Jodi Forlizzi

Research through design as a method for interaction design research in HCI

For years the HCI community has struggled to integrate design in research and practice. While design has gained a strong foothold in practice, it has had much less impact on the HCI research community. In this paper we propose a new model for interaction design research within HCI. Following a research through design approach, designers produce novel integrations of HCI research in an attempt to make the right thing: a product that transforms the world from its current state to a preferred state. This model allows interaction designers to make research contributions based on their strength in addressing under-constrained problems. To formalize this model, we provide a set of four lenses for evaluating the research contribution and a set of three examples to illustrate the benefits of this type of research.

Understanding experience in interactive systems

Understanding experience is a critical issue for a variety of professions, especially design. To understand experience and the user experience that results from interacting with products, designers conduct situated research activities focused on the interactions between people and products, and the experience that results. This paper attempts to clarify experience in interactive systems. We characterize current approaches to experience from a number of disciplines, and present a framework for designing experience for interactive system. We show how the framework can be applied by members of a multidisciplinary team to understand and generate the kinds of interactions and experiences new product and system designs might offer.

A stage-based model of personal informatics systems

People strive to obtain self-knowledge. A class of systems called personal informatics is appearing that help people collect and reflect on personal information. However, there is no comprehensive list of problems that users experience using these systems, and no guidance for making these systems more effective. To address this, we conducted surveys and interviews with people who collect and reflect on personal information. We derived a stage-based model of personal informatics systems composed of five stages (preparation, collection, integration, reflection, and action) and identified barriers in each of the stages. These stages have four essential properties: barriers cascade to later stages; they are iterative; they are user-driven and/or system-driven; and they are uni-faceted or multi-faceted. From these properties, we recommend that personal informatics systems should 1) be designed in a holistic manner across the stages; 2) allow iteration between stages; 3) apply an appropriate balance of automated technology and user control within each stage to facilitate the user experience; and 4) explore support for associating multiple facets of peoples lives to enrich the value of systems.

The building blocks of experience: an early framework for interaction designers

Design activity has recently attempted to embrace designing the user experience. Designers need to demystify how we design for user experience and how the products we design achieve specific user experience goals. This paper proposes an initial framework for understanding experience as it relates to user-product interactions. We propose a system for talking about experience, and look at what influences experience and qualities of experience. The framework is presented as a tool to understand what kinds of experiences products evoke.

Predicting human interruptibility with sensors

A person seeking another persons attention is normally able to quickly assess how interruptible the other person currently is. Such assessments allow behavior that we consider natural, socially appropriate, or simply polite. This is in sharp contrast to current computer and communication systems, which are largely unaware of the social situations surrounding their usage and the impact that their actions have on these situations. If systems could model human interruptibility, they could use this information to negotiate interruptions at appropriate times, thus improving human computer interaction.This article presents a series of studies that quantitatively demonstrate that simple sensors can support the construction of models that estimate human interruptibility as well as people do. These models can be constructed without using complex sensors, such as vision-based techniques, and therefore their use in everyday office environments is both practical and affordable. Although currently based on a demographically limited sample, our results indicate a substantial opportunity for future research to validate these results over larger groups of office workers. Our results also motivate the development of systems that use these models to negotiate interruptions at socially appropriate times.

All robots are not created equal: the design and perception of humanoid robot heads

This paper presents design research conducted as part of a larger project on human-robot interaction. The primary goal of this study was to come to an initial understanding of what features and dimensions of a humanoid robots face most dramatically contribute to peoples perception of its humanness. To answer this question we analyzed 48 robots and conducted surveys to measure peoples perception of each robots humanness. Through our research we found that the presence of certain features, the dimensions of the head, and the total number of facial features heavily influence the perception of humanness in robot heads. This paper presents our findings and initial guidelines for the design of humanoid robot heads.

Predicting human interruptibility with sensors: a Wizard of Oz feasibility study

A person seeking someone elses attention is normally able to quickly assess how interruptible they are. This assessment allows for behavior we perceive as natural, socially appropriate, or simply polite. On the other hand, todays computer systems are almost entirely oblivious to the human world they operate in, and typically have no way to take into account the interruptibility of the user. This paper presents a Wizard of Oz study exploring whether, and how, robust sensor-based predictions of interruptibility might be constructed, which sensors might be most useful to such predictions, and how simple such sensors might be.The study simulates a range of possible sensors through human coding of audio and video recordings. Experience sampling is used to simultaneously collect randomly distributed self-reports of interruptibility. Based on these simulated sensors, we construct statistical models predicting human interruptibility and compare their predictions with the collected self-report data. The results of these models, although covering a demographically limited sample, are very promising, with the overall accuracy of several models reaching about 78%. Additionally, a model tuned to avoiding unwanted interruptions does so for 90% of its predictions, while retaining 75% overall accuracy.

An analysis and critique of Research through Design : towards a formalization of a research approach

The field of HCI is experiencing a growing interest in Research through Design (RtD), a research approach that employs methods and processes from design practice as a legitimate method of inquiry. We are interested in expanding and formalizing this research approach, and understanding how knowledge, or theory, is generated from this type of design research. We conducted interviews with 12 leading HCI design researchers, asking them about design research, design theory, and RtD specifically. They were easily able to identify different types of design research and design theory from contemporary and historical design research efforts, and believed that RtD might be one of the most important contributions of design researchers to the larger research community. We further examined three historical RtD projects that were repeatedly mentioned in the interviews, and performed a critique of current RtD practices within the HCI research and interaction design communities. While our critique summarizes the problems, it also shows possible directions for further developments and refinements of the approach.

Intelligent assistive technology applications to dementia care: current capabilities, limitations, and future challenges.

The number of older Americans afflicted by Alzheimer disease and related dementias will triple to 13 million persons by 2050, thus greatly increasing healthcare needs. An approach to this emerging crisis is the development and deployment of intelligent assistive technologies that compensate for the specific physical and cognitive deficits of older adults with dementia, and thereby also reduce caregiver burden. The authors conducted an extensive search of the computer science, engineering, and medical databases to review intelligent cognitive devices, physiologic and environmental sensors, and advanced integrated sensor networks that may find future applications in dementia care. Review of the extant literature reveals an overwhelming focus on the physical disability of younger persons with typically nonprogressive anoxic and traumatic brain injuries, with few clinical studies specifically involving persons with dementia. A discussion of the specific capabilities, strengths, and limitations of each technology is followed by an overview of research methodological challenges that must be addressed to achieve measurable progress to meet the healthcare needs of an aging America.

A Storytelling Robot: Modeling and Evaluation of Human-like Gaze Behavior

Engaging storytelling is a necessary skill for humanoid robots if they are to be used in education and entertainment applications. Storytelling requires that the humanoid robot be aware of its audience and able to direct its gaze in a natural way. In this paper, we explore how human gaze can be modeled and implemented on a humanoid robot to create a natural, human-like behavior for storytelling. Our gaze model integrates data collected from a human storyteller and a discourse structure model developed by Cassell and her colleagues for human-like conversational agents (1994). We used this model to direct the gaze of a humanoid robot, Hondas ASIMO, as he recited a Japanese fairy tale using a pre-recorded human voice. We assessed the efficacy of this gaze algorithm by manipulating the frequency of ASIMOs gaze between two participants and used pre and post questionnaires to assess whether participants evaluated the robot more positively and did better on a recall task when ASIMO looked at them more. We found that participants performed significantly better in recalling ASIMOs story when the robot looked at them more. Our results also showed significant differences in how men and women evaluated ASIMO based on the frequency of gaze they received from the robot. Our study adds to the growing evidence that there are many commonalities between human-human communication and human-robot communication