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Yang Shi 0004
Person information
- affiliation: North Carolina State University, NC, USA
- affiliation (former): University of Georgia, Athens, GA, USA
Other persons with the same name
- Yang Shi — disambiguation page
- Yang Shi 0001 — University of Victoria, Department of Mechanical Engineering, BC, Canada (and 2 more)
- Yang Shi 0002 — Tongji University, School of Software Engineering, Shanghai, China (and 2 more)
- Yang Shi 0003 — Sun Yat-sen University, School of Information Science and Technology, Guangzhou, China
- Yang Shi 0005 — University of California, Irvine, CA, USA
- Yang Shi 0006 — Ocean University of China, Qingdao, China
- Yang Shi 0007 — Tongji University, College of Design and Innovation, Shanghai, China (and 1 more)
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2020 – today
- 2024
- [c24]Zhengdong Zhang, Zihan Dong, Yang Shi, Thomas W. Price, Noboru Matsuda, Dongkuan Xu:
Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming. AAAI 2024: 23250-23258 - [c23]Yang Shi, Peter Brusilovsky, Bita Akram, Thomas W. Price, Juho Leinonen, Kenneth R. Koedinger, Andrew S. Lan:
8th Educational Data Mining in Computer Science Education (CSEDM) Workshop. EDM 2024 - [c22]Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Evaluating Multi-Knowledge Component Interpretability of Deep Knowledge Tracing Models in Programming. EDM 2024 - [c21]Alex Hicks, Yang Shi, Arun Balajiee Lekshmi Narayanan, Wei Yan, Samiha Marwan:
An Approach to Detect Abnormal Submissions for CodeWorkout Dataset. CSEDM@EDM 2024 - [c20]Keith Tran, John Bacher, Yang Shi, James Skripchuk, Thomas W. Price:
Overcoming Barriers in Scaling Computing Education Research Programming Tools: A Developer's Perspective. ICER (1) 2024: 312-325 - [c19]John Bacher, Thomas W. Price, James Skripchuk, Wengran Wang, Yang Shi, Keith Tran:
Are Engineering Students Motivated by Interacting With Simulations They Program? A Controlled Study. SIGCSE Virtual (1) 2024 - [c18]Muntasir Hoq, Yang Shi, Juho Leinonen, Damilola Babalola, Collin F. Lynch, Thomas W. Price, Bita Akram:
Detecting ChatGPT-Generated Code Submissions in a CS1 Course Using Machine Learning Models. SIGCSE (1) 2024: 526-532 - [c17]Aysa X. Fan, Rully Agus Hendrawan, Yang Shi, Qianou Ma:
Enhancing Code Tracing Question Generation with Refined Prompts in Large Language Models. SIGCSE (2) 2024: 1640-1641 - [c16]James Skripchuk, John Bacher, Yang Shi, Keith Tran, Thomas W. Price:
Novices' Perceptions of Web-Search and AI for Programming. SIGCSE (2) 2024: 1818-1819 - [e2]Yang Shi, Peter Brusilovsky, Bita Akram, Thomas W. Price, Juho Leinonen, Ken Koedinger, Andrew S. Lan:
Proceedings of 8th Educational Data Mining in Computer Science Education Workshop (CSEDM 2024) co-located with the 17th Educational Data Mining Conference (EDM 2024), Atlanta, GA, USA, July 14, 2024. CEUR Workshop Proceedings 3796, CEUR-WS.org 2024 [contents] - [i5]Alex Hicks, Yang Shi, Arun Balajiee Lekshmi Narayanan, Wei Yan, Samiha Marwan:
An Approach to Detect Abnormal Submissions for CodeWorkout Dataset. CoRR abs/2407.17475 (2024) - 2023
- [c15]Muntasir Hoq, Yang Shi, Juho Leinonen, Damilola Babalola, Collin F. Lynch, Bita Akram:
Detecting ChatGPT-Generated Code in a CS1 Course. LLM@AIED 2023: 53-63 - [c14]Yang Shi, Robin Schmucker, Min Chi, Tiffany Barnes, Thomas W. Price:
KC-Finder: Automated Knowledge Component Discovery for Programming Problems. EDM 2023 - [c13]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:
Investigating the Impact of On-Demand Code Examples on Novices' Open-Ended Programming Experience. ICER (1) 2023: 464-475 - [c12]Francisco Castro, Sangho Suh, Jane L. E, Weena Naowaprateep, Yang Shi:
Developing Comic-based Learning Toolkits for Teaching Computing to Elementary School Learners. SIGCSE (2) 2023: 1325 - [i4]Zhengdong Zhang, Zihan Dong, Yang Shi, Noboru Matsuda, Thomas W. Price, Dongkuan Xu:
Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming. CoRR abs/2312.11567 (2023) - 2022
- [c11]Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks. EDM 2022 - [c10]Bita Akram, Thomas W. Price, Yang Shi, Peter Brusilovsky, Sharon I-Han Hsiao:
6th Educational Data Mining in Computer Science Education (CSEDM) Workshop. EDM 2022 - [c9]James Skripchuk, Yang Shi, Thomas W. Price:
Identifying Common Errors in Open-Ended Machine Learning Projects. SIGCSE (1) 2022: 216-222 - [i3]Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks. CoRR abs/2206.03545 (2022) - 2021
- [c8]Yang Shi, Ye Mao, Tiffany Barnes, Min Chi, Thomas W. Price:
More With Less: Exploring How to Use Deep Learning Effectively through Semi-supervised Learning for Automatic Bug Detection in Student Code. EDM 2021 - [c7]Ye Mao, Yang Shi, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi:
Knowing both when and where: Temporal-ASTNN for Early Prediction of Student Success in Novice Programming Tasks. EDM 2021 - [c6]Samiha Marwan, Yang Shi, Ian Menezes, Min Chi, Tiffany Barnes, Thomas W. Price:
Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming. EDM 2021 - [c5]Poorvaja Penmetsa, Yang Shi, Thomas W. Price:
Investigate Effectiveness of Code Features in Knowledge Tracing Task on Novice Programming Course. (Work in Progress). EDM (Workshops) 2021 - [c4]Yang Shi, Krupal Shah, Wengran Wang, Samiha Marwan, Poorvaja Penmetsa, Thomas W. Price:
Toward Semi-Automatic Misconception Discovery Using Code Embeddings. LAK 2021: 606-612 - [i2]Yang Shi, Krupal Shah, Wengran Wang, Samiha Marwan, Poorvaja Penmetsa, Thomas W. Price:
Toward Semi-Automatic Misconception Discovery Using Code Embeddings. CoRR abs/2103.04448 (2021) - 2020
- [c3]Wengran Wang, Yudong Rao, Yang Shi, Alexandra Milliken, Chris Martens, Tiffany Barnes, Thomas W. Price:
Comparing Feature Engineering Approaches to Predict Complex Programming Behaviors. CSEDM@EDM 2020 - [e1]Thomas W. Price, Peter Brusilovsky, Sharon I-Han Hsiao, Ken Koedinger, Yang Shi:
Proceedings of 4th Educational Data Mining in Computer Science Education (CSEDM) Workshop co-located with the 13th Educational Data Mining Conference (EDM 2020), Virtual Event, July 10, 2020. CEUR Workshop Proceedings 2734, CEUR-WS.org 2020 [contents]
2010 – 2019
- 2019
- [j2]Fangyu Li, Yang Shi, Aditya Shinde, Jin Ye, Wen-Zhan Song:
Enhanced Cyber-Physical Security in Internet of Things Through Energy Auditing. IEEE Internet Things J. 6(3): 5224-5231 (2019) - [j1]Fangyu Li, Aditya Shinde, Yang Shi, Jin Ye, Xiang-Yang Li, Wen-Zhan Song:
System Statistics Learning-Based IoT Security: Feasibility and Suitability. IEEE Internet Things J. 6(4): 6396-6403 (2019) - [c2]Yang Shi, Fangyu Li, Wen-Zhan Song, Xiangyang Li, Jin Ye:
Energy audition based cyber-physical attack detection system in IoT. ACM TUR-C 2019: 27:1-27:5 - 2018
- [c1]Yang Shi, Fangyu Li, Tianming Liu, Fred R. Beyette, Wen-Zhan Song:
Dynamic Time-frequency Feature Extraction for Brain Activity Recognition. EMBC 2018: 3104-3107 - [i1]Minhui Zou, Yang Shi, Chengliang Wang, Fangyu Li, Wen-Zhan Song, Yu Wang:
PoTrojan: powerful neural-level trojan designs in deep learning models. CoRR abs/1802.03043 (2018)
Coauthor Index
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last updated on 2025-01-13 02:04 CET by the dblp team
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