| 2026 | AIED | Hierarchical Apprenticeship Learning from Imperfect Demonstrations with Evolving Rewards. | Md. Mirajul Islam, Rajesh Debnath, Adittya Soukarjya Saha, Min Chi |
| 2026 | CHI | Exploring the Design and Impact of Interactive Worked Examples for Learners with Varying Prior Knowledge. | Sutapa Dey Tithi, Xiaoyi Tian, Ally Limke, Min Chi, Tiffany Barnes |
| 2025 | AAAI | Iterative Counterfactual Data Augmentation. | Mitchell Plyler, Min Chi |
| 2025 | AIED | Determining Problem Type Using Deep Reinforcement Learning in a Data-Driven Intelligent Tutor. | Nazia Alam, Kimia Fazeli, Xiaoyi Tian, Min Chi, Tiffany Barnes |
| 2025 | AIED | A Generalized Apprenticeship Learning Framework for Capturing Evolving Student Pedagogical Strategies. | Md. Mirajul Islam, Xi Yang, Rajesh Debnath, Adittya Shoukarjya Saha, Min Chi |
| 2025 | EDM | Investigating the Impact and Student Perceptions of Guided Parsons Problems for Learning Logic with Subgoals. | Sutapa Dey Tithi, Xiaoyi Tian, Min Chi, Tiffany Barnes |
| 2025 | IJCAI | Human-Readable Neuro-Fuzzy Networks from Frequent Yet Discernible Patterns in Reward-Based Environments. | John Wesley Hostetter, Adittya Soukarjya Saha, Md. Mirajul Islam, Tiffany Barnes, Min Chi |
| 2025 | KDD | THEMES: An Offline Apprenticeship Learning Framework for Evolving Reward Functions. | Xi Yang, Md. Mirajul Islam, Ge Gao, Min Chi |
| 2024 | AAAI | Get a Head Start: On-Demand Pedagogical Policy Selection in Intelligent Tutoring. | Ge Gao, Xi Yang, Min Chi |
| 2024 | EDM | Evaluating Multi-Knowledge Component Interpretability of Deep Knowledge Tracing Models in Programming. | Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price |
| 2024 | EDM | How Much Training is Needed? Reducing Training Time using Deep Reinforcement Learning in an Intelligent Tutor. | Nazia Alam, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi, Tiffany Barnes |
| 2024 | EDM | A Generalized Apprenticeship Learning Framework for Modeling Heterogeneous Student Pedagogical Strategies. | Md. Mirajul Islam, Xi Yang, John Wesley Hostetter, Adittya Soukarjya Saha, Min Chi |
| 2024 | EDM | More, May not the Better: Insights from Applying Deep Reinforcement Learning for Pedagogical Policy Induction. | Gyuhun Jung, Markel Sanz Ausin, Tiffany Barnes, Min Chi |
| 2024 | ICLR | On Trajectory Augmentations for Off-Policy Evaluation. | Ge Gao, Qitong Gao, Xi Yang, Song Ju, Miroslav Pajic, Min Chi |
| 2024 | IJCAI | Multi-TA: Multilevel Temporal Augmentation for Robust Septic Shock Early Prediction. | Hyunwoo Sohn, Kyungjin Park, Baekkwan Park, Min Chi |
| 2023 | AAAI | Does Knowing When Help Is Needed Improve Subgoal Hint Performance in an Intelligent Data-Driven Logic Tutor? | Nazia Alam, Mehak Maniktala, Behrooz Mostafavi, Min Chi, Tiffany Barnes |
| 2023 | AIED | Leveraging Deep Reinforcement Learning for Metacognitive Interventions Across Intelligent Tutoring Systems. | Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi |
| 2023 | AIED | Exploring the Effect of Autoencoder Based Feature Learning for a Deep Reinforcement Learning Policy for Providing Proactive Help. | Nazia Alam, Behrooz Mostafavi, Min Chi, Tiffany Barnes |
| 2023 | AIED | A Unified Batch Hierarchical Reinforcement Learning Framework for Pedagogical Policy Induction with Deep Bisimulation Metrics. | Markel Sanz Ausin, Mark Abdelshiheed, Tiffany Barnes, Min Chi |
| 2023 | AIED | Impact of Learning a Subgoal-Directed Problem-Solving Strategy Within an Intelligent Logic Tutor. | Preya Shabrina, Behrooz Mostafavi, Min Chi, Tiffany Barnes |
| 2023 | CogSci | Bridging Declarative, Procedural, and Conditional Metacognitive Knowledge Gap Using Deep Reinforcement Learning. | Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi |
| 2023 | EDM | KC-Finder: Automated Knowledge Component Discovery for Programming Problems. | Yang Shi, Robin Schmucker, Min Chi, Tiffany Barnes, Thomas W. Price |
| 2023 | EDM | Learning Problem Decomposition-Recomposition with Data-driven Chunky Parsons Problems within an Intelligent Logic Tutor. | Preya Shabrina, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi, Tiffany Barnes |
| 2023 | ICLR | Variational Latent Branching Model for Off-Policy Evaluation. | Qitong Gao, Ge Gao, Min Chi, Miroslav Pajic |
| 2023 | IJCAI | Hierarchical Apprenticeship Learning for Disease Progression Modeling. | Xi Yang, Ge Gao, Min Chi |
| 2023 | IVA | XAI to Increase the Effectiveness of an Intelligent Pedagogical Agent. | John Wesley Hostetter, Cristina Conati, Xi Yang, Mark Abdelshiheed, Tiffany Barnes, Min Chi |
| 2022 | AAAI | Cross-Lingual Adversarial Domain Adaptation for Novice Programming. | Ye Mao, Farzaneh Khoshnevisan, Thomas W. Price, Tiffany Barnes, Min Chi |
| 2022 | AIED | Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer. | Mark Abdelshiheed, John Wesley Hostetter, Xi Yang, Tiffany Barnes, Min Chi |
| 2022 | AIED | Student-Tutor Mixed-Initiative Decision-Making Supported by Deep Reinforcement Learning. | Song Ju, Xi Yang, Tiffany Barnes, Min Chi |
| 2022 | CogSci | The Power of Nudging: Exploring Three Interventions for Metacognitive Skills Instruction across Intelligent Tutoring Systems. | Mark Abdelshiheed, John Wesley Hostetter, Preya Shabrina, Tiffany Barnes, Min Chi |
| 2022 | EDM | Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks. | Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price |
| 2022 | IJCAI | A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification. | Ge Gao, Qitong Gao, Xi Yang, Miroslav Pajic, Min Chi |
| 2021 | AIED | Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks. | Markel Sanz Ausin, Mehak Maniktala, Tiffany Barnes, Min Chi |
| 2021 | AIED | Evaluating Critical Reinforcement Learning Framework in the Field. | Song Ju, Guojing Zhou, Mark Abdelshiheed, Tiffany Barnes, Min Chi |
| 2021 | CogSci | Preparing Unprepared Students For Future Learning. | Mark Abdelshiheed, Mehak Maniktala, Song Ju, Ayush Jain, Tiffany Barnes, Min Chi |
| 2021 | EDM | More With Less: Exploring How to Use Deep Learning Effectively through Semi-supervised Learning for Automatic Bug Detection in Student Code. | Yang Shi, Ye Mao, Tiffany Barnes, Min Chi, Thomas W. Price |
| 2021 | EDM | Knowing both when and where: Temporal-ASTNN for Early Prediction of Student Success in Novice Programming Tasks. | Ye Mao, Yang Shi, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi |
| 2021 | EDM | Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming. | Samiha Marwan, Yang Shi, Ian Menezes, Min Chi, Tiffany Barnes, Thomas W. Price |
| 2021 | IJCAI | Multi-series Time-aware Sequence Partitioning for Disease Progression Modeling. | Xi Yang, Yuan Zhang, Min Chi |
| 2020 | AIED | Exploring the Impact of Simple Explanations and Agency on Batch Deep Reinforcement Learning Induced Pedagogical Policies. | Markel Sanz Ausin, Mehak Maniktala, Tiffany Barnes, Min Chi |
| 2020 | CogSci | Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. | Mark Abdelshiheed, Min Chi |
| 2020 | EDM | Does autonomy help Help? The impact of unsolicited hints and choice on help avoidance and learning. | Christa Cody, Mehak Maniktala, David Warren, Min Chi, Tiffany Barnes |
| 2020 | EDM | Pick the Moment: Identifying Critical Pedagogical Decisions Using Long-Short Term Rewards. | Song Ju, Min Chi, Guojing Zhou |
| 2020 | EDM | Extending the Hint Factory: Towards Modelling Productivity for Open-ended Problem-solving. | Mehak Maniktala, Tiffany Barnes, Min Chi |
| 2020 | EDM | What Time is It? Student Modeling Needs to Know. | Ye Mao, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi |
| 2020 | EDM | Immediate Data-Driven Positive Feedback Increases Engagement on Programming Homework for Novices. | Samiha Marwan, Thomas W. Price, Min Chi, Tiffany Barnes |
| 2020 | EDM | The Impact of Data-driven Positive Programming Feedback: When it Helps, What Happens when it Goes Wrong, and How Students Respond. | Preya Shabrina, Samiha Marwan, Min Chi, Thomas W. Price, Tiffany Barnes |
| 2020 | EDM | Student Subtyping via EM-Inverse Reinforcement Learning. | Xi Yang, Guojing Zhou, Michelle Taub, Roger Azevedo, Min Chi |
| 2020 | IJCAI | Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract). | Guojing Zhou, Hamoon Azizsoltani, Markel Sanz Ausin, Tiffany Barnes, Min Chi |
| 2020 | MMM | PRIME: Block-Wise Missingness Handling for Multi-modalities in Intelligent Tutoring Systems. | Xi Yang, Yeo-Jin Kim, Michelle Taub, Roger Azevedo, Min Chi |
| 2019 | AIED | Hierarchical Reinforcement Learning for Pedagogical Policy Induction. | Guojing Zhou, Hamoon Azizsoltani, Markel Sanz Ausin, Tiffany Barnes, Min Chi |
| 2019 | CIKM | Streamline Density Peak Clustering for Practical Adoptions. | Shuai Yang, Xipeng Shen, Min Chi |
| 2019 | CogSci | Big, Little, or Both? Exploring the Impact of Granularity on Learning for Students with Different Incoming Competence. | Guojing Zhou, Xi Yang, Min Chi |
| 2019 | EDM | Leveraging Deep Reinforcement Learning for Pedagogical Policy Induction in an Intelligent Tutoring System. | Markel Sanz Ausin, Hamoon Azizsoltani, Tiffany Barnes, Min Chi |
| 2019 | EDM | Importance Sampling to Identify Empirically Valid Policies and their Critical Decisions. | Song Ju, Shitian Shen, Hamoon Azizsoltani, Tiffany Barnes, Min Chi |
| 2019 | EDM | Identifying Critical Pedagogical Decisions through Adversarial Deep Reinforcement Learning. | Song Ju, Guojing Zhou, Hamoon Azizsoltani, Tiffany Barnes, Min Chi |
| 2019 | EDM | One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks. | Ye Mao, Rui Zhi, Farzaneh Khoshnevisan, Thomas W. Price, Tiffany Barnes, Min Chi |
| 2019 | ICER | Evaluating the Effectiveness of Parsons Problems for Block-based Programming. | Rui Zhi, Min Chi, Tiffany Barnes, Thomas W. Price |
| 2019 | IJCAI | Unobserved Is Not Equal to Non-existent: Using Gaussian Processes to Infer Immediate Rewards Across Contexts. | Hamoon Azizsoltani, Yeo-Jin Kim, Markel Sanz Ausin, Tiffany Barnes, Min Chi |
| 2019 | IJCAI | ATTAIN: Attention-based Time-Aware LSTM Networks for Disease Progression Modeling. | Yuan Zhang, Xi Yang, Julie S. Ivy, Min Chi |
| 2019 | SIGCSE | Exploring the Impact of Worked Examples in a Novice Programming Environment. | Rui Zhi, Thomas W. Price, Samiha Marwan, Alexandra Milliken, Tiffany Barnes, Min Chi |
| 2018 | AIED | Empirically Evaluating the Effectiveness of POMDP vs. MDP Towards the Pedagogical Strategies Induction. | Shitian Shen, Behrooz Mostafavi, Collin F. Lynch, Tiffany Barnes, Min Chi |
| 2018 | IJCAI | Temporal Belief Memory: Imputing Missing Data during RNN Training. | Yeo-Jin Kim, Min Chi |
| 2017 | AIED | A Comparisons of BKT, RNN and LSTM for Learning Gain Prediction. | Chen Lin, Min Chi |
| 2017 | CogSci | The Impact of Decision Agency & Granularity on Aptitude Treatment Interaction in Tutoring. | Guojing Zhou, Min Chi |
| 2017 | EDM | Workshop proposal: deep learning for educational data mining. | Joseph Beck, Min Chi, Ryan S. Baker |
| 2017 | EDM | Clustering Student Sequential Trajectories Using Dynamic Time Wrapping. | Shitian Shen, Min Chi |
| 2017 | EDM | Mining Innovative Augmented Graph Grammars for Argument Diagrams through Novelty Selection. | Linting Xue, Collin F. Lynch, Min Chi |
| 2017 | EDM | Towards Closing the Loop: Bridging Machine-induced Pedagogical Policies to Learning Theories. | Guojing Zhou, Jianxun Wang, Collin F. Lynch, Min Chi |
| 2016 | CogSci | The Impact of Granularity on the Effectiveness of Students' Pedagogical Decisions. | Guojing Zhou, Collin F. Lynch, Thomas W. Price, Tiffany Barnes, Min Chi |
| 2016 | EDM | Aim Low: Correlation-based Feature Selection for Model-based Reinforcement Learning. | Shitian Shen, Min Chi |
| 2016 | EDM | Unnatural Feature Engineering: Evolving Augmented Graph Grammars for Argument Diagrams. | Linting Xue, Collin F. Lynch, Min Chi |
| 2016 | EDM | Deep Learning + Student Modeling + Clustering: a Recipe for Effective Automatic Short Answer Grading. | Yuan Zhang, Rajat Shah, Min Chi |
| 2016 | GECCO | Evolving Augmented Graph Grammars for Argument Analysis. | Collin F. Lynch, Linting Xue, Min Chi |
| 2016 | ITS | Intervention-BKT: Incorporating Instructional Interventions into Bayesian Knowledge Tracing. | Chen Lin, Min Chi |
| 2015 | AIED | Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor. | Behrooz Mostafavi, Guojing Zhou, Collin F. Lynch, Min Chi, Tiffany Barnes |
| 2015 | CogSci | The Impact of Granularity on Worked Examples and Problem Solving. | Guojing Zhou, Thomas W. Price, Collin F. Lynch, Tiffany Barnes, Min Chi |
| 2015 | DBSEC | Detecting Opinion Spammer Groups Through Community Discovery and Sentiment Analysis. | Euijin Choo, Ting Yu, Min Chi |
| 2015 | EDM | Using the Hint Factory to Compare Model-Based Tutoring Systems. | Collin F. Lynch, Thomas W. Price, Min Chi, Tiffany Barnes |
| 2015 | EDM | An Improved Data-Driven Hint Selection Algorithm for Probability Tutors. | Thomas W. Price, Collin F. Lynch, Tiffany Barnes, Min Chi |
| 2015 | EDM | Graph Grammar Induction via Evolutionary Computation. | Linting Xue, Collin F. Lynch, Min Chi |
| 2014 | EDM | Choice-based Assessment: Can Choices Made in Digital Games Predict 6th-Grade Students' Math Test Scores? | Min Chi, Daniel L. Schwartz, Kristen Pilner Blair, Doris B. Chin |
| 2014 | ITS | When Is Tutorial Dialogue More Effective Than Step-Based Tutoring? | Min Chi, Pamela W. Jordan, Kurt VanLehn |
| 2014 | ITS | Can Diagrams Predict Essay Grades? | Collin F. Lynch, Kevin D. Ashley, Min Chi |
| 2011 | EDM | Instructional Factors Analysis: A Cognitive Model For Multiple Instructional Interventions. | Min Chi, Kenneth R. Koedinger, Geoffrey J. Gordon, Pamela W. Jordan, Kurt VanLehn |
| 2011 | EDM | Improving Models of Slipping, Guessing, and Moment-By-Moment Learning with Estimates of Skill Difficulty. | Sujith M. Gowda, Jonathan P. Rowe, Ryan Shaun Joazeiro de Baker, Min Chi, Kenneth R. Koedinger |
| 2010 | ITS | Do Micro-Level Tutorial Decisions Matter: Applying Reinforcement Learning to Induce Pedagogical Tutorial Tactics. | Min Chi, Kurt VanLehn, Diane J. Litman |
| 2009 | AIED | To Elicit Or To Tell: Does It Matter? | Min Chi, Pamela W. Jordan, Kurt VanLehn, Diane J. Litman |
| 2008 | EDM | Reinforcement Learning-based Feature Seleciton For Developing Pedagogically Effective Tutorial Dialogue Tactics. | Min Chi, Pamela W. Jordan, Kurt VanLehn, Moses Hall |
| 2008 | ITS | Eliminating the Gap between the High and Low Students through Meta-cognitive Strategy Instruction. | Min Chi, Kurt VanLehn |
| 2007 | AIED | Accelerated Future Learning via Explicit Instruction of a Problem Solving Strategy. | Min Chi, Kurt VanLehn |
| 2007 | AIED | Domain-Specific and Domain-Independent Interactive Behaviors in Andes. | Min Chi, Kurt VanLehn |
| 2007 | AIED | Porting an Intelligent Tutoring System across Domains. | Min Chi, Kurt VanLehn |
| 2004 | ITS | Implicit Versus Explicit Learning of Strategies in a Non-procedural Cognitive Skill. | Kurt VanLehn, Dumiszewe Bhembe, Min Chi, Collin F. Lynch, Kay G. Schulze, Robert Shelby, Linwood Taylor, Donald Treacy, Anders Weinstein, Mary Wintersgill |