ArgRewrite A tool that helps you rewrite!

This project evaluates the viability of revision as a pedagogical technique by determining whether student interactions with an NLP-based revision assistant enables them to learn to write better -- that is, whether certain forms of the feedback (in terms of the perceived purposes and scopes of changes) encourage students to learn to make more effective revisions.

More specifically, the project works toward three objectives:

  1. Define a schema for characterizing the types of changes that occur at different levels of the rewriting. For example, the writer might add one or more sentences to provide evidence to support a thesis; or the writer might add just one or two words to make a phrase more precise.
  2. Based on the schema, design a computational model for recognizing the purpose and scope of each change within a revision. One application of such a model is a revision assistant that serves as a sounding board for students as they experiment with different revision alternatives.
  3. Conduct experiments to study the interactions between students and the revision writing environment in which variations of idealized computational models are simulated. The findings of the experiments pave the way for developing better technologies to support for student learning.

For more details of the project, please try our demo!

Project publications: Related publications using the data:

Rebecca Hwa

Professor, Computer Science Department / Intelligent Systems Program, University of Pittsburgh

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Diane Litman

Professor, Computer Science Department, Senior Scientist, Learning Research and Development Center Director, Intelligent Systems Program, University of Pittsburgh

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Amanda Godley

Professor, School of Education, University of Pittsburgh

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Tazin Afrin

Graduate Student, Computer Science Deparment, University of Pittsburgh

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Omid Kashefi

Graduate Student, Intelligent Systems Program, University of Pittsburgh

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Chris Olshefski

Graduate Student, School of Education, University of Pittsburgh

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Sonia Cromp

Undergraduate Student Researcher, Computer Science, University of Pittsburgh

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Meghan Dale

Graduate Student, School of Education
University of Pittsburgh

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Fan Zhang

Ph.D, Computer Science Department
University of Pittsburgh
Now working at Google

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Homa Hashemi

Ph.D, Intelligent Systems Program
University of Pittsburgh
Now working at Microsoft Research

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Reed ArmStrong

Undergraduate, Computer Science Deparment, University of Pittsburgh

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Nicolò Manfredi

Undergraduate, Computer Science Deparment, University of Pittsburgh

Made available under the terms of GNU General Public License. The corpus is distributed without any warranty.

To access the ArgRewrite V.2 corpus, please fill out the following form. We respect your privacy and will not use your information for any purpose other than to assess interest in the resource. For the previous version of the corpus, click here!

Currently our work is supported by NSF grant #1735752 from August 2017 till July 2021. Previously our work was supported by NSF grant #1550635 from September 2015 to August 2018. We are also supported by the Learning Research and Development Center at the University of Pittsburgh.

For questions regarding the corpus, please contact kashefi@cs.pitt.edu or tazinafrin@cs.pitt.edu