Zhao, C., Fowler, M., Gertner, Y., Poulsen, S., West, M., & Silva, M. (2026). AI-Supported Grading and Rubric Refinement for Free Response Questions. Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.1, SIGCSE TS 2026, 1, 1207–1214. https://doi.org/10.1145/3770762.3772545
Zhao, C., Silva, M., Poulsen, S. (2025). Language Models are Few-Shot Graders. In: Cristea, A.I., Walker, E., Lu, Y., Santos, O.C., Isotani, S. (eds) Artificial Intelligence in Education. AIED 2025. Lecture Notes in Computer Science, vol 15880. Springer, Cham. https://doi.org/10.1007/978-3-031-98459-4_1
Zhao, C., Silva, M. & Poulsen, S. Autograding Mathematical Induction Proofs with Natural Language Processing. Int J Artif Intell Educ (2025). https://doi.org/10.1007/s40593-025-00498-2
Craig Zilles, Chenyan Zhao, Yuxuan Chen, Evan Michael Matthews, and Matthew West. 2024. A Case for Bayesian Grading. In Proceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 1 (SIGCSE Virtual 2024). Association for Computing Machinery, New York, NY, USA, 275–278. https://doi.org/10.1145/3649165.3703624
Shan Huang, JiWoo Lee, Chenyan Zhao, Geoffrey Herman, Marc Olano, Linda Oliva, Alan Sherman, "A User Experience Study of MeetingMayhem: A Web-Based Game to Teach Adversarial Thinking." In the proceedings of Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1, 2024.
Zhao, C., & West, M., & Silva, M. (2023, June), How Much Deadline Flexibility on Formative Assessments Should We Be Giving to Our Students? Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43372