Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 3 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 3 |
Descriptor
Author
| Barnes, Tiffany | 1 |
| Boxuan Ma | 1 |
| Chi, Min | 1 |
| Kathryn Cunningham | 1 |
| Li Chen | 1 |
| Max Fowler | 1 |
| Mehmet Arif Demirta¸ | 1 |
| Price, Thomas W. | 1 |
| Shi, Yang | 1 |
| Shin’ichi Konomi | 1 |
Publication Type
| Reports - Research | 3 |
| Speeches/Meeting Papers | 3 |
Education Level
| Higher Education | 3 |
| Postsecondary Education | 3 |
Audience
Location
| Japan | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Mehmet Arif Demirta¸; Max Fowler; Kathryn Cunningham – International Educational Data Mining Society, 2024
Analyzing which skills students develop in introductory programming education is an important question for the computer science education community. These key skills and concepts have been formalized as knowledge components, which are units of knowledge that can be measured by performance on a set of tasks. While knowledge components in other…
Descriptors: Programming, Computer Science Education, Skill Development, Knowledge Level
Boxuan Ma; Li Chen; Shin’ichi Konomi – International Association for Development of the Information Society, 2024
Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and…
Descriptors: Artificial Intelligence, Computer Science Education, Programming, Computer Uses in Education
Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation

Peer reviewed
