Yang Shi

According to our database, Yang Shi authored at least 27 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Novices' Perceptions of Web-Search and AI for Programming.

James Skripchuk, John Bacher, Yang Shi, Keith Tran, Thomas W. Price

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Detecting ChatGPT-Generated Code Submissions in a CS1 Course Using Machine Learning Models.

Muntasir Hoq, Yang Shi, Juho Leinonen, Damilola Babalola, Collin F. Lynch, Thomas W. Price, Bita Akram

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Enhancing Code Tracing Question Generation with Refined Prompts in Large Language Models.

Aysa X. Fan, Rully Agus Hendrawan, Yang Shi, Qianou Ma

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Are Engineering Students Motivated by Interacting With Simulations They Program? A Controlled Study.

John Bacher, Thomas W. Price, James Skripchuk, Wengran Wang, Yang Shi, Keith Tran

Proceedings of the 2024 ACM Virtual Global Computing Education Conference V. 1, 2024

Overcoming Barriers in Scaling Computing Education Research Programming Tools: A Developer's Perspective.

Keith Tran, John Bacher, Yang Shi, James Skripchuk, Thomas W. Price

Proceedings of the 2024 ACM Conference on International Computing Education Research, 2024

An Approach to Detect Abnormal Submissions for CodeWorkout Dataset.

Alex Hicks, Yang Shi, Arun Balajiee Lekshmi Narayanan, Wei Yan, Samiha Marwan

Proceedings of 8th Educational Data Mining in Computer Science Education Workshop (CSEDM 2024) co-located with the 17th Educational Data Mining Conference (EDM 2024), 2024

Evaluating Multi-Knowledge Component Interpretability of Deep Knowledge Tracing Models in Programming.

Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price

Proceedings of the 17th International Conference on Educational Data Mining, 2024

8th Educational Data Mining in Computer Science Education (CSEDM) Workshop.

Yang Shi, Peter Brusilovsky, Bita Akram, Thomas W. Price, Juho Leinonen, Kenneth R. Koedinger, Andrew S. Lan

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming.

Zhengdong Zhang, Zihan Dong, Yang Shi, Thomas W. Price, Noboru Matsuda, Dongkuan Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Developing Comic-based Learning Toolkits for Teaching Computing to Elementary School Learners.

Francisco Castro, Sangho Suh, Jane L. E, Weena Naowaprateep, Yang Shi

Proceedings of the 54th ACM Technical Symposium on Computer Science Education, Volume 2, 2023

Investigating the Impact of On-Demand Code Examples on Novices' Open-Ended Programming Experience.

Wengran Wang, John Bacher, Amy Isvik, Ally Limke, Sandeep Sthapit, Yang Shi, Benyamin T. Tabarsi, Keith Tran, Veronica Cateté, Tiffany Barnes, Chris Martens, Thomas W. Price

Proceedings of the 2023 ACM Conference on International Computing Education Research, 2023

KC-Finder: Automated Knowledge Component Discovery for Programming Problems.

Yang Shi, Robin Schmucker, Min Chi, Tiffany Barnes, Thomas W. Price

Proceedings of the 16th International Conference on Educational Data Mining, 2023

Detecting ChatGPT-Generated Code in a CS1 Course.

Muntasir Hoq, Yang Shi, Juho Leinonen, Damilola Babalola, Collin F. Lynch, Bita Akram

Proceedings of the Workshop on Empowering Education with LLMs, 2023

2022

Identifying Common Errors in Open-Ended Machine Learning Projects.

James Skripchuk, Yang Shi, Thomas W. Price

Proceedings of the SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education, 2022

6th Educational Data Mining in Computer Science Education (CSEDM) Workshop.

Bita Akram, Thomas W. Price, Yang Shi, Peter Brusilovsky, Sharon I-Han Hsiao

Proceedings of the 15th International Conference on Educational Data Mining, 2022

Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks.

Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price

Proceedings of the 15th International Conference on Educational Data Mining, 2022

2021

Toward Semi-Automatic Misconception Discovery Using Code Embeddings.

Yang Shi, Krupal Shah, Wengran Wang, Samiha Marwan, Poorvaja Penmetsa, Thomas W. Price

Proceedings of the LAK'21: 11th International Learning Analytics and Knowledge Conference, 2021

Investigate Effectiveness of Code Features in Knowledge Tracing Task on Novice Programming Course. (Work in Progress).

Poorvaja Penmetsa, Yang Shi, Thomas W. Price

Proceedings of the Joint Proceedings of the Workshops at the International Conference on Educational Data Mining 2021 co-located with 14th International Conference on Educational Data Mining (EDM 2021), 2021

Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming.

Samiha Marwan, Yang Shi, Ian Menezes, Min Chi, Tiffany Barnes, Thomas W. Price

Proceedings of the 14th International Conference on Educational Data Mining, 2021

Knowing both when and where: Temporal-ASTNN for Early Prediction of Student Success in Novice Programming Tasks.

Ye Mao, Yang Shi, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi

Proceedings of the 14th International Conference on Educational Data Mining, 2021

More With Less: Exploring How to Use Deep Learning Effectively through Semi-supervised Learning for Automatic Bug Detection in Student Code.

Yang Shi, Ye Mao, Tiffany Barnes, Min Chi, Thomas W. Price

Proceedings of the 14th International Conference on Educational Data Mining, 2021

2020

Comparing Feature Engineering Approaches to Predict Complex Programming Behaviors.

Wengran Wang, Yudong Rao, Yang Shi, Alexandra Milliken, Chris Martens, Tiffany Barnes, Thomas W. Price

Proceedings of 4th Educational Data Mining in Computer Science Education (CSEDM) Workshop co-located with the 13th Educational Data Mining Conference (EDM 2020), 2020

2019

Enhanced Cyber-Physical Security in Internet of Things Through Energy Auditing.

Fangyu Li, Yang Shi, Aditya Shinde, Jin Ye, Wen-Zhan Song

IEEE Internet Things J., 2019

System Statistics Learning-Based IoT Security: Feasibility and Suitability.

Fangyu Li, Aditya Shinde, Yang Shi, Jin Ye, Xiang-Yang Li, Wen-Zhan Song

IEEE Internet Things J., 2019

Energy audition based cyber-physical attack detection system in IoT.

Yang Shi, Fangyu Li, Wen-Zhan Song, Xiangyang Li, Jin Ye

Proceedings of the ACM Turing Celebration Conference - China, 2019

2018

PoTrojan: powerful neural-level trojan designs in deep learning models.

Minhui Zou, Yang Shi, Chengliang Wang, Fangyu Li, Wen-Zhan Song, Yu Wang

CoRR, 2018

Dynamic Time-frequency Feature Extraction for Brain Activity Recognition.

Yang Shi, Fangyu Li, Tianming Liu, Fred R. Beyette, Wen-Zhan Song

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018