[Person photo]

Zahra Rahimi

Graduate Student, Dr. Litman

School of Arts and Sciences

Communication Science and Disorders

Faculty Advisor: Diane Litman

Rahimi, Z., Litman, D., Correnti, R., Wang, E., & Matsumura, L. C. (2017). Assessing students’ use of evidence and organization in response-to-text Writing: Using natural language processing for rubric-based automated scoring. International Journal of Artificial Intelligence in Education, 1-35.

Rahimi, Z., & Litman, D. (2016). Automatically extracting topical components for a response-to-text writing assessment. Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications, 277–282.

Rahimi, Z., Litman, D. J., Correnti, R., Matsumura, L. C., Wang, E., & Kisa, Z. (2015). Incorporating coherence of topics as a criterion in Automatic Response-to-Text assessment of the organization of writing. Proceedings of the 10th Workshop on Innovative Use of NLP for Building Educational Applications.

Rahimi, Z., Litman, D. J., Correnti, R., Matsumura, L. C., Wang, E., & Kisa, Z. (2014). Automated scoring of an analytical response-to-text assessment. In Intelligent Tutoring Systems (pp. 601-610). Springer International Publishing.