Recent Publications
Matsumura, L.C., Wang, E.L., Correnti, R., & Litman, D. (2023) Tasks and feedback: An exploration of students’ opportunity to develop adaptive expertise for analytic text-based writing. Assessing Writing.
McCarthy, K. S., Litman, D., Crossley, S. A., Meyers, K., Boser, U., Allen, L. K., Chaudhri, V. K., … Graesser, A. (2022). Toward more effective and equitable learning: Identifying barriers and solutions for the future of online education. Technology, Mind, and Behavior.
Wang, E.L., Correnti, R., Matsumura, L.C. & Litman, D. (2022). Contributions to automated writing scoring and feedback systems. RAND Research Brief.
Correnti, R., Matsumura, L.C., Wang, E., Litman, D., Zhang, H. (2022). Building a validity argument for an automated writing evaluation system (eRevise) as a formative assessment. Computers and Education Open.
Tran, N., Alikhani, M., & Litman, D. (2022) How to ask for donations? Learning user-specific persuasive dialogue policies through online interactions. In Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, New York, NY, USA, 12–22.
Diane Litman's Google Scholar profile
News and Awards
Kudos to Diane Litman and co-authors Zhexiong Liu, Meiqi Guo, and Yue Dai who received Best Paper Award for "ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness Mining," at the 9th Workshop on Argument Mining, COLING, South Korea 2022.
October 24, 2022
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Diane Litman, Lindsay Clare Matsumura, and Rip Correnti were among the 2021-2022 awardees of the Learning Engineering Tools Competition Catalyst Prize. The team received the award to create the web-based application "Automated Assessment of Classroom Discussion Quality," that will use natural language processing and machine learning methods to analyze classroom discussion quality.
July 12, 2022
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Diane Litman was featured in the Summer 2022 LRDC Research News for "Toward More Effective and Equitable Online Learning."
March 31, 2022
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Pitt Momentum Scaling Grant: Center for Text Analytic Methods in Legal Studies: Kevin Ashley, School of Law with School of Computing & Information Science colleagues Daqing He, Diane Litman, and Rebecca Hwa; and James Anderson, RAND. Scaling Grants are awarded for a two-year term with an award cap of $ 400,000, enable multi-disciplinary teams to competitively scale their research efforts in targeted pursuit of large-scale external funding.
March 21, 2022
Congratulations to Kevin Ashley, Professor, Law, and Diane Litman, Professor, School of Computing and Information, who received a $600,000 grant from Amazon and the National Science Foundation (NSF) Fairness in Artificial Intelligence for "Using AI to Increases Fairness by Improving Access to Justice."
January 28, 2022
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