| 2026 | ACL | MalruleLib: Large-Scale Executable Misconception Reasoning with Step Traces for Modeling Student Thinking in Mathematics. | Xinghe Chen, Naiming Liu, Shashank Sonkar |
| 2026 | AIED | When Can We Trust LLM Graders? Calibrating Confidence for Automated Assessment. | Robinson Ferrer, Damla Turgut, Zhongzhou Chen, Shashank Sonkar |
| 2026 | AIED | Circuit Complexity of Hierarchical Knowledge Tracing. | Naiming Liu, Richard G. Baraniuk, Shashank Sonkar |
| 2026 | AIED | Misconception Acquisition Dynamics in Large Language Models. | Naiming Liu, Xinghe Chen, Richard G. Baraniuk, Mrinmaya Sachan, Shashank Sonkar |
| 2026 | AIED | FoundationalASSIST: Dataset for Foundational Knowledge Tracing & Pedagogical Grounding of Large Language Models. | Eamon Worden, Cristina Heffernan, Neil T. Heffernan, Shashank Sonkar |
| 2026 | EACL | CLEAR-3K: Assessing Causal Explanatory Capabilities in Language Models. | Naiming Liu, Richard G. Baraniuk, Shashank Sonkar |
| 2025 | AIED | Do LLMs Make Mistakes Like Students? Exploring Natural Alignments Between Language Models and Human Error Patterns. | Naiming Liu, Shashank Sonkar, Richard G. Baraniuk |
| 2025 | AIED | Many-Shot Regurgitation Prompting. | Shashank Sonkar, Naiming Liu, Richard G. Baraniuk |
| 2025 | AIED | Turing-Like Test for Personalized Educational AI. | Shashank Sonkar, Naiming Liu, Xinghe Chen, Richard G. Baraniuk |
| 2025 | LAK | Atomic Learning Objectives and LLMs Labeling: A High-Resolution Approach for Physics Education. | Naiming Liu, Shashank Sonkar, Debshila Basu Mallick, Richard G. Baraniuk, Zhongzhou Chen |
| 2024 | AIED | Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. | Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk |
| 2024 | AIED | Automated Long Answer Grading with RiceChem Dataset. | Shashank Sonkar, Kangqi Ni, Lesa Tran Lu, Kristi Kincaid, John S. Hutchinson, Richard G. Baraniuk |
| 2024 | EDM | Leveraging Large Language Models for Next-Generation Educational Technologies. | Neil T. Heffernan, Rose E. Wang, Christopher MacLellan, Arto Hellas, Chenglu Li, Candace A. Walkington, Joshua Littenberg-Tobias, David Joyner, Steven Moore, Adish Singla, Zach A. Pardos, Maciej Pankiewicz, Juho Kim, Shashank Sonkar, Clayton Cohn, Anthony Botelho, Andrew S. Lan, Lan Jiang, Mingyu Feng, Tanja Kser, Eamon Worden |
| 2024 | EMNLP | Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning. | Shashank Sonkar, Naiming Liu, Richard G. Baraniuk |
| 2024 | EMNLP | MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education. | Shashank Sonkar, Naiming Liu, Myco Le, Richard G. Baraniuk |
| 2024 | EMNLP | Pedagogical Alignment of Large Language Models. | Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, Richard G. Baraniuk |
| 2024 | LAK | Code Soliloquies for Accurate Calculations in Large Language Models. | Shashank Sonkar, Xinghe Chen, Myco Le, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk |
| 2023 | AIED | Deduction under Perturbed Evidence: Probing Student Simulation (Knowledge Tracing) Capabilities of Large Language Models. | Shashank Sonkar, Richard G. Baraniuk |
| 2023 | EMNLP | CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles. | Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk |
| 2020 | COLING | Attention Word Embedding. | Shashank Sonkar, Andrew E. Waters, Richard G. Baraniuk |
| 2020 | EDM | qDKT: Question-centric Deep Knowledge Tracing. | Shashank Sonkar, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk |