Publication Date
| In 2026 | 0 |
| Since 2025 | 3 |
Descriptor
| Identification | 3 |
| Accuracy | 2 |
| Artificial Intelligence | 2 |
| Programming | 2 |
| Algorithms | 1 |
| Coding | 1 |
| Computer Science Education | 1 |
| Computer Software | 1 |
| Data Analysis | 1 |
| Electronic Learning | 1 |
| Emotional Response | 1 |
| More ▼ | |
Author
| Austin Wyman | 1 |
| Chenglu Li | 1 |
| Liang Chen | 1 |
| Linjing Wu | 1 |
| Qingtang Liu | 1 |
| Wangda Zhu | 1 |
| Wanli Xing | 1 |
| Xinyue Jiao | 1 |
| Xuan Jin | 1 |
| Xuelin Xiang | 1 |
| Xueyan Yang | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 3 |
| Journal Articles | 2 |
Education Level
| High Schools | 1 |
| Secondary Education | 1 |
Audience
| Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
Zifeng Liu; Wanli Xing; Xinyue Jiao; Chenglu Li; Wangda Zhu – Education and Information Technologies, 2025
The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…
Descriptors: High School Students, Coding, Artificial Intelligence, Electronic Learning
Linjing Wu; Xuelin Xiang; Xueyan Yang; Xuan Jin; Liang Chen; Qingtang Liu – Educational Technology Research and Development, 2025
Problem-solving strategies are crucial in learning programming. Owing to their hidden nature, traditional methods such as interviews and questionnaires cannot reflect the details and differences of problem-solving strategies in programming. This study uses the Hidden Markov Model to detect and compare the problem-solving strategies of different…
Descriptors: Markov Processes, Problem Solving, Programming, Identification

Peer reviewed
Direct link
