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The Effect of Question-Answer Relationships on Ninth-Grade Students' Ability to Accurately Answer Comprehension Questions
Title
The Effect of Question-Answer Relationships on Ninth-Grade Students' Ability to Accurately Answer Comprehension Questions.
Creator
Stafford, Tammy, Zygouris-Coe, Vassiliki, Xu, Lihua, Boote, David, Wilson, Nance, University of Central Florida
Abstract / Description
This experimental research study examined the effects of the Question-Answer Relationships (QAR) taxonomy on ninth-grade students' ability to answer comprehension questions. Participants included 32 incoming ninth-grade students who were required to attend summer school due to poor attendance, grades, and/or standardized test scores. Participants were randomly assigned to experimental and control groups. Experimental group participants received one week of initial strategy instruction...
Show moreThis experimental research study examined the effects of the Question-Answer Relationships (QAR) taxonomy on ninth-grade students' ability to answer comprehension questions. Participants included 32 incoming ninth-grade students who were required to attend summer school due to poor attendance, grades, and/or standardized test scores. Participants were randomly assigned to experimental and control groups. Experimental group participants received one week of initial strategy instruction followed by three weeks of maintenance activities. Results indicated that the strategy had a negative effect on students' question-answering ability and raised questions regarding comprehension instruction, length of interventions, and the role of scaffolded support for a target population of adolescent readers. Discussion of the results revolves around interventions, QAR instruction, reading ability, and motivation of the participants.
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Date Issued
2012
Identifier
CFE0004605, ucf:49921
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004605
SYNTAX-BASED CONCEPT EXTRACTION FOR QUESTION ANSWERING
Title
SYNTAX-BASED CONCEPT EXTRACTION FOR QUESTION ANSWERING.
Creator
Glinos, Demetrios, Gomez, Fernando, University of Central Florida
Abstract / Description
Question answering (QA) stands squarely along the path from document retrieval to text understanding. As an area of research interest, it serves as a proving ground where strategies for document processing, knowledge representation, question analysis, and answer extraction may be evaluated in real world information extraction contexts. The task is to go beyond the representation of text documents as "bags of words" or data blobs that can be scanned for keyword combinations and word...
Show moreQuestion answering (QA) stands squarely along the path from document retrieval to text understanding. As an area of research interest, it serves as a proving ground where strategies for document processing, knowledge representation, question analysis, and answer extraction may be evaluated in real world information extraction contexts. The task is to go beyond the representation of text documents as "bags of words" or data blobs that can be scanned for keyword combinations and word collocations in the manner of internet search engines. Instead, the goal is to recognize and extract the semantic content of the text, and to organize it in a manner that supports reasoning about the concepts represented. The issue presented is how to obtain and query such a structure without either a predefined set of concepts or a predefined set of relationships among concepts. This research investigates a means for acquiring from text documents both the underlying concepts and their interrelationships. Specifically, a syntax-based formalism for representing atomic propositions that are extracted from text documents is presented, together with a method for constructing a network of concept nodes for indexing such logical forms based on the discourse entities they contain. It is shown that meaningful questions can be decomposed into Boolean combinations of question patterns using the same formalism, with free variables representing the desired answers. It is further shown that this formalism can be used for robust question answering using the concept network and WordNet synonym, hypernym, hyponym, and antonym relationships. This formalism was implemented in the Semantic Extractor (SEMEX) research tool and was tested against the factoid questions from the 2005 Text Retrieval Conference (TREC), which operated upon the AQUAINT corpus of newswire documents. After adjusting for the limitations of the tool and the document set, correct answers were found for approximately fifty percent of the questions analyzed, which compares favorably with other question answering systems.
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Date Issued
2006
Identifier
CFE0000985, ucf:46711
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000985