Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Accuracy | 1 |
| Computer Science Education | 1 |
| Difficulty Level | 1 |
| Evaluation Methods | 1 |
| Feedback (Response) | 1 |
| Item Response Theory | 1 |
| Models | 1 |
| Novices | 1 |
| Programming | 1 |
| Programming Languages | 1 |
| Validity | 1 |
| More ▼ | |
Source
| Computer Science Education | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkChristina Glasauer; Martin K. Yeh; Lois Anne DeLong; Yu Yan; Yanyan Zhuang – Computer Science Education, 2025
Background and Context: Feedback on one's progress is essential to new programming language learners, particularly in out-of-classroom settings. Though many study materials offer assessment mechanisms, most do not examine the accuracy of the feedback they deliver, nor give evidence on its validity. Objective: We investigate the potential use of a…
Descriptors: Novices, Computer Science Education, Programming, Accuracy
