Richard Correnti

Associate Professor, University of Pittsburgh School of Education

Research Scientist, Learning Research & Development Center

Education and Training

PhD, University of Michigan, Ann Arbor

Research Interests

Dr. Correnti's research interests include how educational innovations influence teacher practice and how teacher practice influences student learning. He studies how policy and educational reform initiatives can improve instruction and student learning, and how these efforts are influenced by issues of implementation and scaling-up.

Automated Writing Evaluation Education Reform Improvement Science Intelligent Tutoring Systems Interventions Mathematics Coaching Professional Learning Research/Practice Partnerships

Related Research Areas

Improvement Research in Education Learning Technology

Recent Publications

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.

Stein, M.K., Russell, J.L., Bill, V., Correnti, R., & Speranzo, L. (2021). Coach learning to help teachers learn to enact conceptually rich, student-focused mathematics lessons. Journal of Mathematics Teacher Education.

Litman, D., Zhang, H., Correnti, R., Matsumura, L., & Wang, E. A fairness evaluation of automated methods for scoring text evidence usage in writing," Proceedings of 22nd International Conference on Artificial Intelligence in Education (AIED),  June 2021.

Witherspoon, E., Ferrer, N., Correnti, R., Schunn, C., & Stein, M.K.  (2021). Coaching that supports teachers learning to enact ambitious instruction. Instructional Science.

Richard Correnti's Google Scholar profile

News and Awards

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


The James S. McDonnell Foundation has awarded a five-year, $2.5 million grant to Mary Kay Stein, Chris Schunn, Lindsay Clare Matsumura, Jennifer Russell, and Richard Correnti for "Teacher Learning to Enact Productive Discussions in Mathematics and Literacy."

December 15, 2017

Richard Correnti, LRDC Research Scientist and Associate Professor, School of Education, and co-Principal Investigators Mary Kay Stein, Associate Director for Educational Research and Practice, and Jennifer Russell, LRDC Research Scientist and Associate Professor, School of Education were awarded a 2017 Spencer Foundation grant for “Improvement of Mathematics Teaching At-Scale.”


Diane Litman, Richard Correnti, and Lindsay Clare Matsumura, LRDC Research Scientists have been awarded an IES grant for their project, "Response-to-Text Tasks to Assess Students' Use of Evidence and Organization in Writing: Using Natural Language Processing for Scoring Writing and Providing Feedback At-Scale."

July 1, 2016

Meghan Bathgate, Chris Schunn, and Rip Correnti’s research on Childrens’ responses to science across settings is featured in the May 2016 Relating Research to Practice Brief, a website supported by the National Science Foundation.

May 31, 2016


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