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
| Coding | 2 |
| Identification | 2 |
| Program Effectiveness | 2 |
| Age Differences | 1 |
| Alzheimers Disease | 1 |
| Artificial Intelligence | 1 |
| Brain | 1 |
| Computer Science Education | 1 |
| Computer Simulation | 1 |
| Diseases | 1 |
| Error Correction | 1 |
| More ▼ | |
Author
| Barnes, Tiffany | 1 |
| Chi, Min | 1 |
| Gyselinck, V. | 1 |
| Mao, Ye | 1 |
| Nicolas, S. | 1 |
| Piolino, P. | 1 |
| Plancher, G. | 1 |
| Price, Thomas W. | 1 |
| Shi, Yang | 1 |
| Tirard, A. | 1 |
Publication Type
| Reports - Research | 2 |
| Journal Articles | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Adult Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textShi, Yang; Mao, Ye; Barnes, Tiffany; Chi, Min; Price, Thomas W. – International Educational Data Mining Society, 2021
Automatically detecting bugs in student program code is critical to enable formative feedback to help students pinpoint errors and resolve them. Deep learning models especially code2vec and ASTNN have shown great success for "large-scale" code classification. It is not clear, however, whether they can be effectively used for bug…
Descriptors: Artificial Intelligence, Program Effectiveness, Coding, Computer Science Education
Direct linkPlancher, G.; Tirard, A.; Gyselinck, V.; Nicolas, S.; Piolino, P. – Neuropsychologia, 2012
Most neuropsychological assessments of episodic memory bear little similarity to the events that patients actually experience as memories in daily life. The first aim of this study was to use a virtual environment to characterize episodic memory profiles in an ecological fashion, which includes memory for central and perceptual details,…
Descriptors: Computer Simulation, Alzheimers Disease, Diseases, Identification
