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)

Local energy-based framework for feature ranking. - Wei Ji; Yun Li 009; Kejia Chen 001; Guojing Zhou (J. Intell. Fuzzy Syst., 2015)

FREL: A Stable Feature Selection Algorithm. - Yun Li 009; Jennie Si; Guojing Zhou; Shasha Huang; Songcan Chen (IEEE Trans. Neural Networks Learn. Syst., 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)

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

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

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

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

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)

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

Going Deep and Far: Gaze-based Models Predict Multiple Depths of Comprehension During and One Week Following Reading. - Megan Caruso; Candace E. Peacock; Rosy Southwell; Guojing Zhou; Sidney D'Mello (EDM, 2022)

Investigating Temporal Dynamics Underlying Successful Collaborative Problem Solving Behaviors with Multilevel Vector Autoregression. - Guojing Zhou; Robert Moulder; Chen Sun 011; Sidney D'Mello (EDM, 2022)

What do Students' Interactions with Online Lecture Videos Reveal about their Learning? - Guojing Zhou; Tetsumichi Umada; Sidney D'Mello (UMAP, 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)

The relationship between collaborative problem solving behaviors and solution outcomes in a game-based learning environment. - Chen Sun 011; Valerie J. Shute; Angela E. B. Stewart; Quinton Beck-White; Caroline Reinhardt; Guojing Zhou; Nicholas D. Duran; Sidney K. D'Mello (Comput. Hum. Behav., 2022)

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)