Title : Rimac : A Natural - language Dialogue System that Engages Students in Deep Reasoning
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Title Page Not included in page count. Abstract Body Limit 5 pages single spaced.
منابع مشابه
Interactive Event: The Rimac Tutor - A Simulation of the Highly Interactive Nature of Human Tutorial Dialogue
Rimac is a natural-language intelligent tutoring system that engages students in dialogues that address physics concepts and principles, after they have solved quantitative physics problems. Much research has been devoted to identifying features of tutorial dialogue that can explain its effectiveness (e.g., [1]), so that these features can be simulated in natural-language tutoring systems. One ...
متن کاملPilot Test of a Natural-Language Tutoring System for Physics That Simulates the Highly Interactive Nature of Human Tutoring
This poster describes Rimac, a natural-language tutoring system that engages students in dialogues that address physics concepts and principles, after students have solved quantitative physics problems. We summarize our approach to deriving decision rules that simulate the highly interactive nature of human tutoring, and describe a pilot test that compares two versions of Rimac: an experimental...
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We explore the effectiveness of a simple algorithm for adaptively deciding whether to further decompose a step in a line of reasoning during tutorial dialogue. We compare two versions of a tutorial dialogue system, Rimac: one that always decomposes a step to its simplest sub-steps and one that adaptively decides to decompose a step based on a student’s pre-test assessment. We hypothesize that s...
متن کاملIs a Dialogue-Based Tutoring System that Emulates Helpful Co-constructed Relations During Human Tutoring Effective?
We present an initial field evaluation of Rimac, a natural-language tutoring system which implements decision rules that simulate the highly interactive nature of human tutoring. We compared this rule-driven version of the tutor with a non-rule-driven control in high school physics classes. Although students learned from both versions of the system, the experimental group outperformed the contr...
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We describe two tutorial dialogue systems that adapt techniques from task-oriented dialogue systems to tutorial dialogue. Both systems employ the same reusable deep natural language understanding and generation components to interpret students' written utterances and to automatically generate adaptive tutorial responses, with separate domain reasoners to provide the necessary knowledge about th...
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تاریخ انتشار 2010