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MooreJ_Diagnosing Natural Language Answers.pdf117.63 kBAdobe PDFView/Open
Title: Diagnosing natural language answers to support adaptive tutoring
Authors: Dzikovska, Myroslava
Campbell, Gwendolyn
Callaway, Charles
Steinhauser, Natalie
Farrow, Elaine
Moore, Johanna D.
Butler, Leslie
Matheson, Colin
Issue Date: 1-Nov-2010
Journal Title: Proceedings of the 21st FLAIRS Conference
Abstract: Understanding answers to open-ended explanation questions is important in intelligent tutoring systems. Existing systems use natural language techniques in essay analysis, but revert to scripted interaction with short-answer questions during remediation, making adapting dialogue to individual students difficult. We describe a corpus study that shows that there is a relationship between the types of faulty answers and the remediation strategies that tutors use; that human tutors respond differently to different kinds of correct answers; and that re-stating correct answers is associated with improved learning. We describe a design for a diagnoser based on this study that supports remediation in open-ended questions and provides an analysis of natural language answers that enables adaptive generation of tutorial feedback for both correct and faulty answers.
Appears in Collections:Informatics Publications

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