Katharina Reinecke

Improving performance, perceived usability, and aesthetics with culturally adaptive user interfaces

When we investigate the usability and aesthetics of user interfaces, we rarely take into account that what users perceive as beautiful and usable strongly depends on their cultural background. In this paper, we argue that it is not feasible to design one interface that appeals to all users of an increasingly global audience. Instead, we propose to design culturally adaptive systems, which automatically generate personalized interfaces that correspond to cultural preferences. In an evaluation of one such system, we demonstrate that a majority of international participants preferred their personalized versions over a nonadapted interface of the same Website. Results show that users were 22% faster using the culturally adapted interface, needed fewer clicks, and made fewer errors, in line with subjective results demonstrating that they found the adapted version significantly easier to use. Our findings show that interfaces that adapt to cultural preferences can immensely increase the user experience.

Demographic differences in how students navigate through MOOCs

The current generation of Massive Open Online Courses (MOOCs) attract a diverse student audience from all age groups and over 196 countries around the world. Researchers, educators, and the general public have recently become interested in how the learning experience in MOOCs differs from that in traditional courses. A major component of the learning experience is how students navigate through course content. This paper presents an empirical study of how students navigate through MOOCs, and is, to our knowledge, the first to investigate how navigation strategies differ by demographics such as age and country of origin. We performed data analysis on the activities of 140,546 students in four edX MOOCs and found that certificate earners skip on average 22% of the course content, that they frequently employ non-linear navigation by jumping backward to earlier lecture sequences, and that older students and those from countries with lower student-teacher ratios are more comprehensive and non-linear when navigating through the course. From these findings, we suggest design recommendations such as for MOOC platforms to develop more detailed forms of certification that incentivize students to deeply engage with the content rather than just doing the minimum necessary to earn a passing grade. Finally, to enable other researchers to reproduce and build upon our findings, we have made our data set and analysis scripts publicly available.

Predicting users' first impressions of website aesthetics with a quantification of perceived visual complexity and colorfulness

Users make lasting judgments about a websites appeal within a split second of seeing it for the first time. This first impression is influential enough to later affect their opinions of a sites usability and trustworthiness. In this paper, we demonstrate a means to predict the initial impression of aesthetics based on perceptual models of a websites colorfulness and visual complexity. In an online study, we collected ratings of colorfulness, visual complexity, and visual appeal of a set of 450 websites from 548 volunteers. Based on these data, we developed computational models that accurately measure the perceived visual complexity and colorfulness of website screenshots. In combination with demographic variables such as a users education level and age, these models explain approximately half of the variance in the ratings of aesthetic appeal given after viewing a website for 500ms only.

Knowing what a user likes: a design science approach to interfaces that automatically adapt to culture

Adapting user interfaces to a users cultural background can increase satisfaction, revenue, and market share. Conventional approaches to catering for culture are restricted to adaptations for specific countries and modify only a limited number of interface components, such as the language or date and time formats. We argue that a more comprehensive personalization of interfaces to cultural background is needed to appeal to users in expanding markets. This paper introduces a low-cost, yet efficient method to achieve this goal: cultural adaptivity. Culturally adaptive interfaces are able to adapt their look and feel to suit visual preferences. In a design science approach, we have developed a number of artifacts that support cultural adaptivity, including a prototype web application. We evaluate the efficacy of the prototypes automatically generated interfaces by comparing them with the preferred interfaces of 105 Rwandan, Swiss, Thai, and multicultural users. The findings demonstrate the feasibility of providing users with interfaces that correspond to their cultural preferences in a novel yet effective manner.

Doodle around the world: online scheduling behavior reflects cultural differences in time perception and group decision-making

Event scheduling is a group decision-making process in which social dynamics influence peoples choices and the overall outcome. As a result, scheduling is not simply a matter of finding a mutually agreeable time, but a process that is shaped by social norms and values, which can highly vary between countries. To investigate the influence of national culture on peoples scheduling behavior we analyzed more than 1.5 million Doodle date/time polls from 211 countries. We found strong correlations between characteristics of national culture and several behavioral phenomena, such as that poll participants from collectivist countries respond earlier, agree to fewer options but find more consensus than predominantly individualist societies. Our study provides empirical evidence of behavioral differences in group decision-making and time perception with implications for cross-cultural collaborative work.

Culturally adaptive software: moving beyond internationalization

So far, culture has played a minor role in the design of software. Our experience with imbuto, a program designed for Rwandan agricultural advisors, has shown that cultural adaptation increased efficiency, but was extremely time-consuming and, thus, prohibitively expensive. In order to bridge the gap between cost-savings on one hand, and international usability on the other, this paper promotes the idea of culturally adaptive software. In contrast to manual localization, adaptive software is able to acquire details about an individuals cultural identity during use. Combining insights from the related fields international usability, user modeling and user interface adaptation, we show how research findings can be exploited for an integrated approach to automatically adapt software to the users cultural frame.

Choice Architecture for Human-Computer Interaction

People in human–computer interaction have learned a great deal abouthow to persuade and influence users of computing technology. Theyhave much less well-founded knowledge about how to help users choosefor themselves. Its time to correct this imbalance. A first step is toorganize the vast amount of relevant knowledge that has been builtup in psychology and related fields in terms of two comprehensive buteasy-to-remember models: The ASPECT model answers the question“How do people make choices?“ by describing six choice patterns thatchoosers apply alternately or in combination, based on Attributes, Socialinfluence, Policies, Experience, Consequences, and Trial and error.The ARCADE model answers the question “How can we help peoplemake better choices?“ by describing six general high-level strategies forsupporting choice: Access information and experience, Represent thechoice situation, Combine and compute, Advise about processing, Designthe domain, and Evaluate on behalf of the chooser. These strategiescan be implemented with straightforward interaction design, butfor each one there are also specifically relevant technologies. Combiningthese two models, we can understand virtually all existing and possibleapproaches to choice support as the application of one or more of theARCADE strategies to one or more of the ASPECT choice patterns.After introducing the idea of choice architecture for human–computerinteraction and the key ideas of the ASPECT and ARCADEmodels, we discuss each of the Aspect patterns in detail and show howthe high-level ARCADE strategies can be applied to it to yield specifictactics. We then apply the two models in the domains of online communitiesand privacy. Most of our examples concern choices about theuse of computing technology, but the models are equally applicable toeveryday choices made with the help of computing technology.

Tell Me Where You've Lived, and I'll Tell You What You Like: Adapting Interfaces to Cultural Preferences

Adapting user interfaces to cultural preferences has been shown to improve a users performance, but is oftentimes foregone because of its time-consuming and costly procedure. Moreover, it is usually limited to producing one uniform user interface (UI) for each nation disregarding the intangible nature of cultural backgrounds. To overcome these problems, we exemplify a new approach with our culturally adaptive web application MOCCA, which is able to map information in a cultural user model onto adaptation rules in order to create personalized UIs. Apart from introducing the adaptation flexibility of MOCCA, the paper describes a study with 30 participants in which we compared UI preferences to MOCCAs automatically generated UIs. Results confirm that automatically predicting cultural UI preferences is possible, paving the way for low-cost cultural UI adaptations.

Predicting user interface preferences of culturally ambiguous users

To date, localized user interfaces are still being adapted to one nation, not taking into account cultural ambiguities of people within this nation. We have developed an approach to cultural user modeling, which allows to personalize user interfaces to an individuals cultural background. The study presented in this paper shows how we use this approach to predict user interface preferences. Results show that we are able to reduce the absolute error on this prediction to 1.079 on a rating scale of 5. These findings suggest that it is possible to automate the process of localization and, thus, to automatically personalizing user interfaces for users of different cultural backgrounds.

Enabling Designers to Foresee Which Colors Users Cannot See

Users frequently experience situations in which their ability to differentiate screen colors is affected by a diversity of situations, such as when bright sunlight causes glare, or when monitors are dimly lit. However, designers currently have no way of choosing colors that will be differentiable by users of various demographic backgrounds and abilities and in the wide range of situations where their designs may be viewed. Our goal is to provide designers with insight into the effect of real-world situational lighting conditions on peoples ability to differentiate colors in applications and imagery. We therefore developed an online color differentiation test that includes a survey of situational lighting conditions, verified our test in a lab study, and deployed it in an online environment where we collected data from around 30,000 participants. We then created ColorCheck, an image-processing tool that shows designers the proportion of the population they include (or exclude) by their color choices.