James Lester

Also published as: James C. Lester


2023

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Improving Classroom Dialogue Act Recognition from Limited Labeled Data with Self-Supervised Contrastive Learning Classifiers
Vikram Kumaran | Jonathan Rowe | Bradford Mott | Snigdha Chaturvedi | James Lester
Findings of the Association for Computational Linguistics: ACL 2023

Recognizing classroom dialogue acts has significant promise for yielding insight into teaching, student learning, and classroom dynamics. However, obtaining K-12 classroom dialogue data with labels is a significant challenge, and therefore, developing data-efficient methods for classroom dialogue act recognition is essential. This work addresses the challenge of classroom dialogue act recognition from limited labeled data using a contrastive learning-based self-supervised approach (SSCon). SSCon uses two independent models that iteratively improve each other’s performance by increasing the accuracy of dialogue act recognition and minimizing the embedding distance between the same dialogue acts. We evaluate the approach on three complementary dialogue act recognition datasets: the TalkMoves dataset (annotated K-12 mathematics lesson transcripts), the DailyDialog dataset (multi-turn daily conversation dialogues), and the Dialogue State Tracking Challenge 2 (DSTC2) dataset (restaurant reservation dialogues). Results indicate that our self-supervised contrastive learning-based model outperforms competitive baseline models when trained with limited examples per dialogue act. Furthermore, SSCon outperforms other few-shot models that require considerably more labeled data.

2022

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Disruptive Talk Detection in Multi-Party Dialogue within Collaborative Learning Environments with a Regularized User-Aware Network
Kyungjin Park | Hyunwoo Sohn | Wookhee Min | Bradford Mott | Krista Glazewski | Cindy E. Hmelo-Silver | James Lester
Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue

Accurate detection and appropriate handling of disruptive talk in multi-party dialogue is essential for users to achieve shared goals. In collaborative game-based learning environments, detecting and attending to disruptive talk holds significant potential since it can cause distraction and produce negative learning experiences for students. We present a novel attention-based user-aware neural architecture for disruptive talk detection that uses a sequence dropout-based regularization mechanism. The disruptive talk detection models are evaluated with multi-party dialogue collected from 72 middle school students who interacted with a collaborative game-based learning environment. Our proposed disruptive talk detection model significantly outperforms competitive baseline approaches and shows significant potential for helping to support effective collaborative learning experiences.

2015

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NCSU_SAS_SAM: Deep Encoding and Reconstruction for Normalization of Noisy Text
Samuel Leeman-Munk | James Lester | James Cox
Proceedings of the Workshop on Noisy User-generated Text

2014

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Towards Domain-Independent Assessment of Elementary Students’ Science Competency using Soft Cardinality
Samuel Leeman-Munk | Angela Shelton | Eric Wiebe | James Lester
Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications

2013

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Learning Dialogue Management Models for Task-Oriented Dialogue with Parallel Dialogue and Task Streams
Eun Ha | Christopher Mitchell | Kristy Boyer | James Lester
Proceedings of the SIGDIAL 2013 Conference

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Evaluating State Representations for Reinforcement Learning of Turn-Taking Policies in Tutorial Dialogue
Christopher Mitchell | Kristy Boyer | James Lester
Proceedings of the SIGDIAL 2013 Conference

2012

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Expressive NLG for Next-Generation Learning Environments: Language, Affect, and Narrative
James Lester
INLG 2012 Proceedings of the Seventh International Natural Language Generation Conference

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From Strangers to Partners: Examining Convergence within a Longitudinal Study of Task-Oriented Dialogue
Christopher M. Mitchell | Kristy Elizabeth Boyer | James C. Lester
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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Combining Verbal and Nonverbal Features to Overcome the “Information Gap” in Task-Oriented Dialogue
Eun Young Ha | Joseph F. Grafsgaard | Christopher Mitchell | Kristy Elizabeth Boyer | James C. Lester
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2011

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An Affect-Enriched Dialogue Act Classification Model for Task-Oriented Dialogue
Kristy Boyer | Joseph Grafsgaard | Eun Young Ha | Robert Phillips | James Lester
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

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The Impact of Task-Oriented Feature Sets on HMMs for Dialogue Modeling
Kristy Boyer | Eun Young Ha | Robert Phillips | James Lester
Proceedings of the SIGDIAL 2011 Conference

2010

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Exploring Individual Differences in Student Writing with a Narrative Composition Support Environment
Julius Goth | Alok Baikadi | Eun Young Ha | Jonathan Rowe | Bradford Mott | James Lester
Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics and Writing: Writing Processes and Authoring Aids

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Leveraging Hidden Dialogue State to Select Tutorial Moves
Kristy Boyer | Rob Phillips | Eun Young Ha | Michael Wallis | Mladen Vouk | James Lester
Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications

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Exploring the Effectiveness of Lexical Ontologies for Modeling Temporal Relations with Markov Logic
Eun Y. Ha | Alok Baikadi | Carlyle Licata | Bradford Mott | James Lester
Proceedings of the SIGDIAL 2010 Conference

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Dialogue Act Modeling in a Complex Task-Oriented Domain
Kristy Boyer | Eun Y. Ha | Robert Phillips | Michael Wallis | Mladen Vouk | James Lester
Proceedings of the SIGDIAL 2010 Conference

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NCSU: Modeling Temporal Relations with Markov Logic and Lexical Ontology
Eun Ha | Alok Baikadi | Carlyle Licata | James Lester
Proceedings of the 5th International Workshop on Semantic Evaluation

2009

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Inferring Tutorial Dialogue Structure with Hidden Markov Modeling
Kristy Elizabeth Boyer | Eun Young Ha | Robert Phillips | Michael Wallis | Mladen Vouk | James Lester
Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications

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Modeling Dialogue Structure with Adjacency Pair Analysis and Hidden Markov Models
Kristy Elizabeth Boyer | Robert Phillips | Eun Young Ha | Michael Wallis | Mladen Vouk | James Lester
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers

2008

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Learner Characteristics and Feedback in Tutorial Dialogue
Kristy Boyer | Robert Phillips | Michael Wallis | Mladen Vouk | James Lester
Proceedings of the Third Workshop on Innovative Use of NLP for Building Educational Applications

2002

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Pronominalization in Generated Discourse and Dialogue
Charles B. Callaway | James C. Lester
Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics

1998

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Natural Language Generation Journeys to Interactive 3D Worlds Invited Talk Extended Abstract
James C. Lester | William H. Bares | Charles B. Callaway | Stuart G. Towns
Natural Language Generation

1997

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Developing and Empirically Evaluating Robust Explanation Generators: The KNIGHT Experiments
James C. Lester | Bruce W. Porter
Computational Linguistics, Volume 23, Number 1, March 1997