If a school does not meet assessment goals for two consecutive years, by law the district must offer stu dents the opportunity to transfer to a school that is meet ing its goals. Making a choice with such potential impact on a child's future is clearly monumental, yet astonishingly few parents take advantage of the opportunity. Our research has shown that a significant part of the problem arises from issues in information access and information overload, par ticularly for low socioeconomic status families. Thus we have developed an online, content-based recommender sys tem, called SmartChoice. It provides parents with school rec ommendations for individual students based on parents' pref erences and students' needs, interests, abilities, and talents.

Sponsored by the Association for the Advancement of Artificial Intelligence and ACM SIGART Collocated with AAAI-10 AAAI and ACM/SIGART invite students to apply for the Fifteenth AAAI/SIGART Doctoral Consortium. The Doctoral Consortium (DC) provides an opportunity for a group of Ph.D. students to discuss and explore their research interests and career objectives with a panel of established researchers in artificial intelligence. The consortium has the following objectives: (1) to provide a setting for mutual feedback on participants' current research and guidance on future research directions; (2) develop a supportive community of scholars and a spirit of collaborative research; (3) support a new generation of researchers with information and advice on academic, research, industrial, and nontraditional career paths; and (4) contribute to the conference goals through interaction with other researchers and participation in conference events. The Doctoral Consortium will be held as a workshop on July 11-12, 2010, immediately before the start of the main AAAI conference. Student participants in the Doctoral Consortium will receive complimentary conference registration and a fixed allowance for travel/housing.

International Florida Artificial Intelligence Research Society Conference (FLAIRS-23) was held May 19-21, 2010, at the Shores Resort and Spa in Daytona Beach Shores, Florida, USA. The conference featured an exciting lineup of invited speakers, a general conference track on artificial intelligence research, and numerous special tracks. The conference chair was David Wilson from the University of North Carolina at Charlotte. The program cochairs were R. Charles Murray from Carnegie Learning and Hans W. Guesgen from Massey University in New Zealand. The special tracks coordinator was Philip McCarthy from the University of Memphis.

The titles of the seven symposia were Artificial Intelligence for Development; Cognitive Shape Processing; Educational Robotics and Beyond: Design and Evaluation; Embedded Reasoning: Intelligence in Embedded Systems; Intelligent Information Privacy Management; It's All in the Timing: Representing and Reasoning about Time in Interactive Behavior; and Linked Data Meets Artificial Intelligence. The Symposium on Artificial Intelligence for Development was organized to explore opportunities for using machine learning, inference, planning, and perception to enhance the quality of lives of disadvantaged populations. Over the last several years, a community of researchers with interest in applying computing and communication technologies in developing regions has come together under the label Information and Communication Technology for Development (ICT-D). However, ICT-D efforts to date have rarely focused on opportunities to harness machine learning, reasoning, and perception to create intelligent systems, services, models, and analyses. Beyond exploring research projects and directions, we hoped that bringing together a critical mass of researchers who share an interest in applying AI to development challenges would serve to help launch a new vibrant subfield of ICT-D on artificial intelligence for development (AID).

The Association for the Advancement of Artificial Intelligence was pleased to present the 2010 Fall Symposium Series, held Thursday through Saturday, November 11-13, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the eight symposia are as follows: (1) Cognitive and Metacognitive Educational Systems; (2) Commonsense Knowledge; (3) Complex Adaptive Systems: Resilience, Robustness, and Evolvability; (4) Computational Models of Narrative; (5) Dialog with Robots; (6) Manifold Learning and Its Applications; (7) Proactive Assistant Agents; and (8) Quantum Informatics for Cognitive, Social, and Semantic Processes. The highlights of each symposium are presented in this report. The Cognitive and Metacognitive Educational Systems (MCES) AAAI symposium, held in November 2010, was the second edition of this successful AAAI symposium. The idea for the symposium stemmed from several theoretical, conceptual, empirical, and applied considerations about the role of metacognition and self-regulation when learning with computer-based learning environments (CBLEs). A related goal was the design and implementation issues associated with metacognitive educational systems. MCES implemented as CBLEs are designed to interact with users and support their learning and decision-making processes. A critical component of good decision making is self-regulation. The primary aim of this symposium was to continue the discussion started in 2009 on some of the previous considerations and to enhance the discussions with some new ones: What are the theoretical foundations and how are they articulated in CBLEs? Is it possible to develop a unified framework for all metacognitive educational systems? What are the necessary characteristics of these systems to support metacognition? To what extent does the educational system itself have to exhibit metacognitive behaviors, and how are these behaviors organized and enacted to support learning? What are the main aspects of metacognition, self-regulation skills, emotions, and motivations that influence the learning process? What does it mean to be metacognitive, and how can one learn to be metacognitive? Can MCES actually foster learners to be self-regulating agents? How can an MCES be autonomous and increase its knowledge to match the learners' evolving skills and knowledge?

It uses statistical language-classification technology for mapping from a user's text input to system responses. NPCEditor provides a user-friendly editor for creating effective virtual humans quickly. It has been deployed as a part of various virtual human systems in several applications. Imagine talking to a computer system that looks and acts almost human -- it converses, understands, can rea son, and can exhibit emotion. As an example, recall such computer characters created by Hollywood moviemakers as the librarian in Time Machine, the holographic professor in I Robot, and of course, the holodeck characters in numer ous Star Trek: The Next Generation episodes.

In this article we give a summary of three components of the exhibition: the Small-Scale Manipulation Challenge: Robotic Chess; the Learning by Demonstration Challenge; and the Education Track. We also describe the participating teams, highlight the research questions they tackled, and briefly describe the systems they demonstrated. The program has a long tradition of demonstrating innovative research at the intersection of robotics and artificial intelligence. In both the workshop and exhibition portions of the event, we strive to have the robotics program be a venue that pushes the science of embodied AI forward. Over the past few years, a central point of the event has been the discussion of common robot platforms and software, with the primary goal of focusing the research community's energy toward common "challenge" tasks.

The Association for the Advancement of Artificial Intelligence was pleased to present the 2011 Fall Symposium Series, held Friday through Sunday, November 4-6, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia are as follows: (1) Advances in Cognitive Systems; (2) Building Representations of Common Ground with Intelligent Agents; (3) Complex Adaptive Systems: Energy, Information, and Intelligence; (4) Multiagent Coordination under Uncertainty; (5) Open Government Knowledge: AI Opportunities and Challenges; (6) Question Generation; and (7) Robot-Human Teamwork in Dynamic Adverse Environments. The highlights of each symposium are presented in this report. The goal of the AAAI Fall Symposium on Advances in Cognitive Systems was to bring together researchers who are interested in developing intelligent systems that demonstrate the full range of human cognitive abilities and to report progress on this daunting task. The original aims of artificial intelligence, when it was launched in the late 1950s, were to explain intelligence in computational terms and to reproduce the entire range of human cognitive abilities in computational artifacts. Although the field has seen impressive advances in the last few decades, many researchers have, in the process, forgotten or abandoned these important goals. The purpose of the Fall Symposium on Advances in Cognitive Systems was to bring together scientists who remained committed to AI's original vision. The meeting received 50 paper submissions and it was attended by more than 75 participants, suggesting that there remains substantial interest in this view on the discipline. Research in cognitive systems, as reflected by the contributors to the meeting, differs from what has become mainstream AI in five basic ways.

In this article we report on the exhibits and challenges shown at the AAAI 2011 Robotics Program in San Francisco. The event included a broad demonstration of innovative research at the intersection of robotics and artificial intelligence. Through these multiyear challenge events, our goal has been to focus the research community's energy toward common platforms and common problems to work toward the greater goal of embodied AI. The program has a long tradition of demonstrating innovative research at the intersection of robotics and artificial intelligence. In both the workshop and exhibition portions of the event, we strive to have the robotics program be a venue that pushes the science of embodied AI forward. Over the past few years, a central point of the event has been the discussion of common robot platforms and software, with the primary goal of focusing the research community's energy toward common "challenge" tasks. On the day before the exhibition the participants convened a workshop of 18 short talks. Each track's exhibitors presented a summary of their exhibit. In addition, four guest speakers provided a broader context for all of the exhibitors' efforts. The first guest speaker was the National Science Foundation's Sven Koenig, who highlighted several federal programs that support projects in embodied intelligence. Koenig also provided insights into some of these program's specific priorities, such as international collaborations and educational engagement. Guest speakers from Willow Garage and Bosch presented cutting-edge work with the PR2, Willow's mobile two-arm manipulator platform. Bosch detailed its Remote Lab, which provides researchers anywhere with full access to the sensing and mobile manipulation capabilities of a PR2. Willow Garage featured some of its most recent work, in which point clouds (Anderson et al. 2011) are parsed not only to build generic three-dimensional scene models but also task-specific structures such as cabinet and drawer handles. Those structures, in turn, seed the automatic creation of task sequences for object retrieval in unconstrained human environments. Nataniel Dukan of Nao Robotics presented the workshop's final guest talk, a broad overview of humanoid robotics's current resources, along with a compelling vision for where those technologies will be in the next three to five years. Without providing specifics of Aldebaran's unannounced plans, Dukan hinted that the actuation and sensing needed for com-

In this article, we introduce Mechanix, a sketch-based deployed tutoring system for engineering students enrolled in statics courses. Our system not only allows students to enter planar truss and free-body diagrams into the system, just as they would with pencil and paper, but our system also checks the student's work against a hand-drawn answer entered by the instructor, and then returns immediate and detailed feedback to the student. Students are allowed to correct any errors in their work and resubmit until the entire content is correct and thus all of the objectives are learned. Since Mechanix facilitates the grading and feedback processes, instructors are now able to assign more free-response questions, increasing teacher's knowledge of student comprehension. Furthermore, the iterative correction process allows students to learn during a test, rather than simply display memorized information.