Project Activities
Structured Abstract
Setting
Sample
Research design and methods
Control condition
Key measures
Data analytic strategy
People and institutions involved
IES program contact(s)
Products and publications
Products: The outcome of this project will be an advanced version of SWoRD, which will use artificial intelligence and Natural Language Processing techniques to assess student essays and reviewer comments; provide scaffolded assistance to authors and reviewers; and help authors organize reviewer feedback to facilitate writing revisions. Additionally, the researchers expect to publish their findings in scientific journals and conference proceedings.
Journal article, monograph, or newsletter
Loretto, A., DeMartino, S., and Godley, A. (2016). Secondary Students' Perceptions of Peer Review of Writing. Research in the Teaching of English, 51(2): 134-161.
Nguyen, H., Xiong, W., and Litman, D. (2017). Iterative Design and Classroom Evaluation of Automated Formative Feedback for Improving Peer Feedback Localization. International Journal of Artificial Intelligence in Education, 27(3): 582-622.
Schunn, C. D., Godley, A. J., and DiMartino, S. (2016). The Reliability and Validity of Peer Review of Writing in High School AP English Classes. Journal of Adolescent & Adult Literacy, 60(1): 13-23.
Schunn, C., Godley, A. and DeMartino, S. (2016). The Reliability and Validity of Peer Review of Writing in High School AP English Classes. Journal of Adolescent and Adult Literacy, 60(1): 13-23.
Zhang, F., Schunn, C.D., and Baikadi, A. (2017). Charting the Routes to Revision: An Interplay of Writing Goals, Peer Comments, and Self-Reflections from Peer Reviews. Instructional Science, 45: 679-707.
Proceeding
Baikadi, A., Schunn, C., and Ashley, K. (2016). Impact of Revision Planning on Peer-Reviewed Writing. In EDM 2016 Workshops and Tutorials co-located with the 9th International Conference on Educational Data Mining (pp. 1-5). Raleigh, NC: CEUR Workshop Proceedings.
Baikadi, A., Schunn, C., & Ashley, K. D. (2015, June). Understanding Revision Planning in Peer-Reviewed Writing. In EDM (pp. 544-547).
Falakmasir, M. H., Ashley, K. D., Schunn, C. D., & Litman, D. J. (2014, June). Identifying thesis and conclusion statements in student essays to scaffold peer review. In International Conference on Intelligent Tutoring Systems (pp. 254-259). Springer, Cham.
Hashemi, H. B., & Schunn, C. D. (2014, June). A tool for summarizing students' changes across drafts. In International Conference on Intelligent Tutoring Systems (pp. 679-682). Springer, Cham.
Litman, D. (2016, March). Natural language processing for enhancing teaching and learning. In Thirtieth AAAI Conference on Artificial Intelligence.
Nguyen, H., Xiong, W., & Litman, D. (2016, June). Instant feedback for increasing the presence of solutions in peer reviews. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations (pp. 6-10).
Nguyen, H., Xiong, W., & Litman, D. (2014, June). Classroom evaluation of a scaffolding intervention for improving peer review localization. In International Conference on Intelligent Tutoring Systems (pp. 272-282). Springer, Cham.
Xiong, W., & Litman, D. J. (2013). Evaluating topic-word review analysis for understanding student peer review performance. In Proceedings 6th International Conference on Educational Data Mining (EDM 2013) (pp. 200-207). University of Pittsburgh.
Xiong, W., and Litman, D. (2014). Empirical Analysis of Exploiting Review Helpfulness for Extractive Summarization of Online Reviews. In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics (pp. 1985-1995). Dublin, Ireland: ACL Anthology.
Zhang, F., and Litman, D. (2015). Annotation and Classification of Argumentative Writing Revisions. In Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications (pp. 133-143). Denver, CO: Association for Computational Linguistics.
Zhang, F., & Litman, D. (2014, June). Sentence-level rewriting detection. In Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications (pp. 149-154).
Supplemental information
In Year 3, the researchers will conduct a Pilot Study with high school students from at least four teachers' classrooms, resulting in at least 200 students, with half of the students using the basic version of SWoRD (which currently exists) and the other half using the advanced one (which will include the revisions and additions made from the development efforts carried out in this project). Both types of writing genre (argumentative essays and science reports) will be used with each version. Random assignment will be at the student level.
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.