Showing papers in "ACM Transactions on Computer-Human Interaction in 2017"
TL;DR: In this paper, a model that includes new operators for defining rules combining multiple events and conditions exposed by smart objects, and for defining temporal and spatial constraints on rule activation is introduced to enable non-technical users to be directly involved in composing their smart objects by synchronizing their behavior.
Abstract: Research on the Internet of Things (IoT) has devoted many efforts to technological aspects. Little social and practical benefits have emerged so far. IoT devices, so-called smart objects, are becoming even more pervasive and social, leading to the need to provide non-technical users with innovative interaction strategies for controlling their behavior. In other words, the opportunities offered by IoT can be amplified if new approaches are conceived to enable non-technical users to be directly involved in “composing” their smart objects by synchronizing their behavior. To fulfill this goal, this article introduces a model that includes new operators for defining rules combining multiple events and conditions exposed by smart objects, and for defining temporal and spatial constraints on rule activation. The article also presents the results of an elicitation study that was conducted to identify possible visual paradigms for expressing composition rules. Prototypes implementing the resulting visual paradigms were compared during a controlled experiment and the one that resulted most relevant for our goals was used in a study that involved home-automation experts. Finally, the article discusses some design implications that came out from the performed studies and presents the architecture of a platform supporting rule definition and execution.
168 citations
TL;DR: This study reviews 37 papers in the overlap between TAM and UX models and discusses four of the main theories used in reasoning about the experiential component and point to the near absence of psychological needs and negative emotions in the models.
Abstract: Understanding the mechanisms that shape the adoption and use of information technology is central to human--computer interaction. Two accounts are particularly vocal about these mechanisms, namely the technology acceptance model (TAM) and work on user experience (UX) models. In this study, we review 37 papers in the overlap between TAM and UX models to explore the experiential component of human--computer interactions. The models provide rich insights about what constructs influence the experiential component of human--computer interactions and about how these constructs are related. For example, the effect of perceived enjoyment on attitude is stronger than those of perceived usefulness and perceived ease of use. It is less clear why the relations exist and under which conditions the models apply. We discuss four of the main theories used in reasoning about the experiential component and, for example, point to the near absence of psychological needs and negative emotions in the models. In addition, most of the reviewed studies are not tied to specific use episodes, thereby bypassing tasks as an explanatory variable and undermining the accurate measurement of experiences, which are susceptible to moment-to-moment changes. We end by summarizing the implications of our review for future research.
155 citations
TL;DR: In this article, the authors present a method and a set of tools that allow end users without programming experience to customize the context-dependent behavior of their Web applications through the specification of trigger-action rules.
Abstract: Our life is characterized by the presence of a multitude of interactive devices and smart objects exploited for disparate goals in different contexts of use. Thus, it is impossible for application developers to predict at design time the devices and objects users will exploit, how they will be arranged, and in which situations and for which objectives they will be used. For such reasons, it is important to make end users able to easily and autonomously personalize the behaviour of their Internet of Things applications, so that they can better comply with their specific expectations. In this paper, we present a method and a set of tools that allow end users without programming experience to customize the context-dependent behaviour of their Web applications through the specification of trigger-action rules. The environment is able to support end-user specification of more flexible behaviour than what can be done with existing commercial tools, and it also includes an underlying infrastructure able to detect the possible contextual changes in order to achieve the desired behaviour. The resulting set of tools is able to support the dynamic creation and execution of personalized application versions more suitable for users’ needs in specific contexts of use. Thus, it represents a contribution to obtaining low threshold/high ceiling environments. We also report on an example application in the home automation domain, and a user study that has provided useful positive feedback.
139 citations
TL;DR: In this article, the authors show the importance of tailoring games for change in the context of a game designed to improve healthy eating habits, by adapting only the persuasive strategies employed; the game mechanics themselves did not vary.
Abstract: There has been a continuous increase in the design and application of computer games for purposes other than entertainment in recent years. Serious games—games that motivate behavior and retain attention in serious contexts—can change the attitudes, behaviors, and habits of players. These games for change have been shown to motivate behavior change, persuade people, and promote learning using various persuasive strategies. However, persuasive strategies that motivate one player may demotivate another. In this article, we show the importance of tailoring games for change in the context of a game designed to improve healthy eating habits. We tailored a custom-designed game by adapting only the persuasive strategies employed; the game mechanics themselves did not vary. Tailoring the game design to players’ personality type improved the effectiveness of the games in promoting positive attitudes, intention to change behavior, and self-efficacy. Furthermore, we show that the benefits of tailoring the game intervention are not explained by the improved player experience, but directly by the choice of persuasive strategy employed. Designers and researchers of games for change can use our results to improve the efficacy of their game-based interventions.
100 citations
TL;DR: The authors examined how four key principles from human geography (distance decay, structured variation in population density, mental maps, and spatial homophily) manifest in sharing economy platforms and found that the sharing economy is significantly more effective in dense, high socioeconomic status (SES) areas than in low-SES areas and the suburbs.
Abstract: Despite the geographically situated nature of most sharing economy tasks, little attention has been paid to the role that geography plays in the sharing economy. In this article, we help to address this gap in the literature by examining how four key principles from human geography—distance decay, structured variation in population density, mental maps, and “the Big Sort” (spatial homophily)—manifest in sharing economy platforms. We find that these principles interact with platform design decisions to create systemic biases in which the sharing economy is significantly more effective in dense, high socioeconomic status (SES) areas than in low-SES areas and the suburbs. We further show that these results are robust across two sharing economy platforms: UberX and TaskRabbit. In addition to highlighting systemic sharing economy biases, this article more fundamentally demonstrates the importance of considering well-known geographic principles when designing and studying sharing economy platforms.
89 citations
TL;DR: In this article, the authors investigate the problem of emoji entry, starting with a study of the current state of the emoji keyboard implementation in Android and then explore a model for emoji similarity that is able to inform such designs.
Abstract: Emoji, a set of pictographic Unicode characters, have seen strong uptake over the last couple of years. All common mobile platforms and many desktop systems now support emoji entry, and users have embraced their use. Yet, we currently know very little about what makes for good emoji entry. While soft keyboards for text entry are well optimized, based on language and touch models, no such information exists to guide the design of emoji keyboards. In this article, we investigate of the problem of emoji entry, starting with a study of the current state of the emoji keyboard implementation in Android. To enable moving forward to novel emoji keyboard designs, we then explore a model for emoji similarity that is able to inform such designs. This semantic model is based on data from 21 million collected tweets containing emoji. We compare this model against a solely description-based model of emoji in a crowdsourced study. Our model shows good perfor mance in capturing detailed relationships between emoji.
77 citations
TL;DR: The data traces of collaborative writing behavior in student teams’ use of Google Docs are examined to discover how they are writing together now, and system design implications and behavioral guidelines to support people writing together better are suggested.
Abstract: Today's commercially available word processors allow people to write collaboratively in the cloud, both in the familiar asynchronous mode and now in synchronous mode as well. This opens up new ways of working together. We examined the data traces of collaborative writing behavior in student teams’ use of Google Docs to discover how they are writing together now. We found that student teams write both synchronously and asynchronously, take fluid roles in the writing and editing of the documents, and show a variety of styles of collaborative writing, including writing from scratch, beginning with an outline, pasting in a related example as a template to organize their own writing, and three more. We also found that the document serves as a place where they share a number of things not included in the final document, including links or references to related materials, the assignment requirements from the instructor, and informal discussions to coordinate the collaboration or to structure the document. We computed a number of measures to depict a group's collaboration behavior and asked external graders to score these documents for quality. We found that the documents that included balanced participation and/or exhibited leadership were judged higher in quality, as were those that were longer. We then suggested system design implications and behavioral guidelines to support people writing together better, and concluded the paper with future research directions.
74 citations
TL;DR: In this article, the design dimension "bodily interplay" is proposed to give critical focus to how players' bodies interact with one another, and two broad categories of bodily interplay (parallel and interdependent play) are proposed to explain how exertion games can facilitate independent and offensive/defensive type experiences.
Abstract: While exertion games facilitate, and benefit from, social play, most exertion games merely support players acting independently. To help designers explore the richness of social play in exertion games, we present the design dimension “bodily interplay” that gives critical focus to how players’ bodies interact with one another. We offer two broad categories of bodily interplay—parallel and interdependent play—to explain how exertion games can facilitate independent and offensive/defensive-type experiences. These categories can be applied to both the physical and virtual space, and by looking at all permutations of these categories, we articulate four ways of coupling the spaces: comparative, actuated, derived, and projected coupling. This article illustrates the inspirational power of the dimensions by applying them to the analysis of four exertion games. Altogether, we articulate a vocabulary that can guide designers in the creation of social exertion games, helping players profit from the many benefits of exertion.
74 citations
TL;DR: B BubbleView clicks can both successfully approximate eye fixations on different images, and be used to rank image and design elements by importance, and validate the use of mouse-contingent, moving-window methodologies as approximating eyefixations for different image and task types.
Abstract: In this article, we present BubbleView, an alternative methodology for eye tracking using discrete mouse clicks to measure which information people consciously choose to examine. BubbleView is a mouse-contingent, moving-window interface in which participants are presented with a series of blurred images and click to reveal “bubbles” -- small, circular areas of the image at original resolution, similar to having a confined area of focus like the eye fovea. Across 10 experiments with 28 different parameter combinations, we evaluated BubbleView on a variety of image types: information visualizations, natural images, static webpages, and graphic designs, and compared the clicks to eye fixations collected with eye-trackers in controlled lab settings. We found that BubbleView clicks can both (i) successfully approximate eye fixations on different images, and (ii) be used to rank image and design elements by importance. BubbleView is designed to collect clicks on static images, and works best for defined tasks such as describing the content of an information visualization or measuring image importance. BubbleView data is cleaner and more consistent than related methodologies that use continuous mouse movements. Our analyses validate the use of mouse-contingent, moving-window methodologies as approximating eye fixations for different image and task types.
73 citations
TL;DR: In this paper, the authors report on a contextual inquiry study in which they collected qualitative data from 18 participants in 12 households on the current potential and acceptance of home automation, as well as explored the respective benefits and drawbacks of these two notation paradigms for end users.
Abstract: Home automation faces the challenge of providing ubiquitous, unobtrusive services while empowering users with approachable configuration interfaces. These interfaces need to provide sufficient expressiveness to support complex automation, and notations need to be devised that enable less tech-savvy users to express such scenarios. Rule-based and process-oriented paradigms have emerged as opposing ends of the spectrum; however, their underlying concepts have not been studied comparatively. We report on a contextual inquiry study in which we collected qualitative data from 18 participants in 12 households on the current potential and acceptance of home automation, as well as explored the respective benefits and drawbacks of these two notation paradigms for end users. Results show that rule-based notations are sufficient for simple automation tasks but not flexible enough for more complex use cases. The resulting insights can inform the design of interfaces for smart homes to enable usable real-world home automation for end users.
64 citations
TL;DR: Motion correlation has been explored in earlier work but only recently begun to feature in holistic interface designs as discussed by the authors, where users are guided by motion feedback, and only need to copy a presented motion.
Abstract: Selection is a canonical task in user interfaces, commonly supported by presenting objects for acquisition by pointing. In this article, we consider motion correlation as an alternative for selection. The principle is to represent available objects by motion in the interface, have users identify a target by mimicking its specific motion, and use the correlation between the system’s output with the user’s input to determine the selection. The resulting interaction has compelling properties, as users are guided by motion feedback, and only need to copy a presented motion. Motion correlation has been explored in earlier work but only recently begun to feature in holistic interface designs. We provide a first comprehensive review of the principle, and present an analysis of five previously published works, in which motion correlation underpinned the design of novel gaze and gesture interfaces for diverse application contexts. We derive guidelines for motion correlation algorithms, motion feedback, choice of modalities, overall design of motion correlation interfaces, and identify opportunities and challenges identified for future research and design.
TL;DR: It is concluded that control theory offers a promising complement to Fitts’ law based approaches in HCI, with models providing representations and predictions of human pointing dynamics, which can improve the understanding of pointing and inform design.
Abstract: This article presents an empirical comparison of four models from manual control theory on their ability to model targeting behaviour by human users using a mouse: McRuer’s Crossover, Costello’s Surge, second-order lag (2OL), and the Bang-bang model. Such dynamic models are generative, estimating not only movement time, but also pointer position, velocity, and acceleration on a moment-to-moment basis. We describe an experimental framework for acquiring pointing actions and automatically fitting the parameters of mathematical models to the empirical data. We present the use of time-series, phase space, and Hooke plot visualisations of the experimental data, to gain insight into human pointing dynamics. We find that the identified control models can generate a range of dynamic behaviours that captures aspects of human pointing behaviour to varying degrees. Conditions with a low index of difficulty (ID) showed poorer fit because their unconstrained nature leads naturally to more behavioural variability. We report on characteristics of human surge behaviour (the initial, ballistic sub-movement) in pointing, as well as differences in a number of controller performance measures, including overshoot, settling time, peak time, and rise time. We describe trade-offs among the models. We conclude that control theory offers a promising complement to Fitts’ law based approaches in HCI, with models providing representations and predictions of human pointing dynamics, which can improve our understanding of pointing and inform design.
TL;DR: An inference model is developed and evaluated that predicts the optimal sharing policy given the three types of features in multiuser scenarios where arguments are employed, and the predictions of the model are analyzed to uncover potential scenario types that lead to incorrect predictions and to enhance the understanding of when multiusers scenarios are more or less prone to dispute.
Abstract: Social network services (SNSs) enable users to conveniently share personal information. Often, the information shared concerns other people, especially other members of the SNS. In such situations, two or more people can have conflicting privacy preferences; thus, an appropriate sharing policy may not be apparent. We identify such situations as multiuser privacy scenarios. Current approaches propose finding a sharing policy through preference aggregation. However, studies suggest that users feel more confident in their decisions regarding sharing when they know the reasons behind each other’s preferences. The goals of this paper are (1) understanding how people decide the appropriate sharing policy in multiuser scenarios where arguments are employed, and (2) developing a computational model to predict an appropriate sharing policy for a given scenario. We report on a study that involved a survey of 988 Amazon Mechanical Turk (MTurk) users about a variety of multiuser scenarios and the optimal sharing policy for each scenario. Our evaluation of the participants’ responses reveals that contextual factors, user preferences, and arguments influence the optimal sharing policy in a multiuser scenario. We develop and evaluate an inference model that predicts the optimal sharing policy given the three types of features. We analyze the predictions of our inference model to uncover potential scenario types that lead to incorrect predictions, and to enhance our understanding of when multiuser scenarios are more or less prone to dispute.
TL;DR: Three implications for design for supporting end user development of complex electronic DIY are designed: designing transparent open hardware technologies, standardizing communication protocols for the current and future DIY of IoT, and deliberately calling for personal investment and labor in the assembling of DIY kits.
Abstract: We are surrounded by increasingly complex networks of smart objects, yet our understanding and attachment to them is rather limited. One way to support stronger end users’ engagement with such complex technologies is by involving them in the design process and, with the advent of Arduino prototyping platform, even in their making. While DIY practice offers the potential for stronger user engagement with physical artifacts, we know little about end users’ DIY practice of making complex electronic technologies and their potential to ensure engagement with such devices. In this article, we report on interviews with 18 participants from two green communities who built and used an open source DIY energy monitor, with the aim to explore the end users DIY practices of making such complex electronic devices. Findings indicate four key qualities of DIY monitors: transparent modularity, open-endedness, heirloom, and disruptiveness, and how they contribute to more meaningful engagement with the DIY monitors, elevating them from the status of unremarkable objects to that of things. We conclude with three implications for design for supporting end user development of complex electronic DIY: designing transparent open hardware technologies, standardizing communication protocols for the current and future DIY of IoT, and deliberately calling for personal investment and labor in the assembling of DIY kits.
TL;DR: The students who use DragonBox solved many more problems and enjoyed the experience more, but the students who used Lynnette performed significantly better on the post-test, showing that intuitions about what works, educationally, can be fallible.
Abstract: Educational games and intelligent tutoring systems (ITS) both support learning by doing, although often in different ways. The current classroom experiment compared a popular commercial game for equation solving, DragonBox and a research-based ITS, Lynnette with respect to desirable educational outcomes. The 190 participating 7th and 8th grade students were randomly assigned to work with either system for 5 class periods. We measured out-of-system transfer of learning with a paper and pencil pre- and post-test of students’ equation-solving skill. We measured enjoyment and accuracy of self-assessment with a questionnaire. The students who used DragonBox solved many more problems and enjoyed the experience more, but the students who used Lynnette performed significantly better on the post-test. Our analysis of the design features of both systems suggests possible explanations and spurs ideas for how the strengths of the two systems might be combined. The study shows that intuitions about what works, educationally, can be fallible. Therefore, there is no substitute for rigorous empirical evaluation of educational technologies.
TL;DR: It is indicated that mood self-tracking is accepted and can improve performance if the application is well integrated into the work processes and matches the management style.
Abstract: The benefits of self-tracking have been thoroughly investigated in private areas of life, like health or sustainable living, but less attention has been given to the impact and benefits of self-tracking in work-related settings. Through two field studies, we introduced and evaluated a mood self-tracking application in two call centers to investigate the role of mood self-tracking at work, as well as its impact on individuals and teams. Our studies indicate that mood self-tracking is accepted and can improve performance if the application is well integrated into the work processes and matches the management style. The results show that (i) capturing moods and explicitly relating them to work tasks facilitated reflection, (ii) mood self-tracking increased emotional awareness and this improved cohesion within teams, and (iii) proactive reactions by managers to trends and changes in team members’ mood were key for acceptance of reflection and correlated with measured improvements in work performance. These findings help to better understand the role and potential of self-tracking at the workplace, and further provide insights that guide future researchers and practitioners to design and introduce these tools in a work setting.
TL;DR: In this paper, a probabilistic generative modeling framework that expresses semantic concepts as a combination of color and word distributions is proposed to infer a set of color-word topics over a corpus of 2,654 magazine covers spanning 71 distinct titles and 12 genres.
Abstract: We study the concept of color semantics by modeling a dataset of magazine cover designs, evaluating the model via crowdsourcing, and demonstrating several prototypes that facilitate color-related design tasks. We investigate a probabilistic generative modeling framework that expresses semantic concepts as a combination of color and word distributions -- color-word topics. We adopt an extension to Latent Dirichlet Allocation (LDA) topic modeling, called LDA-dual, to infer a set of color-word topics over a corpus of 2,654 magazine covers spanning 71 distinct titles and 12 genres. Although LDA models text documents as distributions over word topics, we model magazine covers as distributions over color-word topics. The results of our crowdsourcing experiments confirm that the model is able to successfully discover the associations between colors and linguistic concepts. Finally, we demonstrate several prototype applications that use the learned model to enable more meaningful interactions in color palette recommendation, design example retrieval, pattern recoloring, image retrieval, and image color selection.
TL;DR: In this paper, the authors focus on individual crowd worker competencies and propose a competence-based pre-selection method that considers accuracy of worker self-assessments for sentiment analysis tasks.
Abstract: Paid crowdsourcing platforms have evolved into remarkable marketplaces where requesters can tap into human intelligence to serve a multitude of purposes, and the workforce can benefit through monetary returns for investing their efforts. In this work, we focus on individual crowd worker competencies. By drawing from self-assessment theories in psychology, we show that crowd workers often lack awareness about their true level of competence. Due to this, although workers intend to maintain a high reputation, they tend to participate in tasks that are beyond their competence. We reveal the diversity of individual worker competencies, and make a case for competence-based pre-selection in crowdsourcing marketplaces. We show the implications of flawed self-assessments on real-world microtasks, and propose a novel worker pre-selection method that considers accuracy of worker self-assessments. We evaluated our method in a sentiment analysis task and observed an improvement in the accuracy by over 15%, when compared to traditional performance-based worker pre-selection. Similarly, our proposed method resulted in an improvement in accuracy of nearly 6% in an image validation task. Our results show that requesters in crowdsourcing platforms can benefit by considering worker self-assessments in addition to their performance for pre-selection.
TL;DR: This work conceptualizes the idea of “Sociable Technologies” and implements a prototype that provides hardware-integrated affordances for communicating and documenting practices of usage and derives lessons learnt when aiming at making complex technologies more usable.
Abstract: 3D printers have become continuously more present and are a perspicuous example of how technologies are becoming more complex and ubiquitous. To some extent, the emerging technological infrastructures around them exemplify ways how digitalization will change production machines and lines, in general, in the Internet of Things (IoT). From an End-User Development perspective, the main question is how users can be supported in managing those complex digital production lines. To reach a better understanding, we carefully analyzed 3D printers as an example of highly digitalized production machines with regard to the creative activities of their users that help them to make these machines work for their practices. In our study of appropriation processes, we are concerned with situational and social aspects of the configuration and practice challenges associated with making digitalization work and how IoT technologies can support these collaborative appropriation activities of end users by making these machines more “sociable.” We therefore conceptualize the idea of “Sociable Technologies” and implement a prototype that provides hardware-integrated affordances for communicating and documenting practices of usage. Based on the findings of our evaluation, we derive lessons learnt when aiming at making complex technologies more usable.
TL;DR: In this article, the authors describe four ways that players can engage with framing structures, which they classify in terms of whether players conform to explore, transgress, or (re)create them.
Abstract: Numerous studies have foregrounded how play is only partially shaped by the artifacts that their designers design. The play activity can change the structures framing it, turning players into co-designers through the mere act of playing.This article contributes to our understanding of how we can design for play taking into account that play has this transformative power. We describe four ways that players can engage with framing structures, which we classify in terms of whether players conform to explore, transgress, or (re)create them. Through the examples of three case studies, we illustrate how this model has been useful in design: as an analytical tool for deconstructing player behavior, to articulate design goals and support specific design choices, and for shaping the design process.
TL;DR: Visual Simple Transformations (ViSiT) is presented as an approach that allows end-users to use a jigsaw puzzle metaphor for specifying transformations that are automatically converted into underlying executable workflows and showed positive indications of perceived usability, learnability, and the ability to conceive real-life scenarios for ViSiT.
Abstract: Empowering end-users to wire Internet of Things (IoT) objects (things and services) together would allow them to more easily conceive and realize interesting IoT solutions. A challenge lies in devising a simple end-user development approach to support the specification of transformations, which can bridge the mismatch in the data being exchanged among IoT objects. To tackle this challenge, we present Visual Simple Transformations (ViSiT) as an approach that allows end-users to use a jigsaw puzzle metaphor for specifying transformations that are automatically converted into underlying executable workflows. ViSiT is explained by presenting meta-models and an architecture for implementing a system of connected IoT objects. A tool is provided for supporting end-users in visually developing and testing transformations. Another tool is also provided for allowing software developers to modify, if they wish, a transformation's underlying implementation. This work was evaluated from a technical perspective by developing transformations and measuring ViSiT's efficiency and scalability and by constructing an example application to show ViSiT's practicality. A study was conducted to evaluate this work from an end-user perspective, and its results showed positive indications of perceived usability, learnability, and the ability to conceive real-life scenarios for ViSiT.
TL;DR: End-user development addresses the challenge of how best to help users to harness the potential power of these large collections of devices to accomplish their tasks within the dynamic technological habitat they provide.
TL;DR: Improv is presented, a cross-device input framework that allows a user to easily leverage the capability of additional devices to create new input methods for an existing, unmodified application, e.g., creating custom gestures on a smartphone to control a desktop presentation application.
Abstract: As computing devices become increasingly ubiquitous, it is now possible to combine the unique capabilities of different devices or Internet of Things to accomplish a task. However, there is currently a high technical barrier for creating cross-device interaction. This is especially challenging for end users who have limited technical expertise—end users would greatly benefit from custom cross-device interaction that best suits their needs. In this article, we present Improv, a cross-device input framework that allows a user to easily leverage the capability of additional devices to create new input methods for an existing, unmodified application, e.g., creating custom gestures on a smartphone to control a desktop presentation application. Instead of requiring developers to anticipate and program these cross-device behaviors in advance, Improv enables end users to improvise them on the fly by simple demonstration, for their particular needs and devices at hand. We showcase a range of scenarios where Improv is used to create a diverse set of useful cross-device input. Our study with 14 participants indicated that on average it took a participant 10 seconds to create a cross-device input technique. In addition, Improv achieved 93.7% accuracy in interpreting user demonstration of a target UI behavior by looking at the raw input events from a single example.
TL;DR: Two studies examine the effect of changing performance requirements, and find that a high performance requirement imposed in a training context can effectively push users to adopt an expert technique, and that use of the technique is maintained when the requirement is subsequently reduced or removed.
Abstract: Expert interaction techniques enable users to greatly improve their performance; however, to realize these advantages, the user must first acquire the skill necessary to use a technique, then choose to use it over competing novice techniques. This article investigates several factors that may influence whether use of an expert technique persists when the context of use changes. Two studies examine the effect of changing performance requirements, and find that a high performance requirement imposed in a training context can effectively push users to adopt an expert technique, and that use of the technique is maintained when the requirement is subsequently reduced or removed. In a final study, performance requirement, high-level task, and environment of use are changed—participants played a training game to learn the menu for a drawing application, which they then used to complete a series of drawings over the following week. Participants exhibited a somewhat surprising “all-or-nothing” effect, using the expert technique nearly exclusively or not at all, and maintaining this behavior over a range of qualitatively different tasks. This suggests that switching to an expert technique involves a global change by the user, rather than an incremental change as suggested by previous work.
TL;DR: It is illustrated how RaPIDO enabled broader exploration of the design space and faster iterations than would otherwise be possible, allowing designers to focus on the core game concepts rather than complex and low-level engineering issues.
Abstract: Outdoor, multi-player games involving social interaction and physical activity are an emerging class of applications particularly interesting for children, for whom the attraction and the health and developmental benefits are clear cut. Implementing and prototyping such games present non-trivial technical challenges to interaction and game designers; this hampers iterative prototyping and testing cycles that are core to user-centred design and game development processes. This insight has motivated the development of RaPIDO (Rapid prototyping of Physical Interaction Design for Outdoor games), a prototyping platform for physical computing, targeting interaction designers with limited electronics or software skills. RaPIDO has been evaluated in a user test, evaluating RaPIDOs software library, and in a case study involving two designers who used it to develop outdoor games for children. We illustrate how RaPIDO enabled broader exploration of the design space and faster iterations than would otherwise be possible, allowing designers to focus on the core game concepts rather than complex and low-level engineering issues.
TL;DR: Metatation as discussed by the authors leverages a critic's annotations as implicit interactions for initiating context-specific computational support that automatically searches external resources to augment close reading in poetry critics, revealing a set of cognitive practices supported through free-form annotation that have not previously been discussed in this context.
Abstract: In the domain of literary criticism, many critics practice close reading, annotating by hand while performing a detailed analysis of a single text. Often this process employs the use of external resources to aid analysis. In this article, we present a study and subsequent tool design focused on leveraging a critic’s annotations as implicit interactions for initiating context-specific computational support that automatically searches external resources. We observed 14 poetry critics performing a close reading, revealing a set of cognitive practices supported through free-form annotation that have not previously been discussed in this context. We used guidelines derived from our study to design a tool, Metatation, which uses a pen-and-paper system with a peripheral display to utilize reader annotations as underspecified interactions to augment close reading. By turning paper-based annotations into implicit queries, Metatation provides relevant supplemental information in a just-in-time manner and acts as a bridge between close and distant reading.
TL;DR: In this article, the problem of identifying functionality sets that strike the best balance among four objectives (i.e., usefulness, satisfaction, ease of use, and profitability) is addressed.
Abstract: Designing interactive technology entails several objectives, one of which is identifying and selecting appropriate functionality. Given candidate functionalities such as “print,” “bookmark,” and “share,” a designer has to choose which functionalities to include and which to leave out. Such choices critically affect the acceptability, productivity, usability, and experience of the design. However, designers may overlook reasonable designs because there is an exponential number of functionality sets and multiple factors to consider. This article is the first to formally define this problem and propose an algorithmic method to support designers to explore alternative functionality sets in early stage design. Based on interviews of professional designers, we mathematically define the task of identifying functionality sets that strike the best balance among four objectives: usefulness, satisfaction, ease of use, and profitability. We develop an integer linear programming solution that can efficiently solve very large instances (set size over 1,300) on a regular computer. Further, we build on techniques of robust optimization to search for diverse and surprising functionality designs. Empirical results from a controlled study and field deployment are encouraging. Most designers rated computationally created sets to be of the comparable or superior quality than their own. Designers reported gaining better understanding of available functionalities and the design space.
TL;DR: A simple context-range semantics (CRS) and a context- range editor (CoRE) that support end users formulate and understand logical expressions regarding context that improves performance of non-programmers in specifying context sensitive system behaviour.
Abstract: The realization and deployment of the Internet of Things require providing to non-programmers some level of programmatic control for tailoring system behaviour to their context and needs. We introduce a simple context-range semantics (CRS) and a context-range editor (CoRE) that support end users formulate and understand logical expressions regarding context. The editor builds on two key ideas (a) contextual information is used to evaluate and minimize logical expressions; (b) logical expressions are presented in a disjunctive normal form (DNF) thus applying a principle established in mental model theory. User tests reveal situations in which the theory regarding the intuitiveness of the DNF needs to be extended with a new element: Logical terms are easier to comprehend and formulate when grouped according to their semantic affinity. We report two experiments that demonstrate the intuitiveness of this approach and how it improves performance of non-programmers in specifying context sensitive system behaviour.
TL;DR: In this article, the authors explore electroencephalography (EEG), electrodermal activity (EDA), and electrocardiography (ECG) as valid sources to infer humor appraisal in a realistic environment.
Abstract: We explore electroencephalography (EEG), electrodermal activity (EDA), and electrocardiography (ECG) as valid sources to infer humor appraisal in a realistic environment. We report on an experiment in which 25 participants browsed a popular user-generated humorous content website while their physiological responses were recorded. We build predictive models to infer the participants’ appraisal of the humorousness of the content and demonstrate that the fusion of several physiological signals can lead to classification performances up to 0.73 in terms of the area under the ROC curve (AUC). We identify that the most discriminative changes in physiological signals happen at the later stages of the information consumption process, reflected in changes on the upper EEG frequency bands, higher levels of EDA, and heart-rate acceleration. Additionally, we present a comprehensive analysis by benchmarking the predictive power of each of the physiological signals separately, and by comparing them to state-of-the-art facial recognition algorithms based on facial video recordings. The classification performance ranges from 0.88 (in terms of AUC) when combining physiological signals and video recordings, to 0.55 when using ECG signals alone.
TL;DR: I'm always excited to usher in the latest advances in the field of human-computer interaction, starting especially with the six sterling results you hold right now in your hands, and expect to have the results for 2016 in hand when I sit down to write my next editorial two months hence.
Abstract: Prognostications. Well, 2016 has been consigned to the dustbin of history and 2017 is here whether you wanted it or not. What exactly the new year will herald remains unclear beyond the nigh-certainties of rising global temperatures and a hothouse of political rhetoric, though I must admit to a certain reticence before I consult my Magic 8-Ball for its prognostications. OUTLOOK UNCLEAR, it informs me, with an admonishment to ASK AGAIN LATER when I have the temerity to prod it again. I guess I shouldn't have asked. But as a practicing seer of the technological near-future, one thing I'm certain of is constantly being surprised by the new insights, analyses, and breakthroughs that grace TOCHI's pages. I'm always excited to usher in the latest advances in the field of human-computer interaction, starting especially with the six sterling results you hold right now in your hands. * * * The sealed envelope. Originally, I had planned to announce the TOCHI 2016 Best Paper Award in this editorial. But it belatedly dawned on me that the final issue of 2016 wouldn't be finalized with enough lead time to actually make that feasible. Apparently, our Associate Editors like to go home and see their families over the winter holidays, the nerve of them! (grin). I also wanted to allow some time for TOCHI readers to nominate any article from 23:6 that may have caught their collective eyes. But the Best Paper process is now in full swing and I expect to have the results for 2016 in hand when I sit down to write my next editorial two months hence. Be sure to keep an eye open for the April issue of TOCHI (in the eventuality that our internationally televised awards ceremony fails to materialize) so that you can join me, with my ever-thinning hair brilliantined and my tux fitting a bit more snugly than it did in my youth, as I open the sealed envelope for all to behold! * * * A turn of fortune. I found this month's allotment of TOCHI contributions even more interesting and diverse than usual, which I suppose says quite a bit about the depth and strength of this batch of papers. And the authors range from CHI Academy veterans to up-and-coming stars of the field. Meanwhile, even as I type this, another acceptance has rolled in from the diligent authors and editors who are burnishing …