Muntasir Hoq
College of Engineering
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Works (2)
Updated: April 20th, 2024 05:00
2024 article
Detecting ChatGPT-Generated Code Submissions in a CS1 Course Using Machine Learning Models
PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1, pp. 526–532.
author keywords: ChatGPT; large language model; artificial intelligence; introductory programming course; CS1; cheat detection; plagiarism detection
TL;DR:
This work evaluated the performance of both traditional machine learning models and Abstract Syntax Tree-based (AST-based) deep learning models in detecting ChatGPT code from student code submissions, and suggested that both traditional machine learning models and AST-based deep learning models are effective in identifying ChatGPT-generated code with accuracy above 90%.
(via Semantic Scholar)
dl.acm.org (publisher PDF)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: March 8, 2024
2023 article
SANN: Programming Code Representation Using Attention Neural Network with Optimized Subtree Extraction
PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023, pp. 783–792.
author keywords: program analysis; code representation; static analysis; algorithm detection; program correctness prediction
TL;DR:
The results indicate the effectiveness of the SANN model in capturing important syntactic and semantic information from students' code, allowing the construction of accurate student models, which serve as the foundation for generating adaptive instructional support such as individualized hints and feedback.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(OpenAlex)
Source: Web Of Science
Added: March 25, 2024
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