In this paper, we explore using large digital displays in combination with a personal mobile application to publicly and privately encourage people to make healthy choices. We designed, built, and deployed an experimental system called Lunch Line that promoted healthy eating. Lunch Line includes a public display that enables passersby to view the reported eating behavior of a group of people and take on daily "food challenges," and a mobile web application that allows users to record personal food choices, report challenge achievement, and compare their choices with other users and with USDA recommendations. Results from a 3-week field evaluation at a company cafeteria showed that our integrated system was effective in drawing public attention, delivering challenges, enabling self-tracking and self-reflection, and providing feedback on personal and group choices. We share lessons on how to design future systems that integrate situated public displays and personal mobile devices to encourage healthy choices.

Today, commodity technologies like mobile phones - once symbols of status and wealth - have become deeply woven into social and economic participation in Western society. Despite the pervasiveness of these technologies, there remain groups who may not have extensive access to them but who are nonetheless deeply affected by their presence in everyday life. In light of this, we designed, built, and deployed a ubiquitous computing system for one such overlooked group: the staff and residents at a shelter for homeless mothers. Our system connects mobile phones, a shared display, and a Web application to help staff and residents stay connected. We report on the adoption and use of this system over the course of a 30 week deployment, discussing the substantial impact our system had on shelter life and the broader implications for such socio-technical systems that sit at the juncture of social action and organizational coordination.

The design and use of Information and Communication Technology (ICT) has now evolved beyond its workplace origins to the wider public, expanding to people who live at the margins of contemporary society. Through field work and participatory co-design with homeless shelter residents and care providers we have explored design at the common boundary of these two "publics." We describe the design of the Community Resource Messenger (CRM), an ICT that supports both those in need and those attempting to provide care in a challenging environment. The CRM consists of three components: 1) a message center that pools messages to and from mobile users into a shared, persistent forum; 2) a text and voice messaging gateway linking the mobile phones of the homeless with the web-enabled computer facilities of the care providers; 3) a shared message display accessible from mobile texting, voice, e-mail, and the web, helping the two groups communicate and coordinate for mutual good. By democratizing design and use of technology at the margins of society, we aim to engage an entire "urban network," enabling shared awareness and collective action in each public.

This paper describes our experiences deploying a recommender system for a mobile phone-based knowledge sharing application to farmers in rural India. Users of the system record questions and call back for answers left by other users and experts. We used collaborative filtering to derive relevant content for each user based on historical navigation patterns of the community. An empirical analysis of behavioral and interview data reveals key issues for future mobile recommender systems in developing regions of the world.

Recent growth in broadband access and proliferation of small personal devices that capture images and videos has led to explosive growth of multimedia content available everywhere - from personal disks to the Web. While digital media capture and upload has become nearly universal with newer device technology, there is still a need for better tools and technologies to search large collections of multimedia data and to find and deliver the right content to a user according to her current needs and preferences. A renewed focus on the subjective dimension in the multimedia lifecycle, from creation, distribution, to delivery and consumption, is required to address this need beyond what is feasible today. Integration of the subjective aspects of the media itself - its affective, perceptual, and physiological potential (both intended and achieved), together with those of the users themselves will allow for personalizing the content access, beyond today's facility. This integration, transforming the traditional multimedia information retrieval (MIR) indexes to more effectively answer specific user needs, will allow a richer degree of personalization predicated on user intention and mode of interaction, relationship to the producer, content of the media, and their history and lifestyle. In this paper, we identify the challenges in achieving this integration, current approaches to interpreting content creation processes, to user modelling and profiling, and to personalized content selection, and we detail future directions. The structure of the paper is as follows: In Section I, we introduce the problem and present some definitions. In Section II, we present a review of the aspects of personalized content and current approaches for the same. Section III discusses the problem of obtaining metadata that is required for personalized media creation and present eMediate as a case study of an integrated media capture environment. Section IV presents the MAGIC system as a case study of capturing effective descriptive data and putting users first in distributed learning delivery. The aspects of modelling the user are presented as a case study in using user's personality as a way to personalize summaries in Section V. Finally, Section VI concludes the paper with a discussion on the emerging challenges and the open problems.

The "Tools for Automatic Generation of Learning Object Metadata" project addresses the requirement of developing advanced distributed learning delivery architecture and services for a large US government agency. We have developed a Webbased system called MAGIC (Metadata Automated Generation for Instructional Content) to assist content authors and course developers in generating metadata for learning objects and information assets to enable wider reuse of these objects across departments and organizations. Using the MAGIC system, content authors review and edit automatically-generated metadata sufficient to register and describe their assets for use and discovery in current and future distributed learning applications complying with the ADL SCORM standard. Course developers can use the system to assist in the conversion of existing courses to SCORM format or in developing new SCORM courses. The MAGIC system includes software tools to analyze and extract descriptive metadata from instructional videos, training documents, and other information assets. The tools generate some of the most critical SCORM metadata completely automatically. Benefits of MAGIC include easier reuse and repurposing, improved interoperability, and more timely registration of content for use by course developers. In this paper, we describe the system architecture, analysis tools developed, and services supported. A live demonstration of the system illustrating several use cases of the system will be presented at the conference, with a discussion of results from user studies and evaluation of the system.

This paper presents our latest work on building a system called MAGIC (Metadata Automated Generation for Instructional Content) that will automatically identify segments and generate critical metadata conforming with the SCORM (Sharable Content Object Reference Model) standard for instructional content. Various content analytics engines are utilized to automatically generate key metadata, which include audiovisual analysis modules that recognize semantic sound categories and identify narrators and informative text segments; text analysis modules that extract title, keywords and summary from text documents; and a text categorizer that classifies a document according to a pre-generated taxonomy. With MAGIC, instructional content developers can generate and edit SCORM metadata to richly describe their content asset for use in distributed learning applications. Experimental results obtained from collections of real data from targeted user communities will be presented.

In this paper, we describe an algorithm to generate textual summaries of discussion groups. Our system combines sentences extracted from individual postings into variable-length summaries by utilizing the hierarchical discourse context provided by discussion threads. We have incorporated this algorithm into a Web-based application called IDS (Interactive Discussion Summarizer).

We are building a collaborative learning environement that supports teams of students as they collaborate synchronously and remotely to solve situated, multi-step problems involving algebraic modeling. Our system, named Algebra Jam, provides a set of tools to help students overcome two of the most serious impediments to successful collaboration: establishing common ground and maintaining group focus. These tools include tethered and untethered modes of operation including discrepancy notification, a goal-oriented team blackboard, object-oriented chat with collabicons, reification of problem solving roles, and the optional inclusion of a tutor agent as a virtual team participant. The tutor agent not only offers help and feedback on problem solving actions but also accumulates evidence about individual and group problem solving performance in a Bayesian inference network. The system is envisioned as a testbed for developing theories of teaming.

Users of complex applications need advice, assistance, and feedback while they work. We are experimenting with “adjunct” user agents that are aware of the history of interaction surrounding the accomplishment of a task. This paper describes an architectural framework for constructing these agents. Using this framework, we have implemented a critiquing system that can give task-oriented critiques to trainees while they use operating system tools and software applications. Our approach is generic, widely applicable, and works directly with off-the-shelf software packages.