Works (47)

Updated: April 17th, 2023 12:48

2023 journal article

TC-DTW: Accelerating multivariate dynamic time warping through triangle inequality and point clustering

INFORMATION SCIENCES, 621, 611–626.

By: D. Shen & M. Chi

Source: Web Of Science
Added: January 17, 2023

2023 article

Time-aware deep reinforcement learning with multi-temporal abstraction

Kim, Y. J., & Chi, M. (2023, March 25). APPLIED INTELLIGENCE.

By: Y. Kim & M. Chi

author keywords: Time-aware; Temporal abstraction; Deep reinforcement learning; Irregular time series; RL for real-world applications; Nuclear reactor control; Sepsis treatment
Source: Web Of Science
Added: April 11, 2023

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.

By: M. Maniktala, M. Chi & T. Barnes

author keywords: Adaptive support; Student modeling; Assistance dilemma; Unproductivity; Data-driven tutoring; Propositional logic
Source: Web Of Science
Added: August 15, 2022

2022 article

Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer

ARTIFICIAL INTELLIGENCE IN EDUCATION, PT I, Vol. 13355, pp. 546–552.

By: M. Abdelshiheed, J. Hostetter, . Yang, T. Barnes & M. Chi

author keywords: Strategy awareness; Time awareness; Metacognitive skill instruction; Preparation for future learning; Backward chaining
Source: Web Of Science
Added: November 21, 2022

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. 151–162.

By: G. Gao, F. Khoshnevisan & M. Chi

author keywords: Electronic Health Records(EHRs); EHRs Imputation; Septic Shock Early Prediction
Source: Web Of Science
Added: October 31, 2022

2022 article

Student-Tutor Mixed-Initiative Decision-Making Supported by Deep Reinforcement Learning

ARTIFICIAL INTELLIGENCE IN EDUCATION, PT I, Vol. 13355, pp. 440–452.

By: S. Ju n, . Yang n, T. Barnes & M. Chi

author keywords: Critical decisions; Reinforcement learning; Student choice
Source: Web Of Science
Added: November 21, 2022

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.

author keywords: Deep reinforcement learning; Pedagogical policy; Explanation
Sources: Web Of Science, ORCID
Added: November 29, 2022

2021 journal article

A Theoretical and Evidence-Based Conceptual Design of MetaDash: An Intelligent Teacher Dashboard to Support Teachers' Decision Making and Students’ Self-Regulated Learning

Frontiers in Education, 6.

By: M. Wiedbusch, V. Kite*, X. Yang*, S. Park, M. Chi, M. Taub, R. Azevedo

author keywords: self-regulated learning (SRL); teacher decision making; learning; multimodal data; teacher dashboards
Sources: Web Of Science, ORCID, Crossref
Added: August 23, 2021

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. 154–155.

By: M. Maniktala, C. Cody, T. Barnes & M. Chi

Source: Web Of Science
Added: December 21, 2020

2021 article

Data to Donations: Towards In-Kind Food Donation Prediction across Two Coasts

2021 IEEE GLOBAL HUMANITARIAN TECHNOLOGY CONFERENCE (GHTC), pp. 281–288.

By: E. Sharma n, L. Davis*, J. Ivy & M. Chi

author keywords: Food Insecurity; Humanitarian Supply Chain; Bayesian Structural Time Series; Long Short Term Memory; Training Length; Expanding and Sliding Window
Source: Web Of Science
Added: March 28, 2022

2021 article

Evaluating Critical Reinforcement Learning Framework in the Field

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 215–227.

By: S. Ju n, G. Zhou, M. Abdelshiheed, T. Barnes & M. Chi

author keywords: Critical decisions; Reinforcement learning; ITS
Source: Web Of Science
Added: November 28, 2022

2021 article

InferNet for Delayed Reinforcement Tasks: Addressing the Temporal Credit Assignment Problem

2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), pp. 1337–1348.

By: M. Ausin n, H. Azizsoltani, S. Ju n, Y. Kim & M. Chi

author keywords: Credit Assignment Problem; Deep Reinforcement Learning
Source: Web Of Science
Added: July 5, 2022

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.

author keywords: Hierarchical reinforcement learning; Decision granularity; Pedagogical policy
Sources: Web Of Science, ORCID
Added: August 23, 2021

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. 1657–1663.

By: Y. Kim, M. Ausin n & M. Chi

author keywords: deep reinforcement learning; time-aware; temporal abstraction; sepsis
Source: Web Of Science
Added: July 5, 2022

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. 356–368.

author keywords: Pedagogical agent; Credit assignment problem; Deep reinforcement learning
Sources: Web Of Science, ORCID
Added: June 16, 2021

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.

By: C. Cody, M. Maniktala, N. Lytle n, M. Chi & T. Barnes

author keywords: Tutoring system; Hints; Assistance; Data-driven methods
Source: Web Of Science
Added: June 10, 2021

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. 1640–1646.

By: S. Ju n, Y. Kim, M. Ausin n, M. Mayorga & M. Chi

author keywords: Reinforcement Learning; Sepsis; Critical Decision
Sources: Web Of Science, ORCID
Added: July 5, 2022

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. 521–537.

By: F. Khoshnevisan* & M. Chi

author keywords: Domain adaptation; Domain generalization; Cross-racial transfer; Septic shock
Source: Web Of Science
Added: November 15, 2021

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. 64–73.

By: F. Khoshnevisan n & M. Chi

author keywords: adversarial domain adaptation variational RNN; Electronic health Record; septic shock; early prediction
Source: Web Of Science
Added: July 26, 2021

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. 213–228.

By: D. Shen* & M. Chi

author keywords: DTW; Time series analytics; Algorithm optimizations; Electrocardiogram
Source: Web Of Science
Added: June 21, 2021

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), 637–667.

By: M. Maniktala, C. Cody, T. Barnes & M. Chi

author keywords: Intelligent tutoring system; Help avoidance; User experience; Unsolicited hints; Aptitude-treatment interaction; Logic proofs; Productive persistence; Clustering; problem solving
Source: Web Of Science
Added: November 9, 2020

2020 journal article

Going deeper: Automatic short-answer grading by combining student and question models

USER MODELING AND USER-ADAPTED INTERACTION, 30(1), 51–80.

By: Y. Zhang, C. Lin & M. Chi

author keywords: Automatic short-answer grading; Machine learning; Deep belief network
Source: Web Of Science
Added: March 30, 2020

2020 article

MuLan: Multilevel Language-based Representation Learning for Disease Progression Modeling

2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), pp. 1246–1255.

By: H. Sohn, K. Park & M. Chi

author keywords: Electronic health records; disease progression modeling; interpretability; representation learning
Source: Web Of Science
Added: July 26, 2021

2020 article

PRIME: Block-Wise Missingness Handling for Multi-modalities in Intelligent Tutoring Systems

MULTIMEDIA MODELING (MMM 2020), PT II, Vol. 11962, pp. 63–75.

By: . Yang n, Y. Kim, M. Taub, R. Azevedo & M. Chi

author keywords: Multimodal; Block-wise missing; Learning gain prediction
Source: Web Of Science
Added: February 22, 2021

2019 article

Hierarchical Reinforcement Learning for Pedagogical Policy Induction

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2019), PT I, Vol. 11625, pp. 544–556.

author keywords: Hierarchical Reinforcement Learning; Pedagogical policies
Sources: Web Of Science, ORCID
Added: December 2, 2019

2018 chapter

Empirically Evaluating the Effectiveness of POMDP vs. MDP Towards the Pedagogical Strategies Induction

In Lecture Notes in Computer Science (pp. 327–331).

By: S. Shen n, B. Mostafavi n, C. Lynch, T. Barnes & M. Chi

author keywords: Reinforcement Learning; POMDP; MDP; ITS
Source: Crossref
Added: January 19, 2020

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. 43–51.

author keywords: Constrained Reinforcement Learning; POMDP; Intelligent Tutoring System
Source: Web Of Science
Added: April 2, 2019

2017 conference paper

A Comparisons of BKT, RNN and LSTM for Learning Gain Prediction

Artificial intelligence in education, aied 2017, 10331, 536–539.

By: C. Lin & M. Chi

Source: NC State University Libraries
Added: August 6, 2018

2017 chapter

A Comparisons of BKT, RNN and LSTM for Learning Gain Prediction

In Lecture Notes in Computer Science (pp. 536–539).

By: C. Lin n & M. Chi

author keywords: LSTM; RNN; BKT; Learning gain prediction
Source: Crossref
Added: February 24, 2020

2017 conference paper

LSTM for septic shock: Adding unreliable labels to reliable predictions

2017 IEEE International Conference on Big Data (Big Data), 1233–1242.

By: Y. Zhang, C. Lin, M. Chi, J. Ivy, M. Capan* & J. Huddleston*

Source: NC State University Libraries
Added: August 6, 2018

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), 177–195.

By: D. Chin*, M. Chi & D. Schwartz*

author keywords: Science education; Science instruction; Inventing; Compare and contrast; Contrasting cases
Source: Web Of Science
Added: August 6, 2018

2016 conference paper

An analysis of feature selection and reward function for model-based reinforcement learning

Intelligent tutoring systems, its 2016, 0684, 504–505.

Source: NC State University Libraries
Added: August 6, 2018

2016 conference paper

Evolving augmented graph grammars for argument analysis

Proceedings of the 2016 Genetic and Evolutionary Computation Conference (GECCO'16 Companion), 65–66.

By: C. Lynch, L. Xue & M. Chi

Source: NC State University Libraries
Added: August 6, 2018

2016 chapter

Intervention-BKT: Incorporating Instructional Interventions into Bayesian Knowledge Tracing

In Intelligent Tutoring Systems (pp. 208–218).

By: C. Lin & M. Chi

author keywords: Knowledge tracing; Hidden Markov Model; Input Output Hidden Markov Model; Student modeling; Instructional intervention
Source: Crossref
Added: February 24, 2020

2016 conference paper

Intervention-BKT: Incorporating instructional interventions into Bayesian knowledge tracing

Intelligent tutoring systems, its 2016, 0684, 208–218.

By: C. Lin & M. Chi

Source: NC State University Libraries
Added: August 6, 2018

2015 chapter

Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor

In Lecture Notes in Computer Science (pp. 726–729).

By: B. Mostafavi n, G. Zhou n, C. Lynch, M. Chi & T. Barnes

author keywords: Worked examples; Data-driven; Problem-solving
Source: Crossref
Added: January 19, 2020

2015 conference paper

Data-driven worked examples improve retention and completion in a logic tutor

Artificial intelligence in education, aied 2015, 9112, 726–729.

Source: NC State University Libraries
Added: August 6, 2018

2015 chapter

Detecting Opinion Spammer Groups Through Community Discovery and Sentiment Analysis

In Data and Applications Security and Privacy XXIX (pp. 170–187).

By: E. Choo n, T. Yu & M. Chi

author keywords: Opinion spammer groups; Sentiment analysis; Community discovery
Source: Crossref
Added: February 24, 2020

2015 conference paper

Detecting opinion spammer groups through community discovery and sentiment analysis

Data and applications security and privacy xxix, 9149, 170–187.

By: E. Choo, T. Yu & M. Chi

Source: NC State University Libraries
Added: August 6, 2018

2014 chapter

Can Diagrams Predict Essay Grades?

In Intelligent Tutoring Systems (pp. 260–265).

By: C. Lynch, K. Ashley* & M. Chi

Source: Crossref
Added: August 28, 2020

2014 chapter

When Is Tutorial Dialogue More Effective Than Step-Based Tutoring?

In Intelligent Tutoring Systems (pp. 210–219).

By: M. Chi, P. Jordan* & K. VanLehn*

Source: Crossref
Added: August 28, 2020

2014 conference paper

When is tutorial dialogue more effective than step-based tutoring?

Intelligent tutoring systems, its 2014, 8474, 210–219.

By: M. Chi, P. Jordan & K. VanLehn

Source: NC State University Libraries
Added: August 6, 2018

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), 137–180.

By: M. Chi, K. VanLehn*, D. Litman* & P. Jordan*

author keywords: Reinforcement learning; Pedagogical strategy; Machine learning; Human learning
Source: Crossref
Added: August 28, 2020

2010 chapter

Do Micro-Level Tutorial Decisions Matter: Applying Reinforcement Learning to Induce Pedagogical Tutorial Tactics

In Intelligent Tutoring Systems (pp. 224–234).

By: M. Chi, K. VanLehn* & D. Litman*

Source: Crossref
Added: August 28, 2020

2010 chapter

Inducing Effective Pedagogical Strategies Using Learning Context Features

In User Modeling, Adaptation, and Personalization (pp. 147–158).

By: M. Chi, K. VanLehn*, D. Litman* & P. Jordan*

Source: Crossref
Added: August 28, 2020

2008 chapter

Eliminating the Gap between the High and Low Students through Meta-cognitive Strategy Instruction

In Intelligent Tutoring Systems (pp. 603–613).

By: M. Chi & K. VanLehn*

Source: Crossref
Added: August 28, 2020

2004 chapter

Implicit Versus Explicit Learning of Strategies in a Non-procedural Cognitive Skill

In Intelligent Tutoring Systems (pp. 521–530).

By: K. VanLehn*, D. Bhembe*, M. Chi, C. Lynch, K. Schulze*, R. Shelby*, L. Taylor*, D. Treacy*, A. Weinstein*, M. Wintersgill*

Source: Crossref
Added: August 28, 2020