How can I improve my performance here?Figure 1: After completing a lap, the driver pauses the video at a specific segment and asks ApexTrainer for feedback.The system generates context-aware suggestions based on the referenced location.

Emotions play a major role in how interpersonal conflicts unfold. Although several strategies and technological approaches have been proposed for emotion regulation, they often require conscious attention and effort. This often limits their efficacy in practice. In this paper, we propose a different approach inspired by self-perception theory: noticing that people are often reacting to the perception of their own behavior, we artificially change their perceptions to influence their emotions. We conducted two studies to evaluate the potential of this approach by automatically and subtly altering how people perceive their own voice. In one study, participants that received voice feedback with a calmer tone during relationship conflicts felt less anxious. In the other study, participants who listened to their own voices with a lower pitch during contentious debates felt more powerful. We discuss the implications of our findings and the opportunities for designing automatic and less perceptible emotion regulation systems.

Alertness is a crucial component of our cognitive performance. Reduced alertness can negatively impact memory consolidation, productivity and safety. As a result, there has been an increasing focus on continuous assessment of alertness. The existing methods usually require users to wear sensors, fill out questionnaires, or perform response time tests periodically, in order to track their alertness. These methods may be obtrusvie to some users, and thus have limited capability. In this work, we propose AlertnessScanner, a computer-vision-based system that collects in-situ pupil information to model alertness in the wild. We conducted two in-the-wild studies to evaluate the effectiveness of our solution, and found that AlertnessScanner passively and unobtrusively assess alertness. We discuss the implications of our findings and present opportunities for mobile applications that measure and act upon changes in alertness.

In this paper we demonstrate that it is possible to help individuals regulate their emotions with mobile interventions that leverage the way we naturally react to our bodily signals. Previous studies demonstrate that the awareness of our bodily signals, such as our heart rate, directly influences the way we feel. By leveraging these findings we designed a wearable device to regulate user's anxiety by providing a false feedback of a slow heart rate. The results of an experiment with 67 participants show that the device kept the anxiety of the individuals in low levels when compared to the control group and the other conditions. We discuss the implications of our findings and present some promising directions for designing and developing this type of intervention for emotion regulation.

Interpersonal communication skills are critical in certain industry sectors like sales and marketing. Recent advances in wearable technology are enabling the design of real-time behavioral feedback tools for apprentices in aforementioned industries. This paper describes the design and implementation of a conversational behavior awareness tool based on Google Glass. The goal of the system is to provide real-time feedback to young sales apprentices about the amount of time they talk in an interaction with a client. We evaluated our system with a pilot study involving 15 apprentices (ages 16--20). Overall, participants found the system fun, little distracting and useful. Furthermore, manual coding of the recorded videos, showed that wearable sensing and real-time feedback did not negatively influence the dyadic social interaction.

The increasing adoption of social media provides unprecedented opportunities to gain insight into human nature at vastly broader scales. Regarding the study of population-wide sentiment, prior research commonly focuses on text-based analyses and ignores a treasure trove of sentiment-laden content: images. In this paper, we make methodological and computational contributions by introducing the Smile Index as a formalized measure of societal happiness. Detecting smiles in 9 million geo-located tweets over 16 months, we validate our Smile Index against both text-based techniques and self-reported happiness. We further make observational contributions by applying our metric to explore temporal trends in sentiment, relate public mood to societal events, and predict economic indicators. Reflecting upon the innate, language-independent aspects of facial expressions, we recommend future improvements and applications to enable robust, global-level analyses. We conclude with implications for researchers studying and facilitating the expression of collective emotion through socio-technical systems.

Persuasive technologies aim to influence user's behaviors. In order to be effective, many of the persuasive technologies de-veloped so far relies on user's motivation and ability, which is highly variable and often the reason behind the failure of such technology. In this paper, we present the concept of Mindless Computing, which is a new approach to persuasive technology design. Mindless Computing leverages theories and concepts from psychology and behavioral economics into the design of technologies for behavior change. We show through a systematic review that most of the current persuasive technologies do not utilize the fast and automatic mental processes for behavioral change and there is an opportunity for persuasive technology designers to develop systems that are less reliant on user's motivation and ability. We describe two examples of mindless technologies and present pilot studies with encouraging results. Finally, we discuss design guidelines and considerations for developing this type of persuasive technology.

The past decade has witnessed the development of a new class of coordination tools that focus on automatically providing individuals a rich context for facilitating the coordination of their work. Despite their valuable contributions, current coordination tools have mostly been designed without taking into account scalability aspects beyond the small-group level. The increasing pervasiveness of large-scale projects suggests that those mechanisms need to scale dramatically to adequately support such work settings. In this paper, we used data from five distinct large-scale projects from three different companies to study the scale, range, and volatility of the coordination requirements that emerged over time within those projects. Our results showed that coordination requirements tend to be quite volatile, vary significantly in their magnitude across project members and a significant proportion of the coordination requirements cut across organizational and geographical boundaries. Furthermore, new coordination requirements represent, on average, a third of the coordination requirements faced by a project member on a monthly basis. The implications of these results for the design of collaborative tools are discussed.

This paper presents RaisAware, a collaborative software development tool aimed at supporting the relationship between software architecture and coordination of software development activities. Our design is based on both dependency analysis of software development artifacts and software developers'