Investigating individual differences in human-product interactions can improve the development of usable products for a diverse range of users. This study explores personality and cognitive ability as predictors of usability. A sample of 972 respondents took the Mini-IPIP measure of Big Five personality, a matrix reasoning test for cognitive ability, and the System Usability Scale (SUS) as an assessment of usability across seven commonly used products (Microsoft Word, Google, Amazon, computer, Microsoft Excel, TV remote, microwave). We ran a hierarchical regression analysis, predicting SUS score from demographic variables (gender, age), then individual differences (personality, cognitive ability). The personality traits of emotional stability and openness were statistically and practically significant predictors of SUS across every product, and gender and conscientiousness were significant predictors across many products. Results suggest that the subjective assessment of usability is not impacted by cognitive ability, and that personality traits are small-to-moderate, but consistent, predictors of SUS score.

The System Usability Scale (SUS) is a widely used instrument that measures the subjective usability of products and systems. Although past research has demonstrated the psychometric reliability and criterion-related validity of the SUS in specific languages, the approach and methodology of validating the translations has been somewhat inconsistent. This paper addresses this issue by systematically translating and validating the SUS across multiple languages. Native speakers of Arabic, Chinese, French, German, Hindi, and Spanish evaluated five common everyday products using the translated SUS. Evidence of consistent scale reliability and validity was found in the Chinese, French, German and Spanish SUS, with Cronbach’s alpha often greater than .80, as well as large statistically significant correlations between the SUS and a one-item adjective rating self-report of overall usability (r =.54-.74). Validity of the SUS across languages was also demonstrated by finding reliable differences in mean SUS scores between products. Overall, these translated SUS measures can be used with confidence in practice to measure the usability of everyday products and systems.

HTTPS and TLS are the backbone of Internet security, however setting up web servers to run these protocols is a notoriously difficult process. In this paper, we perform two live subjects usability studies on the deployment of HTTPS in a real-world setting. Study 1 is a within subjects comparison between traditional HTTPS configuration (purchasing a certificate and installing it on a server) and Let's Encrypt, which automates much of the process. Study 2 is a between subjects study looking at the same two systems, examining why users encounter usability issues. Overall we confirm past results that HTTPS is difficult to deploy, and we find some evidence that suggests Let's Encrypt is an easier, more efficient method for deploying HTTPS.

Marketing researchers use geography to identify specific user groups for studies to more effectively describe their potential customer base. Since usability professionals often recruit users employing similar selection criteria as their marketing peers, the use of geographic information might also be relevant when selecting usability test participants. In total, 3,168 participants from across the United States rated the usability of different hardware, software, and web-based products using the System Usability Scale (SUS). SUS scores were compared across geographic divisions to determine if usability assessments differ by location. SUS scores were also compared across rural and urban areas to determine if usability assessment scores change with population density. There was a lack of evidence to support significant differences in usability scores across both US geographic areas and zones of population density. The findings suggest that people make similar system usability assessments regardless of the area of the United States in which they live.

The system usability scale (SUS) has been widely employed in both the field and the laboratory as a valid and reliable measure of system usability. Although its psychometric properties are relatively well understood, the impact that differences in users’ personality traits have on their perceived usability of products, services, and systems has not been deeply explored—even though people’s scores on personality traits have been shown to be reliable and predict a staggering array of societally important outcomes in work, school, and life domains. In this study, 268 users assessed the usability of 20 different products retrospectively with the SUS. Five broad personality traits were then measured using the Mini-IPIP scale. Results indicated that measured personality traits do correlate with the rated usability of products, where measures of Openness to Experience and Agreeableness have the strongest positive correlations with subjective usability assessment. Implications for practitioners, designers, and researchers are discussed.

The use of applications on mobile devices has reached historic levels. Using the System Usability Scale (SUS), data were collected on the usability of applications used on two kinds of mobile platforms—phones and tablets—across two general classes of operating systems, iOS and Android. Over 4 experiments, 3,575 users rated the usability of 10 applications that had been selected based on their popularity, as well as 5 additional applications that users had identified as using frequently. The average SUS rating for the top 10 apps across all platforms was 77.7, with a nearly 20-point spread (67.7–87.4) between the highest and lowest rated apps. Overall, applications on phone platforms were judged to be more usable than applications on the tablet platforms. Practitioners can use the information in this article to make better design decisions and benchmark their progress against a known universe of apps for their specific mobile platform.

Context information brings new opportunities for efficient and effective applications and services on mobile devices. A wide range of research has exploited context dependency, i.e. the relations between context(s) and the outcome, to achieve significant, quantified, performance gains for a variety of applications and services. These works typically have to deal with the challenges of multiple context sources leading to a sparse training dataset, and the challenges of energy hungry context sensors. Often, they address these challenges in an application specific and ad-hoc manner. We liberate mobile application designers and researchers from these burdens by providing a methodical approach to these challenges. In particular, we 1) define and measure the context-dependency of three principal types of mobile usage (visited websites, phone calls, and app usage) in an application agnostic yet practical manner, providing insight into the performance of potential application. 2) Address the challenge of data sparseness when dealing with multiple context sources in a systematic manner. 3) Present SmartContext to address the energy challenge by automatically selecting among context sources while ensuring a minimum accuracy for each estimation. Our analysis and findings are based on one year of usage and context traces collected in real-life settings from 24 iPhone users. We present findings regarding the context dependency of three types of mobile usage from 24 users, yet our methodology and the lessons we learn can be readily extended to other types of usage as well as system resources. Our findings guide the development of context aware systems, and highlight the challenges and expectations regarding the context dependency of mobile usage.

This article examines the relationship between users’ subjective usability assessments, as measured using the System Usability Scale (SUS), and the ISO metric of effectiveness, using task success as the measure. The article reports the results of two studies designed to explore the relationship between SUS scores and user success rates for a variety of interfaces. The first study was a field study, where stereotypical usability assessments on a variety of products and services were performed. The second study was a well-controlled laboratory study where the level of success that users were able to achieve was controlled. For both studies, the relationship between SUS scores and their attendant performance were examined at both the individual level and the average system level. Although the correlations are far from perfect, there are reliable and reasonably strong positive correlations between subjective usability measures and task success rates, for both the laboratory and field studies at both the individual and system level.

Is it possible to migrate TCP/IP flows between different networks on modern mobile devices without infrastructure support or protocol changes? To answer this question, we make three research contributions: 1) We report a comprehensive characterization of IP traffic on 27 iPhone 3GS users for three months. 2) Driven by these findings, we devise two simple, effective, and easily deployable system mechanisms to support seamless flow migration without network support, and extensively evaluate their effectiveness using our field collected traces of real-life usage. Wait-n-Migrate leverages the fact that most flows are short lived. It establishes new flows on newly available networks but allows preexisting flows on the old network to terminate naturally. Resumption Agent takes advantage of the resumption functionality of modern protocols to securely resume flows without application intervention. Combined, they provide an unprecedented opportunity to immediately deploy policies that leverage multiple networks to improve the performance, efficiency, and connectivity of mobile devices. 3) We report an iPhone-based implementation of these system mechanisms and demonstrate their overhead to be negligible. Furthermore, we employ a sample switching policy, AutoSwitch, to demonstrate their performance. Through traces and field measurements, we show that AutoSwitch reduces user disruptions by an order of magnitude.

This article characterizes the usability of 14 common, everyday products using the System Usability Scale (SUS). More than 1,000 users were queried about the usability of these products using an online survey methodology. The study employed two novel applications of the SUS. First, participants were not asked to perform specific tasks on these products before rating their usability but were rather asked to assess usability based on their overall integrated experience with a given product. Second, some of the evaluated products were assessed as a class of products (e.g., “microwaves”) rather than a specific make and model, as is typically done. The results show clear distinctions among different products and will provide practitioners and researchers with important known benchmarks as they seek to characterize and describe results from their own usability studies.

The current paper establishes empirical patterns associated with mobile internet use on smartphones and explores user differences in these behaviors. We apply a naturalistic and longitudinal logs-based approach to collect real usage data from 24 iPhone users in the wild. These data are used to describe smartphone usage and analyze revisitation patterns of web browsers, native applications, and physical locations where phones are used. Among our findings are that web page revisitation through browsers occurred very infrequently (approximately 25% of URLs are revisited by each user), bookmarks were used sparingly, physical traversing patterns mirrored virtual (internet) traversing patterns and users systematically differed in their web use. We characterize these differences and suggest ways to support users with enhanced design of smartphone technologies and content.

Previous studies have found that smartphone users differ by orders of magnitude. We explore this variability to understand how users install and use native applications in ecologically-valid environments. A quasi-experimental approach is applied to compare how users in different socio-economic status (SES) groups adopt new smartphone technology along with how applications are installed and used. We present a longitudinal study of 34 iPhone 3GS users. 24 of these participants were chosen from two carefully selected SES groups who were otherwise similar and balanced. Usage data collected through an in-device programmable logger, as well as several structured interviews, identify similarities, differences, and trends, and highlight systematic differences in smartphone usage. A group of 10 lower SES participants were later recruited and confirm the influence of SES diversity on device usage. Among our findings are that a large number of applications were uninstalled, lower SES groups spent more money on applications and installed more applications overall, and the lowest SES group perceived the usability of their iPhones poorly in comparison to the other groups. We further discuss the primary reasons behind this low score, and suggest design implications to better support users across SES brackets.

The present report is an empirical analysis of smartphone personalisation. We collected data from two groups of users to measure how they adapt the content, interface and physical appearance of their devices. This user-driven personalisation is measured with a simple heuristic approach to quantify the behaviour. Using these scores, we explore how users differ from each other in how they personalise their smartphones with a focus on gender differences, usability and device usage in the wild. Among our findings are that not all users personalise their smartphones, females and males personalise their iPhones differently, and those who personalised their phones more tended to rate it as more usable. The users who personalised more also used their device for greater periods of time on a broader range of applications. For instance, individuals who adapted their iPhones to a greater degree also accessed the Web more often and spent more time browsing once it was accessed. We conclude with a discussion of possible factors underlying the large user diversity of smartphone personalisation found in this research.

This study investigated performance and preference differences for three different extensible Auditory Progress Bar (APB) designs. Four durations (30 s, 60 s, 120 s, 240 s) of the three APBs (Sine, Cello, and Electronic) were used in the study. There were 105 participants who listened to all durations of a single-stimulus type and were asked to determine the length of time they had listened to the stimulus and to rate the stimuli on aesthetic quality. Participants were significantly worse at time estimation with the Electronic APB. The Sine APB was preferred significantly less than either the Cello or Electronic APBs. Regardless of the stimulus, time estimation was more variable and more accurate as the duration of the APB increased. The results indicate that although they were originally envisioned as a supplement for the visual progress bar, APBs can be effective when used alone. Further, it was found that, even within the small design space presented here, APB design can influence the performance of listeners.

System voice within interactive voice response systems (IVRs) was investigated in order to determine if voice impacts a user’s input responses. In a medical setting, it is possible that a particular voice personality and/or gender may induce more or less disclosure, thus driving a patient to relay more or less sensitive information. In the IVR setting, one could determine this via examination of a user’s button-press responses. In this study, a male and female voice personality expressing an upbeat, professional, and sympathetic personality recorded a script for a medical IVR. Users were randomly assigned to one of these voice personalities when completing a health survey over that IVR. It was found that disclosure rates were not affected by the type of voice heard, nor did they differ by user gender. Additionally, disclosure was higher on the IVR version of the health survey than on a web-based version, further recognizing the privacy offered by IVRs. These findings indicate that designers of IVRs may not have to put additional effort into the selection of voice talent and can instead focus on the design of the IVR, itself.

This article presents nearly 10 year's worth of System Usability Scale (SUS) data collected on numerous products in all phases of the development lifecycle. The SUS, developed by CitationBrooke (1996), reflected a strong need in the usability community for a tool that could quickly and easily collect a user's subjective rating of a product's usability. The data in this study indicate that the SUS fulfills that need. Results from the analysis of this large number of SUS scores show that the SUS is a highly robust and versatile tool for usability professionals. The article presents these results and discusses their implications, describes nontraditional uses of the SUS, explains a proposed modification to the SUS to provide an adjective rating that correlates with a given score, and provides details of what constitutes an acceptable SUS score.