Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 3 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 3 |
Descriptor
Computer Science Education | 3 |
Cues | 3 |
Foreign Countries | 2 |
Learning Processes | 2 |
Programming | 2 |
Programming Languages | 2 |
Teaching Methods | 2 |
Art Education | 1 |
Artificial Intelligence | 1 |
Case Studies | 1 |
Comparative Analysis | 1 |
More ▼ |
Author
Chien-Chia Huang | 1 |
Jeevan Chapagain | 1 |
Kayama, Mizue | 1 |
Maruyama, Ryoga | 1 |
Nagai, Takashi | 1 |
Ogata, Shinpei | 1 |
Priti Oli | 1 |
Rabin Banjade | 1 |
Tachi, Nobuyuki | 1 |
Taguchi, Naomi | 1 |
Tzu-Hua Huang | 1 |
More ▼ |
Publication Type
Reports - Research | 2 |
Speeches/Meeting Papers | 2 |
Journal Articles | 1 |
Reports - Evaluative | 1 |
Education Level
Elementary Education | 3 |
Middle Schools | 3 |
Intermediate Grades | 2 |
Junior High Schools | 2 |
Secondary Education | 2 |
Elementary Secondary Education | 1 |
Grade 4 | 1 |
Grade 5 | 1 |
Grade 6 | 1 |
Grade 7 | 1 |
Grade 8 | 1 |
More ▼ |
Audience
Location
Japan | 1 |
Taiwan (Taipei) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating

Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
Yuan-Chen Liu; Tzu-Hua Huang; Chien-Chia Huang – Interactive Learning Environments, 2024
In this study, an interactive programming learning environment was built with two types of error prompt functions: 1) the key prompt and 2) step-by-step prompt. A quasi-experimental study was conducted for five weeks, in which 75 sixth grade students from disadvantaged learning environments in Taipei, Taiwan, were divided into three groups: 1) the…
Descriptors: Programming, Computer Science Education, Cues, Grade 6
Maruyama, Ryoga; Ogata, Shinpei; Kayama, Mizue; Tachi, Nobuyuki; Nagai, Takashi; Taguchi, Naomi – International Association for Development of the Information Society, 2022
This study aims to explore an educational learning environment that supports students to learn conceptual modelling with the unified modelling language (UML). In this study, we call the describing models "UML programming." In this paper, we show an educational UML programming environment for science, technology, engineering, art, and…
Descriptors: Case Studies, Programming Languages, Learning Processes, Models