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TOWARDS BUILDING AN INTELLIGENT REVISION ASSISTANT FOR ARGUMENTATIVE WRITINGS

Zhang, Fan (2017) TOWARDS BUILDING AN INTELLIGENT REVISION ASSISTANT FOR ARGUMENTATIVE WRITINGS. Doctoral Dissertation, University of Pittsburgh.

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Abstract

Current intelligent writing assistance tools (e.g. Grammarly, Turnitin, etc.) typically work by locating the problems of essays for users (grammar, spelling, argument, etc.) and providing possible solutions. These tools focus on providing feedback on a single draft, while ignoring feedback on an author’s changes between drafts (revision). This thesis argues that it is also important to provide feedback on authors’ revision, as such information can not only improve the quality of the writing but also improve the rewriting skill of the authors. Thus, it is desirable to build an intelligent assistant that focuses on providing feedback to revisions.
This thesis presents work from two perspectives towards the building of such an assistant: 1) a study of the revision’s impact on writings, which includes the development of a sentence-level revision schema, the annotation of corpora based on the schema and data analysis on the created corpora; a prototype revision assistant was built to provide revision feedback based on the schema and a user study was conducted to investigate whether the assistant could influence the users’ rewriting behaviors. 2) the development of algorithms for automatic revision identification, which includes the automatic extraction of the revised content and the automatic classification of revision types; we first investigated the two problems separately in a pipeline manner and then explored a joint approach that solves the two problems at the same time.


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Details

Item Type: University of Pittsburgh ETD
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Zhang, Fanfaz23@pitt.edufaz23
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairLitman, Dianelitman@cs.pitt.edu
Committee MemberHwa, Rebeccahwa@cs.pitt.edu
Committee MemberKovashka, Adrianakovashka@cs.pitt.edu
Committee MemberSchunn, Christianschunn@pitt.edu
Date: 28 September 2017
Date Type: Publication
Defense Date: 7 April 2017
Approval Date: 28 September 2017
Submission Date: 11 June 2017
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 152
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: revision, argumentative writing, automatic identification, ArgRewrite
Date Deposited: 29 Sep 2017 01:21
Last Modified: 29 Sep 2017 01:21
URI: http://d-scholarship.pitt.edu/id/eprint/32428

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