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Min Chi
Publications
- 2023
- [j14]Markel Sanz Ausin, Mehak Maniktala, Tiffany Barnes, Min Chi:
The Impact of Batch Deep Reinforcement Learning on Student Performance: A Simple Act of Explanation Can Go A Long Way. Int. J. Artif. Intell. Educ. 33(4): 1031-1056 (2023) - [j10]Mehak Maniktala, Min Chi, Tiffany Barnes:
Enhancing a student productivity model for adaptive problem-solving assistance. User Model. User Adapt. Interact. 33(1): 159-188 (2023) - [c110]Nazia Alam, Mehak Maniktala, Behrooz Mostafavi, Min Chi, Tiffany Barnes:
Does Knowing When Help Is Needed Improve Subgoal Hint Performance in an Intelligent Data-Driven Logic Tutor? AAAI 2023: 15895-15902 - [c109]Nazia Alam, Behrooz Mostafavi, Min Chi, Tiffany Barnes:
Exploring the Effect of Autoencoder Based Feature Learning for a Deep Reinforcement Learning Policy for Providing Proactive Help. AIED (Posters/Late Breaking Results/...) 2023: 278-283 - [c108]Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi:
Leveraging Deep Reinforcement Learning for Metacognitive Interventions Across Intelligent Tutoring Systems. AIED 2023: 291-303 - [c107]Preya Shabrina, Behrooz Mostafavi, Min Chi, Tiffany Barnes:
Impact of Learning a Subgoal-Directed Problem-Solving Strategy Within an Intelligent Logic Tutor. AIED 2023: 389-400 - [c106]Markel Sanz Ausin, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
A Unified Batch Hierarchical Reinforcement Learning Framework for Pedagogical Policy Induction with Deep Bisimulation Metrics. AIED (Posters/Late Breaking Results/...) 2023: 599-605 - [c105]John Wesley Hostetter, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
A Self-Organizing Neuro-Fuzzy Q-Network: Systematic Design with Offline Hybrid Learning. AAMAS 2023: 1248-1257 - [c103]Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi:
Bridging Declarative, Procedural, and Conditional Metacognitive Knowledge Gap Using Deep Reinforcement Learning. CogSci 2023 - [c102]Yang Shi, Robin Schmucker, Min Chi, Tiffany Barnes, Thomas W. Price:
KC-Finder: Automated Knowledge Component Discovery for Programming Problems. EDM 2023 - [c101]Preya Shabrina, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi, Tiffany Barnes:
Learning Problem Decomposition-Recomposition with Data-driven Chunky Parsons Problems within an Intelligent Logic Tutor. EDM 2023 - [c100]John Wesley Hostetter, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
Leveraging Fuzzy Logic Towards More Explainable Reinforcement Learning-Induced Pedagogical Policies on Intelligent Tutoring Systems. FUZZ 2023: 1-7 - [c95]John Wesley Hostetter, Cristina Conati, Xi Yang, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
XAI to Increase the Effectiveness of an Intelligent Pedagogical Agent. IVA 2023: 28:1-28:9 - [i22]Mark Abdelshiheed, Mehak Maniktala, Song Ju, Ayush Jain, Tiffany Barnes, Min Chi:
Preparing Unprepared Students For Future Learning. CoRR abs/2303.11960 (2023) - [i21]Mark Abdelshiheed, John Wesley Hostetter, Preya Shabrina, Tiffany Barnes, Min Chi:
The Power of Nudging: Exploring Three Interventions for Metacognitive Skills Instruction across Intelligent Tutoring Systems. CoRR abs/2303.11965 (2023) - [i20]Mark Abdelshiheed, John Wesley Hostetter, Xi Yang, Tiffany Barnes, Min Chi:
Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer. CoRR abs/2303.12223 (2023) - [i19]Mark Abdelshiheed, Guojing Zhou, Mehak Maniktala, Tiffany Barnes, Min Chi:
Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. CoRR abs/2303.13541 (2023) - [i18]Mark Abdelshiheed, Mehak Maniktala, Tiffany Barnes, Min Chi:
Assessing Competency Using Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. CoRR abs/2303.14609 (2023) - [i17]Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi:
Leveraging Deep Reinforcement Learning for Metacognitive Interventions across Intelligent Tutoring Systems. CoRR abs/2304.09821 (2023) - [i16]Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi:
Bridging Declarative, Procedural, and Conditional Metacognitive Knowledge Gap Using Deep Reinforcement Learning. CoRR abs/2304.11739 (2023) - 2022
- [j9]Christa Cody, Mehak Maniktala, Nicholas Lytle, Min Chi, Tiffany Barnes:
The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor. Int. J. Artif. Intell. Educ. 32(2): 263-296 (2022) - [j8]Guojing Zhou, Hamoon Azizsoltani, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
Leveraging Granularity: Hierarchical Reinforcement Learning for Pedagogical Policy Induction. Int. J. Artif. Intell. Educ. 32(2): 454-500 (2022) - [c93]Ye Mao, Farzaneh Khoshnevisan, Thomas W. Price, Tiffany Barnes, Min Chi:
Cross-Lingual Adversarial Domain Adaptation for Novice Programming. AAAI 2022: 7682-7690 - [c92]Song Ju, Xi Yang, Tiffany Barnes, Min Chi:
Student-Tutor Mixed-Initiative Decision-Making Supported by Deep Reinforcement Learning. AIED (1) 2022: 440-452 - [c91]Mark Abdelshiheed, John Wesley Hostetter, Xi Yang, Tiffany Barnes, Min Chi:
Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer. AIED (1) 2022: 546-552 - [c90]Mark Abdelshiheed, John Wesley Hostetter, Preya Shabrina, Tiffany Barnes, Min Chi:
The Power of Nudging: Exploring Three Interventions for Metacognitive Skills Instruction across Intelligent Tutoring Systems. CogSci 2022 - [c89]Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks. EDM 2022 - [i11]Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks. CoRR abs/2206.03545 (2022) - [i10]Mehak Maniktala, Min Chi, Tiffany Barnes:
Enhancing a Student Productivity Model for Adaptive Problem-Solving Assistance. CoRR abs/2207.03025 (2022) - [i9]Preya Shabrina, Behrooz Mostafavi, Mark Abdelshiheed, Min Chi, Tiffany Barnes:
Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning towards Improved Problem Solving. CoRR abs/2208.04696 (2022) - [i8]Preya Shabrina, Samiha Marwan, Andrew Bennison, Min Chi, Thomas W. Price, Tiffany Barnes:
A Multicriteria Evaluation for Data-Driven Programming Feedback Systems: Accuracy, Effectiveness, Fallibility, and Students' Response. CoRR abs/2208.05326 (2022) - 2021
- [j7]Mehak Maniktala, Christa Cody, Tiffany Barnes, Min Chi:
Correction to: Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. Int. J. Artif. Intell. Educ. 31(1): 154-155 (2021) - [c86]Song Ju, Guojing Zhou, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
Evaluating Critical Reinforcement Learning Framework in the Field. AIED (1) 2021: 215-227 - [c85]Markel Sanz Ausin, Mehak Maniktala, Tiffany Barnes, Min Chi:
Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks. AIED (1) 2021: 356-368 - [c81]Mark Abdelshiheed, Mehak Maniktala, Song Ju, Ayush Jain, Tiffany Barnes, Min Chi:
Preparing Unprepared Students For Future Learning. CogSci 2021 - [c80]Yang Shi, Ye Mao, Tiffany Barnes, Min Chi, Thomas W. Price:
More With Less: Exploring How to Use Deep Learning Effectively through Semi-supervised Learning for Automatic Bug Detection in Student Code. EDM 2021 - [c79]Ye Mao, Yang Shi, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi:
Knowing both when and where: Temporal-ASTNN for Early Prediction of Student Success in Novice Programming Tasks. EDM 2021 - [c78]Samiha Marwan, Yang Shi, Ian Menezes, Min Chi, Tiffany Barnes, Thomas W. Price:
Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming. EDM 2021 - [i6]Christa Cody, Mehak Maniktala, Nicholas Lytle, Min Chi, Tiffany Barnes:
The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor. CoRR abs/2102.05741 (2021) - 2020
- [j6]Mehak Maniktala, Christa Cody, Tiffany Barnes, Min Chi:
Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. Int. J. Artif. Intell. Educ. 30(4): 637-667 (2020) - [c73]Markel Sanz Ausin, Mehak Maniktala, Tiffany Barnes, Min Chi:
Exploring the Impact of Simple Explanations and Agency on Batch Deep Reinforcement Learning Induced Pedagogical Policies. AIED (1) 2020: 472-485 - [c69]Christa Cody, Mehak Maniktala, David Warren, Min Chi, Tiffany Barnes:
Does autonomy help Help? The impact of unsolicited hints and choice on help avoidance and learning. EDM 2020 - [c67]Mehak Maniktala, Tiffany Barnes, Min Chi:
Extending the Hint Factory: Towards Modelling Productivity for Open-ended Problem-solving. EDM 2020 - [c66]Ye Mao, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi:
What Time is It? Student Modeling Needs to Know. EDM 2020 - [c65]Samiha Marwan, Thomas W. Price, Min Chi, Tiffany Barnes:
Immediate Data-Driven Positive Feedback Increases Engagement on Programming Homework for Novices. CSEDM@EDM 2020 - [c64]Preya Shabrina, Samiha Marwan, Min Chi, Thomas W. Price, Tiffany Barnes:
The Impact of Data-driven Positive Programming Feedback: When it Helps, What Happens when it Goes Wrong, and How Students Respond. CSEDM@EDM 2020 - [c62]Guojing Zhou, Hamoon Azizsoltani, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract). IJCAI 2020: 4691-4695 - [c60]Guojing Zhou, Xi Yang, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Improving Student-System Interaction Through Data-driven Explanations of Hierarchical Reinforcement Learning Induced Pedagogical Policies. UMAP 2020: 284-292 - [i3]Mehak Maniktala, Christa Cody, Tiffany Barnes, Min Chi:
Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. CoRR abs/2009.13371 (2020) - [i2]Mehak Maniktala, Christa Cody, Amy Isvik, Nicholas Lytle, Min Chi, Tiffany Barnes:
Extending the Hint Factory for the assistance dilemma: A novel, data-driven HelpNeed Predictor for proactive problem-solving help. CoRR abs/2010.04124 (2020) - 2019
- [c59]Guojing Zhou, Hamoon Azizsoltani, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
Hierarchical Reinforcement Learning for Pedagogical Policy Induction. AIED (1) 2019: 544-556 - [c54]Markel Sanz Ausin, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Leveraging Deep Reinforcement Learning for Pedagogical Policy Induction in an Intelligent Tutoring System. EDM 2019 - [c53]Song Ju, Shitian Shen, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Importance Sampling to Identify Empirically Valid Policies and their Critical Decisions. EDM (Workshops) 2019: 69-78 - [c52]Song Ju, Guojing Zhou, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Identifying Critical Pedagogical Decisions through Adversarial Deep Reinforcement Learning. EDM 2019 - [c51]Ye Mao, Rui Zhi, Farzaneh Khoshnevisan, Thomas W. Price, Tiffany Barnes, Min Chi:
One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks. EDM 2019 - [c50]Rui Zhi, Min Chi, Tiffany Barnes, Thomas W. Price:
Evaluating the Effectiveness of Parsons Problems for Block-based Programming. ICER 2019: 51-59 - [c47]Hamoon Azizsoltani, Yeo-Jin Kim, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
Unobserved Is Not Equal to Non-existent: Using Gaussian Processes to Infer Immediate Rewards Across Contexts. IJCAI 2019: 1974-1980 - [c44]Rui Zhi, Thomas W. Price, Samiha Marwan, Alexandra Milliken, Tiffany Barnes, Min Chi:
Exploring the Impact of Worked Examples in a Novice Programming Environment. SIGCSE 2019: 98-104 - 2018
- [c43]Shitian Shen, Behrooz Mostafavi, Collin F. Lynch, Tiffany Barnes, Min Chi:
Empirically Evaluating the Effectiveness of POMDP vs. MDP Towards the Pedagogical Strategies Induction. AIED (2) 2018: 327-331 - 2016
- [c30]Guojing Zhou, Collin F. Lynch, Thomas W. Price, Tiffany Barnes, Min Chi:
The Impact of Granularity on the Effectiveness of Students' Pedagogical Decisions. CogSci 2016 - [e2]Tiffany Barnes, Min Chi, Mingyu Feng:
Proceedings of the 9th International Conference on Educational Data Mining, EDM 2016, Raleigh, North Carolina, USA, June 29 - July 2, 2016. International Educational Data Mining Society (IEDMS) 2016 [contents] - 2015
- [c22]Behrooz Mostafavi, Guojing Zhou, Collin F. Lynch, Min Chi, Tiffany Barnes:
Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor. AIED 2015: 726-729 - [c21]Guojing Zhou, Thomas W. Price, Collin F. Lynch, Tiffany Barnes, Min Chi:
The Impact of Granularity on Worked Examples and Problem Solving. CogSci 2015 - [c19]Collin F. Lynch, Thomas W. Price, Min Chi, Tiffany Barnes:
Using the Hint Factory to Compare Model-Based Tutoring Systems. EDM (Workshops) 2015 - [c18]Thomas W. Price, Collin F. Lynch, Tiffany Barnes, Min Chi:
An Improved Data-Driven Hint Selection Algorithm for Probability Tutors. EDM 2015: 610-611
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