Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 2 |
Descriptor
Coding | 2 |
Instructional Effectiveness | 2 |
Novices | 2 |
Programming | 2 |
Achievement Gains | 1 |
Classification | 1 |
Computer Science Education | 1 |
Computer Software | 1 |
Distance Education | 1 |
Electronic Learning | 1 |
Elementary School Teachers | 1 |
More ▼ |
Author
Barnes, Tiffany | 1 |
Bers, Marina | 1 |
Chi, Min | 1 |
Kapoor, Madhu | 1 |
Mao, Ye | 1 |
Marwan, Samiha | 1 |
Price, Thomas W. | 1 |
Shi, Yang | 1 |
Yang, Zhanxia | 1 |
Publication Type
Reports - Research | 2 |
Journal Articles | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Elementary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kapoor, Madhu; Yang, Zhanxia; Bers, Marina – Journal of Technology and Teacher Education, 2022
Prior work has shown a lack of quality professional development (PD) programs specifically targeted for early elementary teachers to improve their knowledge and self-efficacy around teaching coding in their classrooms. Whereas traditional PD programs in this area have relied upon in-person workshops, the COVID-19 pandemic necessitated the need to…
Descriptors: Elementary School Teachers, Faculty Development, Electronic Learning, Distance Education
Mao, Ye; Shi, Yang; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2021
As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…
Descriptors: Programming, Computer Science Education, Learning Processes, Learning Analytics