Human Computer Interaction research at UC Santa Cruz includes work focused on the intersection of Wellbeing and Technology, and research concerning Games and Computational Media.
We are hosting an open house for CHI 2016 attendees to showcase current HCI research at UC Santa Cruz. Demos will be presented in the Jack Baskin School of Engineering, room E2-262.
We’ll adjourn at 3:00 to the Jack O’Neill Lounge at the Dream Inn, where the first drink is on us (via a drink ticket with delimited options).
Contact: Katherine Isbister – email@example.com
Director, Human-Computer Interaction Lab.
We are interested in technologies that improve well-being and support community, to improve focus, reduce stress, abandon bad habits and regulate mood.
Director, Interactive Systems for Individuals with Special Needs (ISIS) Lab.
We look for creative ways that computing systems, their applications and their sensors can be used to maintain and improve the health and well-being of populations with special needs.
Director, Social and Emotional Technologies (SET) Lab.
Current research interests include emotion and games, embodied self-regulation through games and play, and social wearable-enabled games and play.
1:00-3:00pm, Friday May 13
Jack Baskin School of Engineering
room E2-262 (2nd floor)
UC Santa Cruz
1156 High Street
Santa Cruz, CA 95064
3:00-6:00pm, Friday May 13
Jack O’Neill Lounge
175 W Cliff Dr
Santa Cruz, CA 95060
Proper preparation and support before, during, and after the onset of labor is key to shortening labor, decreasing the need for interventions during labor, and ultimately increasing maternal happiness. Digital Birth is an educational iPhone-based game about labor and childbirth. It aims to introduce natural coping mechanisms and their effects on labor, to introduce the mechanics of labor and childbirth, to train birth partners to help women in childbirth, to practice interacting with a woman in labor, and to simulate the stages of labor.
This talk will address two major shortcomings of technologies for health & well-being. First, tools for behavior tracking ignore the motivational role of emotions in guiding behavior. Second, the majority of self-improvement technologies are past-oriented and lack system support to assist users in thinking about their futures. I will outline results of two field system deployments illustrating  the importance of including emotional reflection to improve behavior change success and  the impact of a prototype for forecasting future emotions & activity recommendations to improve mood.
Computational tasks are a large part of the workday for many Americans. Current interfaces and systems have come into question in recent years for inadvertently disrupting quality attention and focus, leading to scattered, distracted, and inefficient work practices and suboptimal mental and emotional functioning. Efforts to address this issue include development of specialized, minimally distracting digital applications within which to work, software that blocks or limits the use of the most distracting applications, and software that encourages and/or enforces break-taking and other non-computational techniques for enhancing focus such as physical activity. Our research takes a novel approach to addressing this problem, combining insights from tangible computing, embodied interaction, and quantified self research within Human Computer Interaction, and building upon promising insights and results within the ADHD (Attention Deficit and Hyperactivity Disorder) research and clinical communities. We are engaged in designing a physical/computational intervention that enables embodied self-regulation of attention, and that provides tools for self-reflection about attentional challenges, toward optimal management of work practice and attentional state.
Traditional cognitive testing for detecting cognitive impairment (CI) can be inaccessible, expensive, and time consuming. This dissertation aims to develop an automated online computerized neuropsychological testing system for rapidly tracking an individual’s cognitive performance throughout the user’s daily or weekly schedule in an unobtrusive way. By utilizing embedded microsensors within tablet devices, the proposed context-aware system will capture ambient and behavioral data pertinent to the real-world contexts and times of testing to compliment psychometric results, by providing insight into the contextual factors relevant to the user’s testing efficacy and performance.
Uses the Microsoft Band and Affdex facial recognition software to add physiological data to gameplay streams to Twitch TV. Researching how adding this data to gameplay streams affects the conversation between spectators and players.
Maintaining work focus when on a computer is a challenge, and people often feel that they use their time ineffectively. We designed meTime, a simple real-time desktop awareness application that shows users how they allocate their time across applications. In two real world deployments we found that meTime helped participants reduce the amount of time they spend in non-work activities and overall time on their computer. However it didn’t lead participants to spend more time in work-related activities.
Does introducing software and mobile technology to speech therapy make a difference? Find out in the next few minutes!
An in progress study exploring the impact of metaphors in Robot-Mediated Communication (RMC). Recent research in this area suggests that differences in behavior may be significantly associated with the degree to which the robot is thought of as a thing vs. an extension of the person using it, as indicated by the metaphors the person uses to describe the robot (e.g. “it” or “the robot”, vs. “Jane” or “my coworker”). We seek to better understand this interaction between metaphor and behavior, and to develop a methodology which can be replicated in future studies building on this research.
Aaron Springer – firstname.lastname@example.org
EmotiCal is an application to automatically forecast future emotions and recommended positive activities to improve mood. We examine the forecasting algorithms within the system along with design implications for future systems that model mood.
The notion of embodiment stems from the concept that cognition does not only occur in the mind but is also supported by bodily activity; situated in and interacting with our physical and social environment. Recent work on educational systems has shown the benefits of incorporating physicality, motion, and embodiment into designs. For instance, improved spatial recall and mental manipulation, more intuitive interfaces, increased engagement, greater positive feelings towards learning content, and enhanced collaboration. However, some studies have faced notable difficulty when attempting to utilize embodiment in their designs due to a broad conceptual usage of embodiment across multiple domains, leading to weak mappings between physical action, embodied cognition, and learning concepts. This ultimately raises questions of how and when embodiment can be beneficial within an educational application. Specifically 1) how can we effectively design embodiment into educational systems; 2) what affordances does embodiment provide to help facilitate learning through the meaning-making process; and 3) when a certain form of embodiment will lead weak or strong mappings between physical action, embodied cognition, and learning concepts?
A photo application that captures ambient data and voice memos to help blind users to maneuver through their catalog of photos.
This work studies two aspects of online communities: Which aspects of linguistic content predict member satisfaction and are temporal changes consistent with proposed online community lifecycle models? The first study examined the extent to which emotional and factual language relate to member satisfaction (A known factor of online community success). This study found that communities with more factual content (less emotional), these communities also had higher levels of member satisfaction. This relationship was further explored by examining various community types as well as various social tools existing within the communities. The second study examines the posting and linking behaviors across two formal roles within enterprise online communities. The findings show that posting and linking behaviors differ across various tools (Forums, Blogs, Wikis) and that these effects are changing over time. Most tools were dominated by specific roles but the level at which these role dominant the behaviors within each tool vary. This findings have interesting implications as to how online community tools should be focused more so on who is using the tools and what is the intention with the content being posted.
An online learning system (in the form of a web-app designed for iPad) made up of a set of activities that aim to help people with developmental disabilities reinforce basic skills such as recognizing numbers, letters, colors, shapes, and money.
This is an ongoing project exploring the effects of positive and negative emotions on how users process digital files. User’s digital information management behaviors can be incredibly varied and idiosyncratic. This makes the challenging task of managing an ever increasing amount of digital stuff difficult for systems to solve programmatically as some of these behaviors may serve a purpose for the individual user. Emotions may present another explanatory variable for differing approaches to information management. More specifically, emotions may explain some discrepancies that a single user may have in how they manage different aspects of their repository. Positive emotion has been shown to trigger flexible and creative thinking styles, whereas negative emotion appears to trigger more systematic and analytic processing. This has clear implications for how one may decide to organize one’s digital files. We are exploring this topic with an in-lab filing simulation where users are either put in a positive or negative mood, and we predict that positive moods will lead to more loose and creative categories while negative moods will lead to more strict and traditional categories. This work could have important implications for how systems can predict and adapt to a user’s affective states and potentially assist users in making the most of their own emotional rhythms.
Recent research has developed analytics that threaten online self-presentation and privacy by automatically generating profiles of individuals’ most personal traits—their personality, values, motivations, and so on. But we know little about people’s reactions to personal traits profiles of themselves, or what influences their decisions to share such profiles. We present an early qualitative study of people’s reactions to a working hyper-personal analytics system. The system lets them see their personality and values profile derived from their own social media text. Our results reveal a paradox. Participants found their personal traits profiles creepily accurate and did not like sharing them in many situations. However, they felt pressured by the social risks of not sharing and showed signs of learned helplessness, leading them to share despite their misgivings. Further, they felt unqualified to significantly modify their profile contents due to a surprising trust in the “expert” algorithm. We explore design implications for hyper-personal analytics systems that consider the needs and preferences of the people being profiled, suggesting ways to enhance the control they feel and the benefits they reap.