Portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 2
This project enables instructors, irrespective of their familiarity with LLM technology, to utilize the ASAG system for grading free-form textual short answers.
In this project, we propose a comprehensive redesign of CS 101,focusing on re-establishing basic programming fundamentals (CS1) during lectures while integrating diverse engineering applications into lab sections and bi-weekly mini-projects.
Following a Universal Design for Learning approach, we build a web-based calculator inside PrairieLearn that has similar functions to the real TI calculators with a more user-friendly interface. This would allow students to access the same calculator interface both inside and outside the testing environment to gain the necessary familiarity.
Published in 2023 ASEE Annual Conference & Exposition, 2023
Recommended citation: 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
Download Paper
Published in International Journal of Artificial Intelligence in Education (in submission), 2024
Recommended citation: Zhao, C., Silva, M., & Poulsen, S. (2024). Autograding Mathematical Induction Proofs with Natural Language Processing (arXiv:2406.10268). arXiv. https://doi.org/10.48550/arXiv.2406.10268
Download Paper
Published in Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1, 2024
Recommended citation: 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.
Download Paper
Published in SIGCSE Virtual 2024: Proceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 1, 2024
Recommended citation: 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
Download Paper
Published in 2025 ASEE Annual Conference & Exposition, 2025
Recommended citation:
Download Paper
Published in 2025 ASEE Annual Conference & Exposition, 2025
Recommended citation:
Download Paper
Published in 26th International Conference on Artificial Intelligence in Education, 2025
Recommended citation:
Download Paper
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Undergraduate course, University of Illinois Urbana-Champaign, Computer Science, 2021
My first experience of teaching, and also the start of the Computing Education Research path.
Graduate course, University of Illinois Urbana-Champaign, Computer Science, 2023
Improving the autograder so it can provide better feedback on student code.
Summer camp, University of Illinois Urbana-Champaign, Computer Science, 2023
I taught some simple machine learning to high school students in an Internet of Things summer camp.
Undergraduate course, University of Illinois Urbana-Champaign, Computer Science, 2023
I retired as a CA and returned as a TA, taking on even more important duties in the class.