CIRCSIM-Tutor
Published 1 January 1997Open access
Martha Evens, Ru-Charn Chang, Yoon Hee Lee, Leem Seop Shim, Chong Woo Woo, Yuemei Zhang
Citations71
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
CIRCSIM-Tutor version 2, a dialogue-based intelligent tutoring system (ITS), is nearly five years old and can handle a variety of syntactic constructions and lexical items, including sentence fragments and misspelled words.
Abstract
CIRCSIM-Tutor version 2, a dialogue-based intelligent tutoring system (ITS), is nearly five years old. It conducts a conversation with a student to help the student learn to solve a class of problems in cardiovascular physiology dealing with the regulation of blood pressure. It uses natural language for both input and output, and can handle a variety of syntactic constructions and lexical items, including sentence fragments and misspelled words.
Keywords
Computer Science
Journal of the Learning SciencesHinting as a Tactic in One-on-One Tutoring
143 Citations1996Gregory D. Hume, Joel Michael +2 more
Hinting is triggered by student errors but ceases when it appears that the student is unable to respond appropriately, and the surface structure of hints is complex and varied, reflecting the fact that the utterances making up hints often serve multiple functions.
Spelling correction using context
40 Citations1998Mohammad Ali Elmi, Martha Evens
A spelling correction system that functions as part of an intelligent tutor that carries on a natural language dialogue with its users to speed up the process of searching the lexicon.
Interaction of discourse planning, instructional planning and dialogue management in an interactive tutoring system
28 Citations1996Gilbert K. Krulee, Reva Freedman
An abstract model of tutorial dialogue of human tutors is developed in order to put text generation for ITSs on solid theoretical footing and is expected to produce longer, more complex, and more varied dialogues than previous work.
Dynamic instructional planning for an intelligent physiology tutoring system
24 Citations2002Chong Woo Woo, Martha Evens +2 more
An intelligent tutoring system (ITS) that will assist first-year medical students in learning the causal relationships between the parameters of the circulatory system and in solving problems of disturbances to the system is discussed.
Knowledge-based discourse generation for an intelligent tutoring system
8 Citations1992Yuemei Zhang
The definition of the tutoring discourse as coherent, integrative, and productive discourse was carried out and it was concluded that the student knowledge status, the dialogue history, and the domain knowledge determine what kind of discourse should be generated.
Acknowledgments in Tutorial Dialogue
7 Citations1997Stefan Brandle, Martha Evens
It is the thesis that an acknowledgment is anything that signals closure or lack of closure of a joint action, and shows promise as a guide for synthesizing tutorial dialogues in Intelligent Tutoring Systems.
Expert SystemsNatural language interface for an expert system
5 Citations1998Yoonhee Lee, Martha Evens
This paper provides complete analysis of natural language interface from the screen manager to the parser/understander, even though it has some limitations.
Surface-level generation of tutorial dialogue using a specially developed lexical functional grammar and lexicon
4 Citations1992Ru-Charn Chang
This thesis describes the design and development of a surface-level text generation system for an intelligent tutoring system for cardiovascular physiology, called CIRCSIM-TUTOR that assists first year medical students to master the negative feedback system that regulates blood pressure.
Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)A Multi-Level Dynamic Instructional Planner for an Intelligent Physiology Tutoring System
4 Citations1992Chong Woo Woo
The design and development of an instructional planner for an intelligent tutoring system for cardiovascular physiology that assists medical students to learn the causal relationships between the parameters of the circulatory system, to understand how a negative feedback system works, and to solve problems involving disturbances to he system are described.