cannot be present to observe and record user actions.