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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.

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.

Nguyen, H., Xiong, W., & Litman, D. (2017). Iterative design and classroom evaluation of automated formative feedback for improving peer feedback localization. International Journal of Artificial Intelligence in Education, 1-41.

Fan, X., Luo, W., Menekse, M., Litman, D., & Wang, J. (2017). Scaling reflection prompts in large classrooms via mobile interfaces and natural language processing. Proceedings of the 22nd ACM Conference on Intelligent User Interfaces (IUI '17), pp. 363-374. ACM, New York, NY, USA.

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.

Litman, D., Young, S., Gales, M., Knill, K., Ottewell, K., Van Dalen, R., & Vandyke, D. (2016). Towards using conversations with spoken dialogue systems in the automated assessment of non-native speakers of English. Proceedings of the SIGDIAL 2016 Conference, pp. 270–275.

Forbes-Riley, K., Zhang, F., & Litman, D. (2016). Extracting PDTB discourse relations from student essays. Proceedings of the SIGDIAL 2016 Conference, pp. 117–127.

Litman, D. (2016). Natural language processing for enhancing teaching and learning. Proceedings of the 30th AAAI Conference on Artificial Intelligence.

Nguyen, H., & Litman, D. (2016). Improving argument mining in student essays by learning and exploiting argument indicators versus essay topics. Proceedings of the 29th International Florida Artificial Intelligence.

Luo, W., & Litman, D. (2016). Determining the quality of a student reflective response. Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference.

Allegretti, S., Litman, D., Paletz, S., Rahimi, Z., & Rice, C. (2016). The teams corpus and entrainment in multi-party spoken dialogues. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 1421–1431.

Zhang, F., Litman, D., & Riley, K. F. (2016). Inferring discourse relations from PDTB-style discourse labels for argumentative revision classification. Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pp. 2615–2624, Osaka, Japan.

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

Diane Litman (Co-Principal Investigator) and Rebecca Hwa (Principal Investigator, Department of Computer Science) have been awarded a grant by the National Science Foundation to investigate whether natural language processing (NLP) methods can help students learn to make a more concrete connection between the abstract principles of rewriting (e.g., "A paper should have a clear thesis") and the particular contexts in which the revision is carried out.

August 5, 2015

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LRDC Senior Scientist and Professor of Computer Science Diane Litman, and co-author Kate Forbes-Riley, received the Best Paper Published in Speech Communication (2011-2013) award by the International Speech Communication Association (ISCA). The award was given for "Benefits and Challenges of Real-time Uncertainty Detection and Adaptation in a Spoken Dialogue Computer Tutor," (2011), volume 53, issue 9, at the Interspeech 2014 conference in Singapore.

September 2014

The first Intelligent Systems Program Yearly Newsletter.

September 2014

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A list of recent LRDC award recipients is on page 18 of the August 28 issue of the University Times. Einat Heyd-Metzuyanim, Melissa Libertus, Diane Litman, Charles Perfetti, Christian Schunn, Natasha Tokowicz, Tessa Warren, and Jingtao Wang were all mentioned.

August 2014

Diane Litman along with Steve Young, University of Cambridge, received a Distinguished Visiting Fellowship Award for collaborating "Dialogue systems for teaching & assessing conversational skills in second language learning."

August 2014

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Congratulations to Christian Schunn, Diane Litman, and Amanda Godley. "An Intelligent Ecosystem for Science Writing Instruction," was awarded a The National Science Foundation (NSF) grant.

July 2014

Diane Litman is a recent recipient of Google's Faculty Research Awards. She is researching how to enable computers to derive meaning from human language so the computers can analyze student peer assessments in "massively open-access online courses," or MOOCs. Article appeared in May 19th issue of the Pitt Chronicle.

June 2014

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Diane Litman has been awarded a 2014 Google Faculty Research Award for Natural Language Processing.

March 20, 2014