Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 3 |
Descriptor
Cognitive Processes | 3 |
Computer Science Education | 3 |
Foreign Countries | 3 |
Programming | 3 |
Troubleshooting | 3 |
College Students | 2 |
Difficulty Level | 2 |
Eye Movements | 2 |
Arousal Patterns | 1 |
Computer Software | 1 |
Correlation | 1 |
More ▼ |
Author
Caner, Sonay | 1 |
Chang, Chia-Hu | 1 |
Gaševic, Dragan | 1 |
Giannakos, Michalis | 1 |
Hou, Ting-Yun | 1 |
Lin, Yu-Chih | 1 |
Lin, Yu-Tzu | 1 |
Mangaroska, Katerina | 1 |
Sharma, Kshitij | 1 |
Turkmen, Gamze | 1 |
Wu, Cheng-Chih | 1 |
More ▼ |
Publication Type
Journal Articles | 3 |
Reports - Research | 3 |
Education Level
Higher Education | 3 |
Postsecondary Education | 3 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Turkmen, Gamze; Caner, Sonay – Turkish Online Journal of Distance Education, 2020
This study aims to provide a comprehensive and in-depth investigation of the debugging process in programming teaching in terms of cognitive and metacognitive aspects, based on programming students who demonstrate low, medium, and high programming performance and to propose instructional strategies for scaffolding novice learners in an effective…
Descriptors: Programming, Novices, Electronic Learning, Troubleshooting
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michalis – Journal of Learning Analytics, 2020
Programming is a complex learning activity that involves coordination of cognitive processes and affective states. These aspects are often considered individually in computing education research, demonstrating limited understanding of how and when students learn best. This issue confines researchers to contextualize evidence-driven outcomes when…
Descriptors: Learning Analytics, Data Collection, Instructional Design, Learning Modalities
Lin, Yu-Tzu; Wu, Cheng-Chih; Hou, Ting-Yun; Lin, Yu-Chih; Yang, Fang-Ying; Chang, Chia-Hu – IEEE Transactions on Education, 2016
This study explores students' cognitive processes while debugging programs by using an eye tracker. Students' eye movements during debugging were recorded by an eye tracker to investigate whether and how high- and low-performance students act differently during debugging. Thirty-eight computer science undergraduates were asked to debug two C…
Descriptors: Cognitive Processes, Programming, Computer Software, Computer Science Education