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2023 journal article
Healthful Connected Living: Vision and Challenges for the Case of Obesity
IEEE INTERNET COMPUTING, 27(3), 7β14.
2023 article
How and When: The Impact of Metacognitive Knowledge Instruction and Motivation on Transfer Across Intelligent Tutoring Systems
Abdelshiheed, M., Barnes, T., & Chi, M. (2023, September 27). INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION.
2023 article
Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning Towards Improved Problem Solving
Shabrina, P., Mostafavi, B., Abdelshiheed, M., Chi, M., & Barnes, T. (2023, August 21). INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION.
2023 journal article
TC-DTW: Accelerating multivariate dynamic time warping through triangle inequality and point clustering
INFORMATION SCIENCES, 621, 611β626.
2023 article
Time-aware deep reinforcement learning with multi-temporal abstraction
Kim, Y. J., & Chi, M. (2023, March 25). APPLIED INTELLIGENCE.
2022 article
Enhancing a student productivitymodel for adaptive problem-solving assistance
Maniktala, M., Chi, M., & Barnes, T. (2022, August 3). USER MODELING AND USER-ADAPTED INTERACTION.
2022 article
Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer
ARTIFICIAL INTELLIGENCE IN EDUCATION, PT I, Vol. 13355, pp. 546β552.
2022 article
Reconstructing Missing EHRs Using Time-Aware Within- and Cross-Visit Information for Septic Shock Early Prediction
2022 IEEE 10TH INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI 2022), pp. 151β162.
2022 article
Student-Tutor Mixed-Initiative Decision-Making Supported by Deep Reinforcement Learning
ARTIFICIAL INTELLIGENCE IN EDUCATION, PT I, Vol. 13355, pp. 440β452.
2022 article
The Impact of Batch Deep Reinforcement Learning on Student Performance: A Simple Act of Explanation Can Go A Long Way
Ausin, M. S., Maniktala, M., Barnes, T., & Chi, M. (2022, November 28). INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION.
2021 journal article
A Theoretical and Evidence-Based Conceptual Design of MetaDash: An Intelligent Teacher Dashboard to Support Teachers' Decision Making and Studentsβ Self-Regulated Learning
Frontiers in Education, 6.
2021 article
Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor (September, 10.1007/s40593-020-00213-3, 2020)
Maniktala, M., Cody, C., Barnes, T., & Chi, M. (2021, March). INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, Vol. 31, pp. 154β155.
2021 article
Data to Donations: Towards In-Kind Food Donation Prediction across Two Coasts
2021 IEEE GLOBAL HUMANITARIAN TECHNOLOGY CONFERENCE (GHTC), pp. 281β288.
2021 article
Evaluating Critical Reinforcement Learning Framework in the Field
ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 215β227.
2021 article
InferNet for Delayed Reinforcement Tasks: Addressing the Temporal Credit Assignment Problem
2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), pp. 1337β1348.
2021 article
Leveraging Granularity: Hierarchical Reinforcement Learning for Pedagogical Policy Induction
Zhou, G., Azizsoltani, H., Ausin, M. S., Barnes, T., & Chi, M. (2021, August 16). INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, Vol. 8.
2021 article
Multi-Temporal Abstraction with Time-Aware Deep Q-Learning for Septic Shock Prevention
2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), pp. 1657β1663.
2021 article
Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks
ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 356β368.
2021 article
The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor
Cody, C., Maniktala, M., Lytle, N., Chi, M., & Barnes, T. (2021, May 21). INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION.
2021 article
To Reduce Healthcare Workload: Identify Critical Sepsis Progression Moments through Deep Reinforcement Learning
2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), pp. 1640β1646.
2021 article
Unifying Domain Adaptation and Domain Generalization for Robust Prediction Across Minority Racial Groups
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, Vol. 12975, pp. 521β537.
2020 article
An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems
2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), pp. 64β73.
2020 article
An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis
ADVANCED ANALYTICS AND LEARNING ON TEMPORAL DATA, AALTD 2019, Vol. 11986, pp. 213β228.
2020 journal article
Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 30(4), 637β667.
2020 journal article
Going deeper: Automatic short-answer grading by combining student and question models
USER MODELING AND USER-ADAPTED INTERACTION, 30(1), 51β80.
2020 article
MuLan: Multilevel Language-based Representation Learning for Disease Progression Modeling
2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), pp. 1246β1255.
2020 article
PRIME: Block-Wise Missingness Handling for Multi-modalities in Intelligent Tutoring Systems
MULTIMEDIA MODELING (MMM 2020), PT II, Vol. 11962, pp. 63β75.
2019 article
Hierarchical Reinforcement Learning for Pedagogical Policy Induction
ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2019), PT I, Vol. 11625, pp. 544β556.
2018 chapter
Empirically Evaluating the Effectiveness of POMDP vs. MDP Towards the Pedagogical Strategies Induction
In Lecture Notes in Computer Science (pp. 327β331).
2018 article
Improving Learning & Reducing Time: A Constrained Action-Based Reinforcement Learning Approach
Improving Learning & Reducing Time: A Constrained Action-Based Reinforcement Learning Approach. PROCEEDINGS OF THE 26TH CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION (UMAP'18), pp. 43β51.
2017 chapter
A Comparisons of BKT, RNN and LSTM for Learning Gain Prediction
In Lecture Notes in Computer Science (pp. 536β539).
2017 conference paper
A Comparisons of BKT, RNN and LSTM for Learning Gain Prediction
Artificial intelligence in education, aied 2017, 10331, 536β539.
2017 conference paper
LSTM for septic shock: Adding unreliable labels to reliable predictions
2017 IEEE International Conference on Big Data (Big Data), 1233β1242.
2016 journal article
A comparison of two methods of active learning in physics: inventing a general solution versus compare and contrast
INSTRUCTIONAL SCIENCE, 44(2), 177β195.
2016 conference paper
An analysis of feature selection and reward function for model-based reinforcement learning
Intelligent tutoring systems, its 2016, 0684, 504β505.
2016 conference paper
Evolving augmented graph grammars for argument analysis
Proceedings of the 2016 Genetic and Evolutionary Computation Conference (GECCO'16 Companion), 65β66.
2016 chapter
Intervention-BKT: Incorporating Instructional Interventions into Bayesian Knowledge Tracing
In Intelligent Tutoring Systems (pp. 208β218).
2016 conference paper
Intervention-BKT: Incorporating instructional interventions into Bayesian knowledge tracing
Intelligent tutoring systems, its 2016, 0684, 208β218.
2015 chapter
Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor
In Lecture Notes in Computer Science (pp. 726β729).
2015 conference paper
Data-driven worked examples improve retention and completion in a logic tutor
Artificial intelligence in education, aied 2015, 9112, 726β729.
2015 chapter
Detecting Opinion Spammer Groups Through Community Discovery and Sentiment Analysis
In Data and Applications Security and Privacy XXIX (pp. 170β187).
2015 conference paper
Detecting opinion spammer groups through community discovery and sentiment analysis
Data and applications security and privacy xxix, 9149, 170β187.
2014 chapter
Can Diagrams Predict Essay Grades?
In Intelligent Tutoring Systems (pp. 260β265).
2014 chapter
When Is Tutorial Dialogue More Effective Than Step-Based Tutoring?
In Intelligent Tutoring Systems (pp. 210β219).
2014 conference paper
When is tutorial dialogue more effective than step-based tutoring?
Intelligent tutoring systems, its 2014, 8474, 210β219.
2011 journal article
Empirically evaluating the application of reinforcement learning to the induction of effective and adaptive pedagogical strategies
User Modeling and User-Adapted Interaction, 21(1-2), 137β180.
2010 chapter
Do Micro-Level Tutorial Decisions Matter: Applying Reinforcement Learning to Induce Pedagogical Tutorial Tactics
In Intelligent Tutoring Systems (pp. 224β234).
2010 chapter
Inducing Effective Pedagogical Strategies Using Learning Context Features
In User Modeling, Adaptation, and Personalization (pp. 147β158).
2008 chapter
Eliminating the Gap between the High and Low Students through Meta-cognitive Strategy Instruction
In Intelligent Tutoring Systems (pp. 603β613).
2004 chapter
Implicit Versus Explicit Learning of Strategies in a Non-procedural Cognitive Skill
In Intelligent Tutoring Systems (pp. 521β530).