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 (Intelligent Tutoring Systems, 2004)

Accelerated Future Learning via Explicit Instruction of a Problem Solving Strategy. - Min Chi; Kurt VanLehn (AIED, 2007)

Domain-Specific and Domain-Independent Interactive Behaviors in Andes. - Min Chi; Kurt VanLehn (AIED, 2007)

Porting an Intelligent Tutoring System across Domains. - Min Chi; Kurt VanLehn (AIED, 2007)

Reinforcement Learning-based Feature Seleciton For Developing Pedagogically Effective Tutorial Dialogue Tactics. - Min Chi; Pamela W. Jordan; Kurt VanLehn; Moses Hall (EDM, 2008)

Eliminating the Gap between the High and Low Students through Meta-cognitive Strategy Instruction. - Min Chi; Kurt VanLehn (Intelligent Tutoring Systems, 2008)

To Elicit Or To Tell: Does It Matter? - Min Chi; Pamela W. Jordan; Kurt VanLehn; Diane J. Litman (AIED, 2009)

Do Micro-Level Tutorial Decisions Matter: Applying Reinforcement Learning to Induce Pedagogical Tutorial Tactics. - Min Chi; Kurt VanLehn; Diane J. Litman (Intelligent Tutoring Systems (1), 2010)

Inducing Effective Pedagogical Strategies Using Learning Context Features. - Min Chi; Kurt VanLehn; Diane J. Litman; Pamela W. Jordan (UMAP, 2010)

Meta-Cognitive Strategy Instruction in Intelligent Tutoring Systems: How, When, and Why. - Min Chi; Kurt VanLehn (J. Educ. Technol. Soc., 2010)

Instructional Factors Analysis: A Cognitive Model For Multiple Instructional Interventions. - Min Chi; Kenneth R. Koedinger; Geoffrey J. Gordon; Pamela W. Jordan; Kurt VanLehn (EDM, 2011)

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 (EDM, 2011)

An Evaluation of Pedagogical Tutorial Tactics for a Natural Language Tutoring System: A Reinforcement Learning Approach. - Min Chi; Kurt VanLehn; Diane J. Litman; Pamela W. Jordan (Int. J. Artif. Intell. Educ., 2011)

Empirically evaluating the application of reinforcement learning to the induction of effective and adaptive pedagogical strategies. - Min Chi; Kurt VanLehn; Diane J. Litman; Pamela W. Jordan (User Model. User Adapt. Interact., 2011)

Choice-based Assessment: Can Choices Made in Digital Games Predict 6th-Grade Students' Math Test Scores? - Min Chi; Daniel L. Schwartz 001; Kristen Pilner Blair; Doris B. Chin (EDM, 2014)

Tug of War: What is it Good For? Measuring Student Inquiry Choices in an Online Science Game. - Nicole R. Hallinen; Julius Cheng; Min Chi; Daniel L. Schwartz 001 (ICLS, 2014)

When Is Tutorial Dialogue More Effective Than Step-Based Tutoring? - Min Chi; Pamela W. Jordan; Kurt VanLehn (Intelligent Tutoring Systems, 2014)

Can Diagrams Predict Essay Grades? - Collin F. Lynch; Kevin D. Ashley; Min Chi (Intelligent Tutoring Systems, 2014)

Revealing and incorporating implicit communities to improve recommender systems. - Euijin Choo; Ting Yu 001; Min Chi; Yan Sun 001 (EC, 2014)

Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor. - Behrooz Mostafavi; Guojing Zhou; Collin F. Lynch; Min Chi; Tiffany Barnes (AIED, 2015)

The Impact of Granularity on Worked Examples and Problem Solving. - Guojing Zhou; Thomas W. Price; Collin F. Lynch; Tiffany Barnes; Min Chi (CogSci, 2015)

Detecting Opinion Spammer Groups Through Community Discovery and Sentiment Analysis. - Euijin Choo; Ting Yu 001; Min Chi (DBSec, 2015)

Using the Hint Factory to Compare Model-Based Tutoring Systems. - Collin F. Lynch; Thomas W. Price; Min Chi; Tiffany Barnes (EDM (Workshops), 2015)

An Improved Data-Driven Hint Selection Algorithm for Probability Tutors. - Thomas W. Price; Collin F. Lynch; Tiffany Barnes; Min Chi (EDM, 2015)

Graph Grammar Induction via Evolutionary Computation. - Linting Xue; Collin F. Lynch; Min Chi (EDM (Workshops), 2015)

The Impact of Granularity on the Effectiveness of Students' Pedagogical Decisions. - Guojing Zhou; Collin F. Lynch; Thomas W. Price; Tiffany Barnes; Min Chi (CogSci, 2016)

Aim Low: Correlation-based Feature Selection for Model-based Reinforcement Learning. - Shitian Shen; Min Chi (EDM, 2016)

Unnatural Feature Engineering: Evolving Augmented Graph Grammars for Argument Diagrams. - Linting Xue; Collin F. Lynch; Min Chi (EDM, 2016)

Deep Learning + Student Modeling + Clustering: a Recipe for Effective Automatic Short Answer Grading. - Yuan Zhang; Rajat Shah; Min Chi (EDM, 2016)

Evolving Augmented Graph Grammars for Argument Analysis. - Collin F. Lynch; Linting Xue; Min Chi (GECCO (Companion), 2016)

Intervention-BKT: Incorporating Instructional Interventions into Bayesian Knowledge Tracing. - Chen Lin; Min Chi (ITS, 2016)

Incorporating Student Response Time and Tutor Instructional Interventions into Student Modeling. - Chen Lin; Shitian Shen; Min Chi (UMAP, 2016)

Reinforcement Learning: the Sooner the Better, or the Later the Better? - Shitian Shen; Min Chi (UMAP, 2016)

A Comparisons of BKT, RNN and LSTM for Learning Gain Prediction. - Chen Lin; Min Chi (AIED, 2017)

LSTM for septic shock: Adding unreliable labels to reliable predictions. - Yuan Zhang 028; Chen Lin; Min Chi; Julie S. Ivy; Muge Capan; Jeanne M. Huddleston (IEEE BigData, 2017)

The Impact of Decision Agency & Granularity on Aptitude Treatment Interaction in Tutoring. - Guojing Zhou; Min Chi (CogSci, 2017)

Workshop proposal: deep learning for educational data mining. - Joseph Beck 001; Min Chi; Ryan S. Baker 001 (EDM, 2017)

Clustering Student Sequential Trajectories Using Dynamic Time Wrapping. - Shitian Shen; Min Chi (EDM, 2017)

Mining Innovative Augmented Graph Grammars for Argument Diagrams through Novelty Selection. - Linting Xue; Collin F. Lynch; Min Chi (EDM, 2017)

Towards Closing the Loop: Bridging Machine-induced Pedagogical Policies to Learning Theories. - Guojing Zhou; Jianxun Wang 002; Collin F. Lynch; Min Chi (EDM, 2017)

Detecting opinion spammer groups and spam targets through community discovery and sentiment analysis. - Euijin Choo; Ting Yu 001; Min Chi (J. Comput. Secur., 2017)

Empirically Evaluating the Effectiveness of POMDP vs. MDP Towards the Pedagogical Strategies Induction. - Shitian Shen; Behrooz Mostafavi; Collin F. Lynch; Tiffany Barnes; Min Chi (AIED (2), 2018)

Time-aware Subgroup Matrix Decomposition: Imputing Missing Data Using Forecasting Events. - Xi Yang 019; Yuan Zhang 028; Min Chi (IEEE BigData, 2018)

Recent Temporal Pattern Mining for Septic Shock Early Prediction. - Farzaneh Khoshnevisan; Julie S. Ivy; Muge Capan; Ryan Arnold; Jeanne Huddleston; Min Chi (ICHI, 2018)

Early Diagnosis and Prediction of Sepsis Shock by Combining Static and Dynamic Information Using Convolutional-LSTM. - Chen Lin; Yuan Zhang 028; Julie S. Ivy; Muge Capan; Ryan Arnold; Jeanne M. Huddleston; Min Chi (ICHI, 2018)

Temporal Belief Memory: Imputing Missing Data during RNN Training. - Yeo-Jin Kim; Min Chi (IJCAI, 2018)

Improving Learning & Reducing Time: A Constrained Action-Based Reinforcement Learning Approach. - Shitian Shen; Markel Sanz Ausin; Behrooz Mostafavi; Min Chi (UMAP, 2018)

Hierarchical Reinforcement Learning for Pedagogical Policy Induction. - Guojing Zhou; Hamoon Azizsoltani; Markel Sanz Ausin; Tiffany Barnes; Min Chi (AIED (1), 2019)

Network-Based Modeling of Sepsis: Quantification and Evaluation of Simultaneity of Organ Dysfunctions. - Ali Jazayeri; Muge Capan; Christopher C. Yang; Farzaneh Khoshnevisan; Min Chi; Ryan Arnold (BCB, 2019)

Multi-layer Facial Representation Learning for Early Prediction of Septic Shock. - Chen Lin; Julie S. Ivy; Min Chi (IEEE BigData, 2019)

Streamline Density Peak Clustering for Practical Adoptions. - Shuai Yang; Xipeng Shen; Min Chi (CIKM, 2019)

Big, Little, or Both? Exploring the Impact of Granularity on Learning for Students with Different Incoming Competence. - Guojing Zhou; Xi Yang 019; Min Chi (CogSci, 2019)

Leveraging Deep Reinforcement Learning for Pedagogical Policy Induction in an Intelligent Tutoring System. - Markel Sanz Ausin; Hamoon Azizsoltani; Tiffany Barnes; Min Chi (EDM, 2019)

Importance Sampling to Identify Empirically Valid Policies and their Critical Decisions. - Song Ju; Shitian Shen; Hamoon Azizsoltani; Tiffany Barnes; Min Chi (EDM (Workshops), 2019)

Identifying Critical Pedagogical Decisions through Adversarial Deep Reinforcement Learning. - Song Ju; Guojing Zhou; Hamoon Azizsoltani; Tiffany Barnes; Min Chi (EDM, 2019)

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 (EDM, 2019)

Evaluating the Effectiveness of Parsons Problems for Block-based Programming. - Rui Zhi; Min Chi; Tiffany Barnes; Thomas W. Price (ICER, 2019)

Missing Data Imputation for MIMIC-III using Matrix Decomposition. - Xi Yang 019; Yeo-Jin Kim; Farzaneh Khoshnevisan; Yuan Zhang 028; Min Chi (ICHI, 2019)

Time-aware Adversarial Networks for Adapting Disease Progression Modeling. - Yuan Zhang 028; Xi Yang 019; Julie S. Ivy; Min Chi (ICHI, 2019)

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 (IJCAI, 2019)

ATTAIN: Attention-based Time-Aware LSTM Networks for Disease Progression Modeling. - Yuan Zhang 028; Xi Yang 019; Julie S. Ivy; Min Chi (IJCAI, 2019)

An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis. - Daniel Shen; Min Chi (AALTD@PKDD/ECML, 2019)

Exploring the Impact of Worked Examples in a Novice Programming Environment. - Rui Zhi; Thomas W. Price; Samiha Marwan; Alexandra Milliken; Tiffany Barnes; Min Chi (SIGCSE, 2019)

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 (AIED (1), 2020)

An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems. - Farzaneh Khoshnevisan; Min Chi (IEEE BigData, 2020)

MuLan: Multilevel Language-based Representation Learning for Disease Progression Modeling. - Hyunwoo Sohn; Kyungjin Park; Min Chi (IEEE BigData, 2020)

Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. - Mark Abdelshiheed; Min Chi (CogSci, 2020)

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 (EDM, 2020)

Pick the Moment: Identifying Critical Pedagogical Decisions Using Long-Short Term Rewards. - Song Ju; Min Chi; Guojing Zhou (EDM, 2020)

Extending the Hint Factory: Towards Modelling Productivity for Open-ended Problem-solving. - Mehak Maniktala; Tiffany Barnes; Min Chi (EDM, 2020)

What Time is It? Student Modeling Needs to Know. - Ye Mao; Samiha Marwan; Thomas W. Price; Tiffany Barnes; Min Chi (EDM, 2020)

Immediate Data-Driven Positive Feedback Increases Engagement on Programming Homework for Novices. - Samiha Marwan; Thomas W. Price; Min Chi; Tiffany Barnes (CSEDM@EDM, 2020)

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 (CSEDM@EDM, 2020)

Student Subtyping via EM-Inverse Reinforcement Learning. - Xi Yang 019; Guojing Zhou; Michelle Taub; Roger Azevedo; Min Chi (EDM, 2020)

Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract). - Guojing Zhou; Hamoon Azizsoltani; Markel Sanz Ausin; Tiffany Barnes; Min Chi (IJCAI, 2020)

PRIME: Block-Wise Missingness Handling for Multi-modalities in Intelligent Tutoring Systems. - Xi Yang 019; Yeo-Jin Kim; Michelle Taub; Roger Azevedo; Min Chi (MMM (2), 2020)

Improving Student-System Interaction Through Data-driven Explanations of Hierarchical Reinforcement Learning Induced Pedagogical Policies. - Guojing Zhou; Xi Yang 019; Hamoon Azizsoltani; Tiffany Barnes; Min Chi (UMAP, 2020)

Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. - Mehak Maniktala; Christa Cody; Tiffany Barnes; Min Chi (Int. J. Artif. Intell. Educ., 2020)

Extending the Hint Factory for the assistance dilemma: A novel, data-driven HelpNeed Predictor for proactive problem-solving help. - Mehak Maniktala; Christa Cody; Amy Isvik; Nicholas Lytle; Min Chi; Tiffany Barnes (CoRR, 2020)

Going deeper: Automatic short-answer grading by combining student and question models. - Yuan Zhang 028; Chen Lin; Min Chi (User Model. User Adapt. Interact., 2020)

Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks. - Markel Sanz Ausin; Mehak Maniktala; Tiffany Barnes; Min Chi (AIED (1), 2021)

Evaluating Critical Reinforcement Learning Framework in the Field. - Song Ju; Guojing Zhou; Mark Abdelshiheed; Tiffany Barnes; Min Chi (AIED (1), 2021)

InferNet for Delayed Reinforcement Tasks: Addressing the Temporal Credit Assignment Problem. - Markel Sanz Ausin; Hamoon Azizsoltani; Song Ju; Yeo-Jin Kim; Min Chi (IEEE BigData, 2021)

To Reduce Healthcare Workload: Identify Critical Sepsis Progression Moments through Deep Reinforcement Learning. - Song Ju; Yeo Jin Kim; Markel Sanz Ausin; Maria E. Mayorga; Min Chi (IEEE BigData, 2021)

Multi-Temporal Abstraction with Time-Aware Deep Q-Learning for Septic Shock Prevention. - Yeo Jin Kim; Markel Sanz Ausin; Min Chi (IEEE BigData, 2021)

Preparing Unprepared Students For Future Learning. - Mark Abdelshiheed; Mehak Maniktala; Song Ju; Ayush Jain; Tiffany Barnes; Min Chi (CogSci, 2021)

More With Less: Exploring How to Use Deep Learning Effectively through Semi-supervised Learning for Automatic Bug Detection in Student Code. - Yang Shi 004; Ye Mao; Tiffany Barnes; Min Chi; Thomas W. Price (EDM, 2021)

Knowing both when and where: Temporal-ASTNN for Early Prediction of Student Success in Novice Programming Tasks. - Ye Mao; Yang Shi 004; Samiha Marwan; Thomas W. Price; Tiffany Barnes; Min Chi (EDM, 2021)

Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming. - Samiha Marwan; Yang Shi 004; Ian Menezes; Min Chi; Tiffany Barnes; Thomas W. Price (EDM, 2021)

Data to Donations: Towards In-Kind Food Donation Prediction across Two Coasts. - Esha Sharma; Lauren B. Davis; Julie S. Ivy; Min Chi (GHTC, 2021)

Multi-series Time-aware Sequence Partitioning for Disease Progression Modeling. - Xi Yang 019; Yuan Zhang 028; Min Chi (IJCAI, 2021)

Making a (Counterfactual) Difference One Rationale at a Time. - Mitchell Plyler; Michael Green; Min Chi (NeurIPS, 2021)

Unifying Domain Adaptation and Domain Generalization for Robust Prediction Across Minority Racial Groups. - Farzaneh Khoshnevisan; Min Chi (ECML/PKDD (1), 2021)

Correction to: Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. - Mehak Maniktala; Christa Cody; Tiffany Barnes; Min Chi (Int. J. Artif. Intell. Educ., 2021)

TC-DTW: Accelerating Multivariate Dynamic Time Warping Through Triangle Inequality and Point Clustering. - Daniel Shen; Min Chi (CoRR, 2021)

Time-Aware Q-Networks: Resolving Temporal Irregularity for Deep Reinforcement Learning. - Yeo-Jin Kim; Min Chi (CoRR, 2021)

Cross-Lingual Adversarial Domain Adaptation for Novice Programming. - Ye Mao; Farzaneh Khoshnevisan; Thomas W. Price; Tiffany Barnes; Min Chi (AAAI, 2022)

Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer. - Mark Abdelshiheed; John Wesley Hostetter; Xi Yang 019; Tiffany Barnes; Min Chi (AIED (1), 2022)

Student-Tutor Mixed-Initiative Decision-Making Supported by Deep Reinforcement Learning. - Song Ju; Xi Yang 019; Tiffany Barnes; Min Chi (AIED (1), 2022)

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 (CogSci, 2022)

Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks. - Yang Shi 004; Min Chi; Tiffany Barnes; Thomas W. Price (EDM, 2022)

Reconstructing Missing EHRs Using Time-Aware Within- and Cross-Visit Information for Septic Shock Early Prediction. - Ge Gao; Farzaneh Khoshnevisan; Min Chi (ICHI, 2022)

A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification. - Ge Gao; Qitong Gao; Xi Yang 019; Miroslav Pajic; Min Chi (IJCAI, 2022)

The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor. - Christa Cody; Mehak Maniktala; Nicholas Lytle; Min Chi; Tiffany Barnes (Int. J. Artif. Intell. Educ., 2022)

Leveraging Granularity: Hierarchical Reinforcement Learning for Pedagogical Policy Induction. - Guojing Zhou; Hamoon Azizsoltani; Markel Sanz Ausin; Tiffany Barnes; Min Chi (Int. J. Artif. Intell. Educ., 2022)

A Multicriteria Evaluation for Data-Driven Programming Feedback Systems: Accuracy, Effectiveness, Fallibility, and Students' Response. - Preya Shabrina; Samiha Marwan; Andrew Bennison; Min Chi; Thomas W. Price; Tiffany Barnes (CoRR, 2022)

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 (AAAI, 2023)

Leveraging Deep Reinforcement Learning for Metacognitive Interventions Across Intelligent Tutoring Systems. - Mark Abdelshiheed; John Wesley Hostetter; Tiffany Barnes; Min Chi (AIED, 2023)

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 (AIED (Posters/Late Breaking Results/...), 2023)

A Unified Batch Hierarchical Reinforcement Learning Framework for Pedagogical Policy Induction with Deep Bisimulation Metrics. - Markel Sanz Ausin; Mark Abdelshiheed; Tiffany Barnes; Min Chi (AIED (Posters/Late Breaking Results/...), 2023)

Impact of Learning a Subgoal-Directed Problem-Solving Strategy Within an Intelligent Logic Tutor. - Preya Shabrina; Behrooz Mostafavi; Min Chi; Tiffany Barnes (AIED, 2023)

HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare. - Ge Gao; Song Ju; Markel Sanz Ausin; Min Chi (AAMAS, 2023)

A Self-Organizing Neuro-Fuzzy Q-Network: Systematic Design with Offline Hybrid Learning. - John Wesley Hostetter; Mark Abdelshiheed; Tiffany Barnes; Min Chi (AAMAS, 2023)

Bridging Declarative, Procedural, and Conditional Metacognitive Knowledge Gap Using Deep Reinforcement Learning. - Mark Abdelshiheed; John Wesley Hostetter; Tiffany Barnes; Min Chi (CogSci, 2023)

KC-Finder: Automated Knowledge Component Discovery for Programming Problems. - Yang Shi 004; Robin Schmucker; Min Chi; Tiffany Barnes; Thomas W. Price (EDM, 2023)

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 (EDM, 2023)

Leveraging Fuzzy Logic Towards More Explainable Reinforcement Learning-Induced Pedagogical Policies on Intelligent Tutoring Systems. - John Wesley Hostetter; Mark Abdelshiheed; Tiffany Barnes; Min Chi (FUZZ, 2023)

Latent Space Encoding for Interpretable Fuzzy Logic Rules in Continuous and Noisy High-Dimensional Spaces. - John Wesley Hostetter; Min Chi (FUZZ, 2023)

Trace Augmentation with Missing EHRs for Sepsis Treatments. - Ge Gao; Min Chi (ICHI, 2023)

Variational Latent Branching Model for Off-Policy Evaluation. - Qitong Gao; Ge Gao; Min Chi; Miroslav Pajic (ICLR, 2023)

Hierarchical Apprenticeship Learning for Disease Progression Modeling. - Xi Yang 019; Ge Gao; Min Chi (IJCAI, 2023)

XAI to Increase the Effectiveness of an Intelligent Pedagogical Agent. - John Wesley Hostetter; Cristina Conati; Xi Yang 019; Mark Abdelshiheed; Tiffany Barnes; Min Chi (IVA, 2023)

Off-Policy Evaluation for Human Feedback. - Qitong Gao; Ge Gao; Juncheng Dong; Vahid Tarokh; Min Chi; Miroslav Pajic (NeurIPS, 2023)

Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. - Mark Abdelshiheed; Guojing Zhou; Mehak Maniktala; Tiffany Barnes; Min Chi (CoRR, 2023)

Assessing Competency Using Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. - Mark Abdelshiheed; Mehak Maniktala; Tiffany Barnes; Min Chi (CoRR, 2023)

An Offline Time-aware Apprenticeship Learning Framework for Evolving Reward Functions. - Xi Yang 019; Ge Gao; Min Chi (CoRR, 2023)

Healthful Connected Living: Vision and Challenges for the Case of Obesity. - Munindar P. Singh; Min Chi; Veena Misra (IEEE Internet Comput., 2023)

Enhancing a student productivity model for adaptive problem-solving assistance. - Mehak Maniktala; Min Chi; Tiffany Barnes (User Model. User Adapt. Interact., 2023)

TC-DTW: Accelerating multivariate dynamic time warping through triangle inequality and point clustering. - Daniel S. Shen; Min Chi (Inf. Sci., 2023)

Time-aware deep reinforcement learning with multi-temporal abstraction. - Yeo Jin Kim; Min Chi (Appl. Intell., 2023)

The Impact of Batch Deep Reinforcement Learning on Student Performance: A Simple Act of Explanation Can Go A Long Way. - Markel Sanz Ausin; Mehak Maniktala; Tiffany Barnes; Min Chi (Int. J. Artif. Intell. Educ., 2023)

Get a Head Start: On-Demand Pedagogical Policy Selection in Intelligent Tutoring. - Ge Gao; Xi Yang 019; Min Chi (AAAI, 2024)

Evaluating Multi-Knowledge Component Interpretability of Deep Knowledge Tracing Models in Programming. - Yang Shi 004; Min Chi; Tiffany Barnes; Thomas W. Price (EDM, 2024)

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 (EDM, 2024)

A Generalized Apprenticeship Learning Framework for Modeling Heterogeneous Student Pedagogical Strategies. - Md. Mirajul Islam; Xi Yang 019; John Wesley Hostetter; Adittya Soukarjya Saha; Min Chi (EDM, 2024)

More, May not the Better: Insights from Applying Deep Reinforcement Learning for Pedagogical Policy Induction. - Gyuhun Jung; Markel Sanz Ausin; Tiffany Barnes; Min Chi (EDM, 2024)

On Trajectory Augmentations for Off-Policy Evaluation. - Ge Gao; Qitong Gao; Xi Yang 019; Song Ju; Miroslav Pajic; Min Chi (ICLR, 2024)

Multi-TA: Multilevel Temporal Augmentation for Robust Septic Shock Early Prediction. - Hyunwoo Sohn; Kyungjin Park; Baekkwan Park; Min Chi (IJCAI, 2024)

Off-Policy Selection for Initiating Human-Centric Experimental Design. - Ge Gao; Xi Yang 019; Qitong Gao; Song Ju; Miroslav Pajic; Min Chi (NeurIPS, 2024)

How and When: The Impact of Metacognitive Knowledge Instruction and Motivation on Transfer Across Intelligent Tutoring Systems. - Mark Abdelshiheed; Tiffany Barnes; Min Chi (Int. J. Artif. Intell. Educ., 2024)

Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning Towards Improved Problem Solving. - Preya Shabrina; Behrooz Mostafavi; Mark Abdelshiheed; Min Chi; Tiffany Barnes (Int. J. Artif. Intell. Educ., 2024)

Example, nudge, or practice? Assessing metacognitive knowledge transfer of factual and procedural learners. - Mark Abdelshiheed; Robert Moulder; John Wesley Hostetter; Tiffany Barnes; Min Chi (User Model. User Adapt. Interact., 2024)

Iterative Counterfactual Data Augmentation. - Mitchell Plyler; Min Chi (AAAI, 2025)

Determining Problem Type Using Deep Reinforcement Learning in a Data-Driven Intelligent Tutor. - Nazia Alam; Kimia Fazeli; Xiaoyi Tian 001; Min Chi; Tiffany Barnes (AIED (6), 2025)

A Generalized Apprenticeship Learning Framework for Capturing Evolving Student Pedagogical Strategies. - Md. Mirajul Islam; Xi Yang 019; Rajesh Debnath; Adittya Shoukarjya Saha; Min Chi (AIED (3), 2025)

Investigating the Impact and Student Perceptions of Guided Parsons Problems for Learning Logic with Subgoals. - Sutapa Dey Tithi; Xiaoyi Tian 001; Min Chi; Tiffany Barnes (CoRR, 2025)

Attention-Based Reward Shaping for Sparse and Delayed Rewards. - Ian Holmes; Min Chi (CoRR, 2025)

Gradient-Based Neuroplastic Adaptation for Concurrent Optimization of Neuro-Fuzzy Networks. - John Wesley Hostetter; Min Chi (CoRR, 2025)