Yun‐Fang Tu
- Computer Science Applications top 0.5%
- Education top 5%
- Artificial Intelligence top 5%
- Information Systems top 5%
- Developmental and Educational Psychology top 5%
- Co-authors
- Gwo‐Jen HwangYoumei WangChenchen LiuKai‐Yu TangHui‐Chun ChuBiyun HuangMorris Siu–Yung JongChing Sing Chai
- Topics
- Innovative Teaching and Learning Methods (20 papers)Online Learning and Analytics (13 papers)Mobile Learning in Education (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaComputers & EducationSustainability
In The Last Decade
Yun‐Fang Tu
57 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Computer Science Applications 377
- Education 332
- Artificial Intelligence 255
- Information Systems 244
- Developmental and Educational Psychology 236
Countries citing papers authored by Yun‐Fang Tu
This map shows the geographic impact of Yun‐Fang Tu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yun‐Fang Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun‐Fang Tu more than expected).
Fields of papers citing papers by Yun‐Fang Tu
This network shows the impact of papers produced by Yun‐Fang Tu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yun‐Fang Tu. The network helps show where Yun‐Fang Tu may publish in the future.
Co-authorship network of co-authors of Yun‐Fang Tu
This figure shows the co-authorship network connecting the top 25 collaborators of Yun‐Fang Tu. A scholar is included among the top collaborators of Yun‐Fang Tu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yun‐Fang Tu. Yun‐Fang Tu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 1 | |
| 10 | 8 | |
| 11 | 25 | |
| 12 | 18 | |
| 13 | 5 | |
| 14 | 1 | |
| 15 | 27 | |
| 16 | 8 | |
| 17 | 16 | |
| 18 | Roles and Research Trends of Artificial Intelligence in Mathematics Education: A Bibliometric Mapping Analysis and Systematic Reviewbreakdown → | 201 |
| 19 | Factors Affecting the Adoption of AI-based Applications in Higher Education: An Analysis of Teachers’ Perspectives using Structural Equation Modeling | 65 |
| 20 | Incorporating a reflective thinking promoting mechanism into artificial intelligence-supported English writing environmentsbreakdown → | 117 |
About Yun‐Fang Tu
Yun‐Fang Tu is a scholar working on Computer Science Applications, Library and Information Sciences and Developmental and Educational Psychology, having authored 65 papers that have together received 1.1k indexed citations. Recurring topics across this work include Innovative Teaching and Learning Methods (20 papers), Online Learning and Analytics (13 papers) and Mobile Learning in Education (13 papers). The work is most often cited by research in Health Informatics (124 citations), Computer Science Applications (377 citations) and Developmental and Educational Psychology (236 citations). Yun‐Fang Tu has collaborated with scholars based in Taiwan, China and Hong Kong. Frequent co-authors include Gwo‐Jen Hwang, Youmei Wang, Chenchen Liu, Kai‐Yu Tang, Chenchen Liu, Hui‐Chun Chu, Biyun Huang, Morris Siu–Yung Jong, Ching Sing Chai and Michael Yi‐Chao Jiang. Their work appears in journals such as SHILAP Revista de lepidopterología, Computers & Education and Sustainability.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.