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Diane Litman

Faculty, University of Pittsburgh Intelligent Systems Program

Professor, University of Pittsburgh Department of Computer Science

Senior Scientist, Learning Research & Development Center

Research Interests

My research is in the area of artificial intelligence, and includes contributions in the areas of artificial intelligence and education, computational linguistics, knowledge representation and reasoning, natural language learning, spoken language, and user modeling.

Ashley, K., Litman, D., He, D., Hwa, R., & Anderson, J. (2021). Center for text analytic methods in legal studies. In: Pitt Momentum Fund 2021.

Wang, E.L., Matsumura, L.C., Correnti, R., Litman, D., Zhang, H., Howe, E., Magooda, A., & Quintana, R. (2020). eRevis(ing): Students’ revision of text evidence use in an automated writing evaluation system. Assessing Writing.

Lugini, L., Olshefski, C., Singh, R., Litman, D., & Godley, A. (2020). Discussion tracker: Supporting teacher learning about students' collaborative argumentation in high school classrooms. Proceedings of the 27th International Conference on Computational Linguistics, Barcelona, Spain, pp. 53-58.

Zhang, H. & Litman, D. (2020). Automated topical component extraction using neural network attention scores from source-based essay scoring. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 8569-8584.

Lugini, L. & Litman, D. (2020). Contexual argument component classification for class discussions. Proceedings of the 28th International Conference on Computational Linguistics,Barcelona, Spain, pp. 1475-1480.

Correnti, R., Matsumura, L.C., Wang, E., Litman, D., Rahimi, Z., & Kisa, Z. (2020). Automated Scoring of Students Use of Text Evidence in Writing. Reading Research Quarterly, 55(3).

Afrin, T., Wang, E., Litman, D., Matsumura, L.C., & Correnti, R. (2020). Annotation and classification of evidence and reasoning revisions in argumentative writing.  Proceedings of the 15th Workshop on Innovative Use of NLP for Building Educational Applications, 75-84.

Olshefski, C., Lugini, L., Singh, R., Litman, D., & Godley, A. (2020). The discussion tracker corpus of collaborative argumentation.

Matsumura, L.C., Wang, E., Correnti, R. & Litman, D. (2020). What do Teachers want to see in Automated Writing Evaluation Systems? eSchool News Innovations in Educational Transformation.

Afrin, T., & Litman, D. (2019). Identifying editor roles in argumentative writing from student revision histories. Springer Link.19

Litman, D. J., & Nguyen, H. V. (2018). Argument mining for improving the automated scoring of persuasive essays. Association for the Advancement of Artificial Intelligence.

Afrin, T., & Litman, D. (2018). Annotation and classification of sentence-level revision improvement. Association for Computational Linguistics, 240-246.

Zhang, H., & Litman, D. (2018). Co-attention based neural network for source-dependent essay scoring. Association for Computational Linguistics, 399-409.

Luo, W., Liu, F., Liu, Z., & Litman, D. (2018). A novel ILP framework for summarizing content with high lexical variety. Natural Language Engineering, 1-32.

Rahimi, Z., Litman, D., & Paletz, S. (2018). Acoustic-prosodic entrainment in multi-party spoken dialogues: Does simple averaging extend existing pair measures properly? Advanced Social Interaction with Agents: 8th International Workshop on Spoken Dialog Systems, 510, 169 – 177.

Litman, D., Strik, H., & Lim, G. (2018). Speech technologies and the assessment of second language speaking: Approaches, challenges, and opportunities. Language Assessment Quarterly: An International Journal, 15(3), 294-309.

Lugini, L. & Litman, D. (2018). Argument component classification for classroom discussions. Proceedings of the 5th Workshop on Argument Mining, (pp. 57–67). Brussels, Belgium.

Lugini, L., Litman, D., Godley, A., & Olshefski, C. (2018). Annotating student talk in text-based classroom discussions. Association for Computational Linguistics, 110-116.

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.

Magooda, A. & Litman, D. (2017). Syntactic and semantic features for human like judgement in spoken CALL. Proceedings Seventh ISCA Workshop on Speech and Language Technology in Education (SLaTE). Stockholm, Sweden.

Zhang, F., Hashemi, H. B., Hwa, R. & Litman, D. (2017). A corpus of annotated revisions for studying argumentative writing. Proceedings Annual Meeting of the Association for Computational Linguistics (ACL), Vancouver, Canada.

Rahimi, Z., Litman, D., & Paletz, S. (2017). Acoustic-prosodic entrainment in multi-party spoken dialogues: Does simple averaging extend existing pair measures properly? Proceedings International Workshop on Spoken Dialogue Systems Technology (IWSDS), Farmington, PA.

Rahimi, Z., Litman, D., & Paletz, S. (2017). Acoustic-prosodic entrainment in multi-party spoken dialogues: Does simple averaging extend existing pair measures properly? Proceedings International Workshop on Spoken Dialogue Systems Technology (IWSDS), Farmington, PA.

Zhang, H., & Litman, D. (2017). Word embedding for response-to-text assessment of evidence. Proceedings of the 55th Annual Association for Computational Linguistics (Student Research Workshop), pp. 75-81.

Chandrasekaran, M. K., Epp, C. D., Kan, M-Y., & Litman, D. (2017). Using discourse signals for robust instructor intervention prediction. Proceedings of the 31st AAAI Conference on Artificial Intelligence.

Kudos to Diane Litman and colleagues, recipients of a Cyber Accelerator Grant, details in March 25 Pittwire accolade.

March 25, 2021

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Kevin Ashley and Diane Litman are featured in a Pittwire accolade for the recently awarded National Science Foundation (NSF) FAI: Using AI to Increase Fairness by Improving Access to Justice.

February 24, 2021

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Kevin Ashley and Diane Litman have received a National Science Foundation award titled FAI: Using AI to Increase Fairness by Improving Access to Justice for their research on fairness in artificial intelligence in collaboration with Amazon.

January 25, 2021

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Erin Walker, SCI, has been named principal investigator for a National Science Foundation grant to study the use of robots in middle school math classrooms. Her co-principal investigators are Diane Litman, Computer Science, and Timothy Nokes-Malach, Psychology, and Adriana Kovashka, (SCI).

November 10, 2020

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Erin Walker, Diane Litman, Timothy Nokes-Malach, and Adriana Kovashka received a National Science Foundation award for their study on "Designing Effective Dialogue, Gaze, and Gesture Behaviors in a Social Robot that Supports Collaborative Learning in Middle School Mathematics."

September 14, 2020

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Diane Litman, Professor, Computer Science and School of Computing and Information, was the recipient of the Provost's Award for Excellence in Doctoral Mentoring.

March 10, 2020

Diane Litman and Amanda Godley were featured in Pittwire's "What Will the 2020s Bring for AI?"

December 13, 2019

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Amanda Godley (PI) and Diane Litman (co-PI) were awarded a three-year NSF Cyberlearning grant “Discussion Tracker: Development of Human Language Technologies to Improve the Teaching of Collaborative Argumentation in High School English Classrooms.”

September 1, 2019

Diane Litman, director of the Intelligent Systems Program, professor in the University of Pittsburgh’s School of Computing and Information and senior scientist at the Learning Research and Development Center (LRDC) has been awarded a research grant from the Institute of Education Sciences to study undergraduate STEM education, announced in PittWire.

August 31, 2018

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Diane Litman and Amanda Godley have received a grant from the National Science Foundation for their project titled "EAGER: Discussion Tracker: Development of Human Language Technologies to Improve the Teaching of Collaborative Argumentation in High School English Classrooms."

July 29, 2018

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Diane Litman and colleagues have received a research grant in Postsecondary and Adult Education through the Institute of Education Sciences (IES) for their project titled "Enhancing Undergraduate STEM Education by Integrating Mobile Learning Technologies with Natural Language Processing."

July 17, 2018

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Diane Litman, Director, Intelligent Systems Program, and Professor, Department of Computer Science, is featured in the Pittwire Accolades for her election as an Association of Computational Linguistics (ACL) Fellow.

January 24, 2018

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Diane Litman has been elected to be an Association of Computational Linguistics Fellow for her key contributions to dialog systems research, especially the application of reinforcement learning and multimodal analysis to tutoring dialog

January 2018

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Diane Litman, Intelligent Systems Program, Computer Science, and LRDC Senior Scientist, is one of six newly elected Executive Committee members of the International Artificial Intelligence in Education Society (IAIED).

October 16, 2017

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The National Science Foundation (NSF) IIS Division of Information and Intelligent Systems awarded a grant to Principal Investigator Rebecca Hwa, Associate Professor, Computer Science, and co-PIs Diane Litman, Faculty, Intelligent Systems Program, Professor, Computer Science, and LRDC Senior Scientist, and Amanda Godley, Associate Professor, English Education and Language, Literacy & Culture, and LRDC Center Associate, for "Development of Human Language Technologies to Improve Disciplinary Writing and Learning through Self-Regulated Revising."

September 5, 2017

Senior Personnel Diane Litman, Professor, Computer Science, and LRDC Senior Scientist, and Principal Investigator M. Richardson were awarded a combined grant from NIH (Brain Initiative) and LRDC on September 30, 2016 for “Subthalamic and Corticosubthalamic Coding of Speech Production.”

September 2016

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

LRDC awarded a grant to Co-Principal Investigators Diane Litman, Professor, Computer Science, and LRDC Senior Scientist and A. Godley for “Using Natural Language Processing to Study the Role of Specificity and Evidence Type in Text Based Classroom Discussions."

July 2016

LRDC

Two of the three nominees for Best Student Paper at the 29th International Florida Artificial Intelligence Research Society Conference were first-authored by LRDC graduate students of Diane Litman. Wencan Luo, “Determining the Quality of a Student Reflective Response,” and Huy Nguyen, “Improving Argument Mining in Student Essays by Learning and Exploiting Argument Indicators versus Essay Topics.”

April 11, 2016

Diane Litman, LRDC Senior Scientist, has been elected to a three-year term as Councilor of the Association for the Advancement of Artificial Intelligence (AAAI) -- a nonprofit scientific society devoted to advancing the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines.

2015