| 2026 | LAK | Enhancing LLM-Based Data Annotation with Error Decomposition. | Zhen Xu, Vedant Khatri, Yijun Dai, Xiner Liu, Siyan Li, Xuanming Zhang, Renzhe Yu |
| 2025 | AIED | Evaluating an AI Tutor for Bias Across Different Foundation Models. | Aditya Vinodh, Emma Harvey, Husni Almoubayyed, Renzhe Yu, Christopher Brooks, Allison Koenecke, Ren F. Kizilcec |
| 2025 | AIED | From Course to Skill: Evaluating Large Language Model Performance in Curricular Analytics. | Zhen Xu, Xinjin Li, Yingqi Huan, Veronica Minaya, Renzhe Yu |
| 2025 | AIES | When the Past Misleads: Rethinking Training Data Expansion Under Temporal Distribution Shifts. | Chengyuan Yao, Yunxuan Tang, Christopher Brooks, Ren F. Kizilcec, Renzhe Yu |
| 2025 | EDM | Understanding Predictive Models of Student Success with a Multiverse Analysis. | Yunxuan Tang, Emma Harvey, Chengyuan Yao, Renzhe Yu, Ren F. Kizilcec, Christopher Brooks |
| 2025 | EMNLP | Bringing Pedagogy into Focus: Evaluating Virtual Teaching Assistants' Question-Answering in Asynchronous Learning Environments. | Li Siyan, Zhen Xu, Vethavikashini Chithrra Raghuram, Xuanming Zhang, Renzhe Yu, Zhou Yu |
| 2025 | Interspeech | Predicting Adolescent Suicidal Risk from Multi-task-based Speech: An Ensemble Learning Approach. | Xi Chen, Renzhe Yu, Yanshen Tan, Yiyi Li, Quan Qian, Ying Lin |
| 2025 | LAK | Towards Fair and Privacy-Aware Transfer Learning for Educational Predictive Modeling: A Case Study on Retention Prediction in Community Colleges. | Chengyuan Yao, Carmen Cortez, Renzhe Yu |
| 2024 | LAK | Temporal and Between-Group Variability in College Dropout Prediction. | Dominik Glandorf, Hye Rin Lee, Gabe Avakian Orona, Marina Pumptow, Renzhe Yu, Christian Fischer |
| 2024 | LAK | Contexts Matter but How? Course-Level Correlates of Performance and Fairness Shift in Predictive Model Transfer. | Zhen Xu, Joseph Olson, Nicole Pochinki, Zhijian Zheng, Renzhe Yu |
| 2023 | EDM | Semantic Topic Chains for Modeling Temporality of Themes in Online Student Discussion Forums. | Harshita Chopra, Yiwen Lin, Mohammad Amin Samadi, Jacqueline G. Cavazos, Renzhe Yu, Spencer Jaquay, Nia Nixon |
| 2022 | AIED | Modeling Student Discourse in Online Discussion Forums Using Semantic Similarity Based Topic Chains. | Harshita Chopra, Yiwen Lin, Mohammad Amin Samadi, Jacqueline Guadalupe Cavazos, Renzhe Yu, Spencer Jaquay, Nia Nixon |
| 2022 | EDM | FATED 2022: Fairness, Accountability, and Transparency in Educational Data. | Collin F. Lynch, Mirko Marras, Mykola Pechenizkiy, Anna N. Rafferty, Steven Ritter, Vinitra Swamy, Renzhe Yu |
| 2020 | AIED | LIWCs the Same, Not the Same: Gendered Linguistic Signals of Performance and Experience in Online STEM Courses. | Yiwen Lin, Renzhe Yu, Nia Dowell |
| 2020 | EDM | Towards Accurate and Fair Prediction of College Success: Evaluating Different Sources of Student Data. | Renzhe Yu, Qiujie Li, Christian Fischer, Shayan Doroudi, Di Xu |
| 2019 | EDM | Student Behavioral Embeddings and Their Relationship to Outcomes in a Collaborative Online Course. | Renzhe Yu, Zachary A. Pardos, John Scott |
| 2019 | LAK | Utilizing Learning Analytics to Map Students' Self-Reported Study Strategies to Click Behaviors in STEM Courses. | Fernando Rodriguez, Renzhe Yu, Jihyun Park, Mariela Janet Rivas, Mark Warschauer, Brian K. Sato |
| 2018 | EDM | Understanding Student Procrastination via Mixture Models. | Jihyun Park, Renzhe Yu, Fernando Rodriguez, Rachel B. Baker, Padhraic Smyth, Mark Warschauer |