Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 2 |
Descriptor
Author
| Cambronero, José | 1 |
| Gulwani, Sumit | 1 |
| Heiner, Cecily | 1 |
| Kohn, Tobias | 1 |
| Majumdarm, Rupak | 1 |
| Phung, Tung | 1 |
| Singla, Adish | 1 |
| Soares, Gustavo | 1 |
| Zachary, Joseph L. | 1 |
Publication Type
| Reports - Evaluative | 2 |
| Speeches/Meeting Papers | 2 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
| Utah | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textPhung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Heiner, Cecily; Zachary, Joseph L. – International Working Group on Educational Data Mining, 2009
Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…
Descriptors: Classification, Questioning Techniques, Introductory Courses, Computer Science Education
