This 10-year systematic review examines the impact of game-based interventions (GBI) on adult cognition, covering game-based learning and training, serious games, gamification, and exergames. The research followed PRISMA guidelines and Cochrane recommendations for bias assessment. We reviewed 1,398 articles and selected 42 studies (26 randomized trials, 16 non-randomized). Our findings highlight the influence of contextual factors on GBI, such as culture and individual traits. We emphasize the predominance of digital over analog applications, reflecting GBI’s connection to Human-Computer Interaction (HCI). This review underscores GBI’s interdisciplinary nature and the need for high-quality research standards. We examined 23 outcome categories and found positive effects in areas like Satisfaction, Flow, Learning, Motivation, and Perception, though with varying bias risks. On average, GBI designs incorporated nine game elements. Most interventions used Puzzle and Simulation genres, were single-player, 2D, and computer-based. Innovations in neurophysiological tools, movement monitoring, and virtual reality offer promising HCI research avenues.

Understanding which factors affect information visualization transparency continues to be one of the most relevant challenges in current research, especially since trust models how users build on the knowledge and use it. This work extends the current body of research by studying the user’s subjective evaluation of the visualization transparency of hierarchical charts through the clarity, coverage, and look and feel dimensions. Additionally, we extend the user profile to better understand whether personality facets manifest a biasing effect on the trust-building process. Our results show that the data encodings do not affect how users perceive visualization transparency while controlling for personality factors. Regarding personality, the propensity to trust affects how they judge the clarity of a hierarchical chart. Our findings provide new insights into the research challenges of measuring trust and understanding the transparency of information visualization. Specifically, we explore how personality factors manifest in this trust-building relationship and user interaction within visualization systems.

Incidental visualizations convey information to a person during an ongoing primary task, without the person consciously searching for or requesting that information. They differ from glanceable visualizations by not being people’s main focus, and from ambient visualizations by not being embedded in the environment. Instead, they are presented as secondary information that can be observed without a person losing focus on their current task. However, despite extensive research on glanceable and ambient visualizations, the topic of incidental visualizations is yet a novel topic in current research. To bridge this gap, we conducted an empirical user study presenting participants with an incidental visualization while performing a primary task. We aimed to understand how complexity contributory factors — task complexity, output complexity, and pressure — affected primary task performance and incidental visualization accuracy. Our findings showed that incidental visualizations effectively conveyed information without disrupting the primary task, but working memory limitations should be considered. Additionally, output and pressure significantly influenced the primary task’s results. In conclusion, our study provides insights into the perception accuracy and performance impact of incidental visualizations in relation to complexity factors.

In InfoVis design, visualizations make use of pre-attentive features to highlight visual artifacts and guide users' perception into relevant information during primitive visual tasks. These are supported by visual marks such as dots, lines, and areas. However, research assumes our pre-attentive processing only allows us to detect specific features in charts. We argue that a visualization can be completely perceived pre-attentively and still convey relevant information. In this work, by combining cognitive perception and psychophysics, we executed a user study with six primitive visual tasks to verify if they could be performed pre-attentively. The tasks were to find: horizontal and vertical positions, length and slope of lines, size of areas, and color luminance intensity. Users were presented with very simple visualizations, with one encoded value at a time, allowing us to assess the accuracy and response time. Our results showed that horizontal position identification is the most accurate and fastest task to do, and the color luminance intensity identification task is the worst. We believe our study is the first step into a fresh field called Incidental Visualizations, where visualizations are meant to be seen at-a-glance, and with little effort.

This paper discusses how quizzes are applied within the field of software engineering learning and how quizzes can help self-regulate student learning. For this, a systematic mapping that selected the most relevant studies on the use of quizzes in education was performed, aiming to clarify their relationships and mutual impacts. Our analysis shows that student engagement and quiz work is a prominent learning solution for increasing motivation in and out of the classroom. We found that quizzes can be applied in software engineering and through generic quizzes, online Quizzes, pop-Quizzes, gamified Quizzes, in quiz games or, alternatively, as an exercise in creating quizzes. However, we did not find approaches to the use of quizzes, explicitly containing Zimmerman's cyclic model, only some of the model's activities in isolation and not explicitly. We argue that sharing the quizzes will raise the potential for then to be use as a self-regulation tool in software engineering education. We describe the steps taken by a Software Engineering Gamification project to create a effective tool for creating and sharing software engineering quizzes. Our next requirement to be implemented in the project will be the application of self-regulation of learning containing the three phases of the Zimermman cyclic model.

Ten years ago, Thaler and Sunstein introduced the notion of nudging to talk about how subtle changes in the 'choice architecture' can alter people's behaviors in predictable ways. This idea was eagerly adopted in HCI and applied in multiple contexts, including health, sustainability and privacy. Despite this, we still lack an understanding of how to design effective technology-mediated nudges. In this paper we present a systematic review of the use of nudging in HCI research with the goal of laying out the design space of technology-mediated nudging - the why (i.e., which cognitive biases do nudges combat) and the how (i.e., what exact mechanisms do nudges employ to incur behavior change). All in all, we found 23 distinct mechanisms of nudging, grouped in 6 categories, and leveraging 15 different cognitive biases. We present these as a framework for technology-mediated nudging, and discuss the factors shaping nudges' effectiveness and their ethical implications.

A fundamental step in medical diagnosis for patient follow-up relies on the ability of radiologists to perform a trusty diagnostic from acquired images. Basically, the diagnosis strongly depends on the visual inspection over the shape of the lesions. As datasets increase in size, such visual evaluation becomes harder. For this reason, it is crucial to introduce easy-to-use interfaces that help the radiologists to perform a reliable visual inspection and allow the efficient delineation of the lesions. We will explore the radiologist's receptivity to the current touch environment solution. The advantages of touch are threefold: (i) the time performance is superior regarding the traditional use, (ii) it has more intuitive control and, (iii) for less time, the user interface delivers more information per action, concerning annotations. From our studies, we conclude that the radiologists still exhibit a resistance to change from traditional to touch based interfaces in current clinical setups.

In this demo paper we describe PlaylistCreator, an assisted approach for supporting the creation of music playlists. Our solution allows creators to express song selection and browsing through a visual representation of their intents in a unified view, which relies on a set-based model for representing sources of songs. Creators can convey their purposes by seamlessly combining criteria for song selection from either manual or automatic sources, such as artists and albums, or similarity measures between artists or songs.

Blind people rely mostly on the auditory feedback of screen readers to consume digital information. Still, how fast can information be processed remains a major problem. The use of faster speech rates is one of the main techniques to speed-up the consumption of digital information. Moreover, recent experiments have suggested the use of concurrent speech as a valid alternative when scanning for relevant information. In this paper, we present an experiment with 30 visually impaired participants, where we compare the use of faster speech rates against the use of concurrent speech. Moreover, we combine these two approaches by gradually increasing the speech rate with one, two and three voices. Results show that concurrent voices with speech rates slightly faster than the default rate, enable a significantly faster scanning for relevant content, while maintaining its comprehension. In contrast, to keep-up with concurrent speech timings, One-Voice requires larger speech rate increments, which cause a considerable loss in performance. Overall, results suggest that the best compromise between efficiency and the ability to understand each sentence is the use of Two-Voices with a rate of 1.75*default-rate (approximately 278 WPM).

Tablet devices can display full-size QWERTY keyboards similar to the physical ones. Yet, the lack of tactile feedback and the inability to rest the fingers on the home keys result in a highly demanding and slow exploration task for blind users. We present SpatialTouch, an input system that leverages previous experience with physical QWERTY keyboards, by supporting two-handed interaction through multitouch exploration and spatial, simultaneous audio feedback. We conducted a user study, with 30 novice touchscreen participants entering text under one of two conditions: (1) SpatialTouch or (2) mainstream accessibility method Explore by Touch. We show that SpatialTouch enables blind users to leverage previous experience as they do a better use of home keys and perform more efficient exploration paths. Results suggest that although SpatialTouch did not result in faster input rates overall, it was indeed able to leverage previous QWERTY experience in contrast to Explore by Touch.

Over the years, screen readers have been an essential tool for assisting blind users in accessing digital information. Yet, its sequential nature undermines blind people's ability to efficiently find relevant information, despite the browsing strategies they have developed. We propose taking advantage of the Cocktail Party Effect, which states that people are able to focus on a single speech source among several conversations, but still identify relevant content in the background. Therefore, oppositely to one sequential speech channel, we hypothesize that blind people can leverage concurrent speech channels to quickly get the gist of digital information. In this paper, we present an experiment with 23 participants, which aims to understand blind people's ability to search for relevant content listening to two, three or four concurrent speech channels. Our results suggest that it is easy to identify the relevant source with two and three concurrent talkers. Moreover, both two and three sources may be used to understand the relevant source content depending on the task intelligibility demands and user characteristics.

Visualization is a powerful way to convey data, showing potential for joining and interrelating data items. However, when dealing with large amounts of data, visually merging different classes of information poses several challenges. Color, however, due to its effectiveness for labeling and categorizing information, may be a solution to this shortcoming. Merging items with different colors may suggest mixing their original colors. This approach generates an immediately perceivable way to represent merged items. It also keeps context through the association of the mixed color to its original colors. We studied to which extent color blending provides users with the means to understand the provenience of data items by conducting two user studies using CIE-LCh, CMYK and HSV blending to ascertain (i) to which extent people are able to, given a particular color, understand its provenience, and (ii) the color model in which to perform color blending so that users find it intuitive. Results showed colors which are more suitable for blending so that users understand their provenience and indicated that the CIE-LCh model is more effective for representing color blending.

Nowadays, electronic devices are part of our daily routines, resulting in information generation at virtually any time and context. Due to different styles of interaction, data produced by human activities is not only in considerable quantities, but it is also extremely rich, which makes it difficult to manage and analyze. Visualization has the potential to overcome this limitation: not only is it an excellent means to display large quantities of information, but it also alleviates cognitive load associated with data interpretation. We created an interactive multi-level layered visualization, in which time may be represented sequentially through layers. Data entities are displayed as circles with size proportional to a particular data feature we need to highlight, allowing immediate comparison between entities. By selecting an entity, we may see, through visual connectors, all the interrelated entities over the different time layers. User tests have shown that our visualization makes important information immediately perceivable, in a way that is easy to navigate and analyze.

In this paper, we describe a tool to visualize and explore communities of politicians arising from mentions in news articles, combining techniques from network analysis and visual analytics. With this tool one can explore the communities, their organization according to parties, with whom a politician was mentioned with in a given year, or key political events, like the emergence of a new prime-minister. User tests involving our tool, and a collection of Portuguese news articles for a period of 10 years, have shown the interest on this kind of tool, and its applicability to analyze group evolution.

Providing the educational community with tools to analyze educational processes may result in a more effective education. Applying Data Mining techniques to educational data results in information on educational settings which, however, comprehend an extensive set of symbolic patterns that are usually difficult to understand. Visualization, due to its potential to display large quantities of data, may overcome this limitation. We used the results of educational data mining techniques that had been applied to analyze the interdependence among courses in a university program and studied visualization mechanisms to enable the analysis of such patterns. We created a multi-level visualization, in which each level depicts a semester with corresponding courses. We have studied visual connectors to display a high number of interrelations between courses. User tests have shown the effectiveness of a connector which combines visual merging techniques with Bezier curves to represent course interrelation.

Wikipedia articles see bursts of update activity whenever a topic is of more interest to the community or has somehow become controversial. Analyzing when and what changes are made can, thus, give us an idea of how the community feels about particular subjects. In this paper we present Pop Culture, a system that provides a visualization of Wikipedia's edits that allows us to reflect on how different subjects are perceived by people over time and, by comparing articles from different language wikipedias, find regional and cultural differences of interest and perception. A set of user studies shows that, indeed, users are able to use Pop Culture effectively and efficiently to find such trends and differences.

Despite the overwhelming emergence of accessible digital technologies, Braille still plays a role in providing blind people with access to content. Nevertheless, many fail to see the benefits of nurturing Braille, particularly given the time and effort required to achieve proficiency. Our research focuses on maximizing access and motivation to learn and use Braille. We present initial insights from 5 interviews with blind people, comprising of Braille instructors and students, where we characterize the learning process and usage of Braille. Based on our findings, we have identified a set of opportunities around Braille education. Moreover, we devised scenarios, and built hardware and software solutions to motivate discovery and retention of Braille literacy.

In this paper we present AppInsight, a visualization tool that enables users to reminisce on their computer usage history and derive meaningful insights about behaviors and trends. Human memory has the ability to re-experience episodes from our lives when supplied with suitable contextual cues, such as places, music, and so on. We explore a small set of properties, such as the application's name, URL and window title as contextual cues, in order to characterize the users' activity on their personal computers and how it evolves over time. Our user study shows that users enjoyed viewing their computer usage history and were able to both recall past events and introspect about their lives. Moreover, one of the most surprising outcomes is that they found several different applications for our tool, such as improving usage behaviors, controlling productivity, generating activity reports, and monitoring users in psychological studies. Finally, we discuss some lessons learned from our study and propose future research directions.

Over the past years, music listening histories have become easily accessible due to the expansion of online lifelogging services. These histories represent the sequence of songs listen by users over time. Although this data contains intrinsic users' tastes and listening behaviors, it has been mainly used to personalize recommendations. Tools to help users exploring and reasoning about the information contained in the listening history, only recently have started to emerge. In this paper we describe a new visualization and exploration tool that allows users to interactively browse their listening histories, while leading them to identify listening trends and habits. Our solution combines a rich-featured timeline-based visualization, a set of synchronized-views and an interactive filtering mechanism to provide a flexible, effective and easy to use system for the analysis and knowledge exploration of listening histories. This was complemented with brushing and highlighting techniques to uncover listening trends about artists, albums and songs. Experimental evaluation with users revealed that they were able to complete all the requested tasks with a low error rate, and that they found the solution flexible and easy to use. Additionally, users were able to infer about their main life events and listening changes, which indicates that our combination of visualization techniques is effective in conveying relevant information about the listening habits.

One of the most frequently used ways to communicate with others is email. We have created "Who Have I Been Talking To?", a visualization of the users' email that can provide insights about their relationships with others how one relation has evolved over time (reflected by the number of messages exchanged); the nature of the relationship (comparing the subjects of messages and how asymmetric is the ratio between sent and received email); and allowing users to compare their relationships with different people. We found that a variant of a stacked bar chart over an interactive timeline allowed all of those goals to be achieved. User studies showed that the users were able to understand the visualization and gain meaningful insights about their electronic communications with others.

Our Personal Information is now scattered among several applications and personal devices in an unrelated, but still connected, information network. We have never had so much information at our disposal as we have now, giving us the opportunities to find information about other people, a very frequent need. While previous works have proposed several solutions to relate data from multiple sources that does not happen at the presentation level. When needing information about people, we still have to navigate among sources to find it. Besides troublesome, it is difficult to have an overall characterization of what each person represents to us. We argue that gathering information from all these sources and presenting it in a unified interface benefits the user by providing a quick and meaningful overview of who that person is and how he/she is related to him/her. We present Visualiz'em, a personal visualization tool based on three interconnected views: Profile, Tagcloud and Timeline. When compared to traditional applications Visualiz'em provides a faster and richer overview of whom a person is and his/her relationship with the user. Moreover, results show that our visualization tool promotes serendipitous behaviors, allowing users to easily explore data and find interaction patterns.

Nowadays, a hitherto unseen amount of information can be found in the World Wide Web. While available, this information is fragmented among different web sites. This is especially true for implicit knowledge, not directly written in any one site, but arising from patterns and interactions between pages. For instance, the number of search results for a particular query string might be a meaningful indicator of its popularity or overall interest. Our research focuses on the design of an interface that allows end-users to access implicit information. A prototype application, Metabrain, embodies our solutions and makes it possible to mine the web for statistically relevant patterns, with the help of simple and straightforward algorithms and user interface. To help the users make sense of that information, Metabrain then allows custom visualizations to be crafted. User studies show that users can search for relevant information up to four times faster than using traditional Web search engines alone. A system usability scale questionnaire confirms the interface is usable and effective.

Nowadays, people spend time using services to track their music listening history. Although these services provide statistics and small graphics/charts, they are mainly used to record and to allow direct access to the information, not providing any visualization and exploration functionality. In this paper we describe a new approach for browsing and visualizing music listening histories, which combines a timeline-based visualization, with a set of synchronized-views and an interactive filtering mechanism to provide a flexible and easy to use solution. This was complemented with brushing and highlighting techniques that allow users to observe trends on artists, albums and tracks listening. Experimental evaluation with users revealed that they were able to complete all the proposed tasks with a low error rate, and that they found the solution easy to use. Moreover, users liked our approach for browsing and exploring listening histories, emphasizing its flexibility and effectiveness, and founding the full experience engaging and rewarding.

The emergence of touch-based mobile devices brought fresh and exciting possibilities. These came at the cost of a considerable number of novel challenges. They are particularly apparent with the blind population, as these devices lack tactile cues and are extremely visually demanding. Existing solutions resort to assistive screen reading software to compensate the lack of sight, still not all the information reaches the blind user. Good spatial ability is still required to have notion of the device and its interface, as well as the need to memorize buttons' position on screen. These abilities, as many other individual attributes as age, age of blindness onset or tactile sensibility are often forgotten, as the blind population is presented with the same methods ignoring capabilities and needs. Herein, we present a study with 13 blind people consisting of a touch screen text-entry task with four different methods. Results show that different capability levels have significant impact on performance and that this impact is related with the different methods' demands. These variances acknowledge the need of accounting for individual characteristics and giving space for difference, towards inclusive design.

Touch screen mobile devices bear the promise of endless leisure, communication, and productivity opportunities to motor-impaired people. Indeed, users with residual capacities in their upper extremities could benefit immensely from a device with no demands regarding strength. However, the precision required to effectively select a target without physical cues creates problems to people with limited motor abilities. Our goal is to thoroughly study mobile touch screen interfaces, their characteristics and parameterizations, thus providing the tools for informed interface design for motor-impaired users. We present an evaluation performed with 15 tetraplegic people that allowed us to understand the factors limiting user performance within a comprehensive set of interaction techniques (Tapping, Crossing, Exiting and Directional Gesturing) and parameterizations (Position, Size and Direction). Our results show that for each technique, accuracy and precision vary across different areas of the screen and directions, in a way that is directly dependent on target size. Overall, Tapping was both the preferred technique and among the most effective. This proves that it is possible to design inclusive unified interfaces for motor-impaired and able-bodied users once the correct parameterization or adaptability is assured.

Mobile devices are designed mostly to fit users with no particular disability. Tactile affordances are neglected at the expense of more attractive stylish interfaces and assistive solutions are stereotypical, also facing disabilities with a narrow perspective. A blind user is presented with screen reading software to overcome the inability to receive feedback from the device. However, these solutions go only half-way. In the absence of sight other capabilities stand up. Above all, the sense of touch plays an essential role while interacting with physical keypads. To empower these users, a deeper understanding of their capabilities and how they relate with technology is mandatory. We propose a user-product compatibility approach, taking in account that blind users have different tactile attributes. We expect to correlate the user's tactile sensitivity and keypad demands, enabling informed keypad design and selection.

The proliferation of personal devices and their constant awareness of our interactions have generated an enormous amount of data that can be useful to help the user obtaining relevant information when needed. Our approach uses the personal information on users' devices, together with public online sources, to provide relevant information from the user point of view. The information from the users' devices, due to its personal and credible character, works as a filter to the retrieved from other less trustable and structured sources. A preliminary evaluation, suggested that we can provide the user with inter-connected relevant information from heterogeneous sources. However, we found some limitations that led us to our current research challenges.

Mobile touch-screen interfaces and tetraplegic people have a controversial connection. While users with residual capacities in their upper extremities could benefit immensely from a device which does not require strength to operate, the precision needed to effectively select a target bars these people access to countless communication, leisure and productivity opportunities. Insightful projects attempted to bridge this gap via either special hardware or particular interface tweaks. Still, we need further insight into the challenges and the frontiers separating failure from success for such applications to take hold. This paper discusses an evaluation conducted with 15 tetraplegic people to learn the limits to their performance within a comprehensive set of interaction methods. We then present the results concerning a particular interaction technique: Tapping. Results show that performance varies across different areas of the screen whose distribution changes with target size.

NavTap is a navigational method that enables blind users to input text in a mobile device by reducing the associated cognitive load.

With the growing popularity of digital cameras, the organization, browsing, management and grouping of photos become a problem of every photograph (professional or amateur), because their collections easily achieve the order of thousands. Here, we present a system to automate these processes, which relies on photo information, such as, semantic features (extracted from content), meta-information and low level.

Most computer users find organizing large amounts of personal information problematic. Often, hierarchies are the sole means to do it. However, users can remember a broader range of autobiographic contextual data about their personal items. Unfortunately, it can seldom be used to manage and retrieve them. Even when this is possible, it is often done by asking users to fill in values for arbitrary properties in dialog boxes or wizards.

Traditional ways to help users organize and retrieve their documents don't scale well, nor do they properly handle non-textual documents. This paper evaluates narrative-based interfaces as a natural and effective alternative for document retrieval. We have identified what shape document-describing stories take, and what contents to expect. This led to an interface that is able to capture stories, and a knowledge-based infrastructure to understand them. A prototype of the interface was used to validate narrative-based interfaces, with emphasis on story accuracy. To this end, we collected thirty stories whose contents were then compared to the documents they portrayed. Results allow us to conclude that, for the most part, such stories are trustworthy enough to allow humans to retrieve documents reliably (81%-91% of all information is correct). We also confirmed that stories told to a computer are similar to those told to human interviewers.

With the increasing number of computers per user, it has become common for most users to deal with growing numbers of electronic documents. Those documents are usually stored in hierarchic file systems, requiring them to be classified into the hierarchy, a difficult task. Such organization schemes do not provide adequate support for the efficient and effortless retrieval of documents at a later time, since their position in the hierarchy is one of the only clues to a document's whereabouts. However, humans are natural-born storytellers, and stories help relate and remember important pieces of information. Hence, the usage of narratives where a user "tells a story" about the document will be a valuable tool towards simplifying the retrieval task.To find out if there are common patterns in stories about documents, we performed a study where 60 such stories were collected and analyzed. We identified the most common story elements (time, storage and purpose) and how they are likely to relate in typical stories. This preliminary study suggests that it is possible to infer archetypical stories. Further, we present a set of guidelines for the design of narrative-based document retrieval interfaces.