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<Paper uid="W98-1430">
  <Title>SYSTEM DEMONSTRATION CONTENT PLANNING AS THE BASIS FOR AN * *INTELLIGENT*TUTORING SYSTEM</Title>
  <Section position="1" start_page="0" end_page="0" type="metho">
    <SectionTitle>
SYSTEM DEMONSTRATION
CONTENT PLANNING AS THE BASIS FOR AN
* *INTELLIGENT*TUTORING SYSTEM
</SectionTitle>
    <Paragraph position="0"> http ://www. csam. lit. edu/~circsim</Paragraph>
  </Section>
  <Section position="2" start_page="0" end_page="0" type="metho">
    <SectionTitle>
1. INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> The negative feedback loop which maintains a steady blood pressure in the human body is one of the more difficult topics for first-year medical students to master. CIRCSIM-Tutor v. 3 is the latest in a series of dialogue-based intelligent tutoring systems intended to help students master the concepts involved.</Paragraph>
    <Paragraph position="1"> CIRCSIM-Tutor v. 3 differs from many other ITSs in that text planning is an integral part of the system rather than part of a natural-language front-end. It contains a global planner whose fundamental goal is &amp;quot;generate a conversation resulting in the student knowing &lt;concepts&gt;&amp;quot; rather than &amp;quot;teach &lt;concepts&gt;.&amp;quot; Constraints on the plan operators can be used to take a variety Of knowledge Sources into account, including the tutorial history, the domain knowledge base and a student model.</Paragraph>
    <Paragraph position="2"> To ensure that CIP, CSiM-Tutor is useful in the classroom, we have paid particular attention to broad coverage of the domain, maintenance of a coherent conversation and fast response time. We often need to model what human tutors do without a deep model of why they say what they say. As a result our content planner uses a schema-based.representation which allows us to control the decomposition and sequence of goals. Through the use of a reactive planning architecture, we can update our plan based on the student's answers. Text realization is accomplished via a high-level template mechanism based on a mini-syntax of potential answers. Botl! the content schemata and the text realization templates are based on detailed modeling of the dialogu e patterns of expert human tutors.</Paragraph>
  </Section>
  <Section position="3" start_page="0" end_page="281" type="metho">
    <SectionTitle>
2, DESCRIPTION OF DOMAIN AND USER INTERFACE
</SectionTitle>
    <Paragraph position="0"> CIRCSIM-Tut0r helps students practice the reasoning they have learned in Introduction to Physiology.</Paragraph>
    <Paragraph position="1"> Students are given a simplified qualitative model of the heart, followed by a series of problems which utilize the model. In each problem, an incident such as the administration of a drug affects the processing This work was supported by the Cognitive Science Program, Office of Naval Research under Grant No. N0001494--1-0338 to Illinois Institute Of Technology. The content does not reflect the position or policy of the government and no official endorsement should be inferred.</Paragraph>
    <Paragraph position="2"> *This work was performed while Reva Freedman was at the Illinois Institute of Technology.</Paragraph>
    <Paragraph position="4"> of file heart. The student is then asked to predict tile direction of change of seven core variables: HR: Heart rate (beats/min) MAP: IS: Inotropic state, a measure of the SV: heart's contractile ability &amp;quot; CVP: TPR: Total peripheral *resistance CO: The qualitative causal relationships between the core variables (i.e. an increase in X causes an Mean arterial pressure Stroke volume (vol/beat) Central venous pressure Cardiac output (vol/min) increase/decrease in Y) are shown on tlie left-hand side of Figure I. In this diagram, NS = nervous system and Baro = the baroreceptors in the neck which recognize a change in blood pressure. A finer-grained knowledge representation is also available for the tutor to usewhen needed. A section of this knowledge base, the leg from the nervous system to TPR, is shown on tlie right-hand side of Figure 1. Each variable must be Predicted at three points: the DR or direct response phase immediately after the incident, the RR or reflex response phase, which shows the effect of the nervous system, and the SS or steady state phase after a new steady state has emerged. After the predictions are made, * the tutor engages the student in a dialogue to help the student learn the correct answers and file concepts underlying them. The basic user interface is tile screen shown in Figure 2. A description of the current problem is shown at the top of the screen. The left-hand Side of the screen contains a table where the student can fill in predictions for tile three stages, and the right-hand side contains a window where the dialogue evolves. The student part of tile dialogue is free text. Instead of restricting what students can say, we attempt to guide them toward understandable responses through the way the questions are framed, e.g. by asking short-answer questions instead of open-ended ones. Input processing is based on finite-state transducers. Eachquestion the system can ask is associated with a transducer which can categorize and extract a variety of student answers. Often if the student just uses some of the right words, the sentence is accepted since the input processor uses very little syntax. Spelling correction, an essential in any system which allows free-text typing, is based on algorithms developed by Elmi \[1998\]. Tile transducers were coded by hand using as input both dialogues with human tutors and logs from earlier versions of CIRCSIM-Tutor.</Paragraph>
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