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A Writing Tool that Provides Real-Time Feedback to Students on their Grammar Using Deep Learning

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Conference

2019 Fall Mid Atlantic States Conference

Location

New York, New York

Publication Date

November 1, 2019

Start Date

November 1, 2019

End Date

November 30, 2019

Page Count

9

Permanent URL

https://peer.asee.org/33799

Download Count

87

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Paper Authors

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Basak Taylan Graduate Center of City University of New York

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Basak Taylan is a Ph.D. candidate in Computer Science Department at the Graduate Center of the City University of New York. She received a bachelor's degree in Computer Engineering from Mersin University, Turkey and a master's degree in Computer Science from New York University Polytechnic School of Engineering. Her current research interest is natural language processing, machine learning, and AI.

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Ashwin Satyanarayana New York City College of Technology

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Dr. Ashwin Satyanarayana is currently an Associate Professor with the Department of Computer Systems Technology, New York City College of Technology (CUNY). Prior to this, Dr. Satyanarayana was a Research Scientist at Microsoft in Seattle from 2006 to 2012, where he worked on several Big Data problems including Query Reformulation on Microsoft’s search engine Bing. He holds a PhD in Computer Science from SUNY, with particular emphasis on Data Mining and Big data analytics. He is an author or co-author of over 25 peer reviewed journal and conference publications and co-authored a textbook – “Essential Aspects of Physical Design and Implementation of Relational Databases.” He has four patents in the area of Search Engine research. He is also a recipient of the Math Olympiad Award, and is currently serving as Chair of the ASEE (American Society of Engineering Education) Mid-Atlantic Conference. He also serves as an NSF (National Science Foundation) panelist.

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Sawdiatou Samb New York City College of Technology

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Undergraduate Student
Computer Engineering Technology

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Abstract

Teaching English writing skills to students from non-English backgrounds is a challenge in undergraduate colleges. Grammar teaching is centered on accuracy of form and rule learning. Grammar pedagogy has received a lot of attention in recent years by researchers. One of the main challenges for first-language English teacher’s approach to teaching writing is introducing formulaic approaches to grammar. Another challenge is the amount of time it takes for a teacher to provide feedback to students on their written work. Exceptional rules in the language, cultural and social differences cause a lot of language issues. Applying correct grammar, syntax, spelling, and vocabulary into written work might be challenging especially for international students. In our work, we address both the challenges by proposing a writing tool for students. In our work we use a state- of-the-art deep learning model which helps students identify grammatically incorrect sentences in real time. Our tool not only identifies grammatically incorrect sentences but also gives students an opportunity to correct the sentence themselves. The tool does not correct the sentence for the student. Using this active approach with feedback, students learn by reflecting on their writing and correcting sentences on their own. Our tool identifies incorrect sentences with an accuracy of 80%. We have tried our tool on student essays and have shown that it helps them better understanding grammatical rules of English.

Taylan, B., & Satyanarayana, A., & Samb, S. (2019, November), A Writing Tool that Provides Real-Time Feedback to Students on their Grammar Using Deep Learning Paper presented at 2019 Fall Mid Atlantic States Conference, New York, New York. https://peer.asee.org/33799

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