Chaudhri, Vinay K. (SRI International) | Cheng, Britte (SRI International) | Overtholtzer, Adam (SRI International) | Roschelle, Jeremy (SRI International) | Spaulding, Aaron (SRI International) | Clark, Peter (Vulcan Inc.) | Greaves, Mark (Pacific Northwest National Laboratory) | Gunning, Dave (Palo Alto Research Center)
Inquire Biology is a prototype of a new kind of intelligent textbook -- one that answers students' questions, engages their interest, and improves their understanding. Inquire Biology provides unique capabilities via a knowledge representation that captures conceptual knowledge from the textbook and uses inference procedures to answer students' questions. In an initial controlled experiment, community college students using the Inquire Biology prototype outperformed students using either a hardcopy or conventional E-book version of the same biology textbook. While additional research is needed to fully develop Inquire Biology, the initial prototype clearly demonstrates the promise of applying knowledge representation and question-answering technology to electronic textbooks.
Gunning, David (Vulcan, Inc.) | Chaudhri, Vinay K. (SRI International) | Clark, Peter E. (Boeing Research and Technology) | Barker, Ken (University of Texas at Austin) | Chaw, Shaw-Yi (University of Texas at Austin) | Greaves, Mark (Vulcan, Inc.) | Grosof, Benjamin (Vulcan, Inc.) | Leung, Alice (Raytheon BBN Technologies Corporation) | McDonald, David D. (Raytheon BBN Technologies Corporation) | Mishra, Sunil (SRI International) | Pacheco, John (SRI International) | Porter, Bruce (University of Texas at Austin) | Spaulding, Aaron (SRI International) | Tecuci, Dan (University of Texas at Austin) | Tien, Jing (SRI International)
In the winter, 2004 issue of AI Magazine, we reported Vulcan Inc.'s first step toward creating a question-answering system called "Digital Aristotle." The goal of that first step was to assess the state of the art in applied Knowledge Representation and Reasoning (KRR) by asking AI experts to represent 70 pages from the advanced placement (AP) chemistry syllabus and to deliver knowledge-based systems capable of answering questions from that syllabus. This paper reports the next step toward realizing a Digital Aristotle: we present the design and evaluation results for a system called AURA, which enables domain experts in physics, chemistry, and biology to author a knowledge base and that then allows a different set of users to ask novel questions against that knowledge base. These results represent a substantial advance over what we reported in 2004, both in the breadth of covered subjects and in the provision of sophisticated technologies in knowledge representation and reasoning, natural language processing, and question answering to domain experts and novice users.
When creating algorithms or systems that are supposed to be used by people, we should be able to adopt a "binocular" view of users' interaction with intelligent systems: a view that regards the design of interaction and the design of intelligent algorithms as interrelated parts of a single design problem. This special issue offers a coherent set of articles on two levels of generality that illustrate the binocular view and help readers to adopt it.