Yanjin Long
Impact in
-
- Online Learning and Analytics
- Teaching and Learning Programming
- E-Learning and Knowledge Management
-
- Innovative Teaching and Learning Methods
- Educational Games and Gamification
Papers in
-
- Innovative Teaching and Learning Methods 13
- Educational and Psychological Assessments 3
- Educational Games and Gamification 2
- Learning Styles and Cognitive Differences 1
-
- Intelligent Tutoring Systems and Adaptive Learning 12
- Co-authors
- Vincent Aleven (13 shared papers)Kenneth Holstein (1 shared paper)Kenneth R. Koedinger (2 shared papers)Carrie Demmans Epp (1 shared paper)Christian D. Schunn (1 shared paper)F.B. Li (1 shared paper)Susanne P. Lajoie (1 shared paper)Lin Shi (1 shared paper)
- Journals
- ACM Transactions on Computer-Human Interaction (1 paper)User Modeling and User-Adapted Interaction (1 paper)Lecture notes in computer science (9 papers)Water Research X (1 paper)Educational Data Mining (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Yanjin Long
14 papers receiving 321 citations
Peers
Comparison fields: 5 of 38
- Computer Science Applications 203
- Developmental and Educational Psychology 227
- Artificial Intelligence 193
- Human-Computer Interaction 14
- Education 61
Countries citing papers authored by Yanjin Long
This map shows the geographic impact of Yanjin Long'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 Yanjin Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanjin Long more than expected).
Fields of papers citing papers by Yanjin Long
This network shows the impact of papers produced by Yanjin Long. 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 Yanjin Long. The network helps show where Yanjin Long may publish in the future.
Co-authors
The 16 scholars most cited alongside Yanjin Long, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 75 | |
| 2 | 2013 | 58 | |
| 3 | 2014 | 51 | |
| 4 | 2017 | 42 | |
| 5 | 2011 | 23 | |
| 6 | 2016 | 23 | |
| 7 | 2013 | 17 | |
| 8 | 2013 | 16 | |
| 9 | 2015 | 10 | |
| 10 | 2018 | 9 | |
| 11 | 2014 | 5 | |
| 12 | 2011 | 5 | |
| 13 | Redefining "What" in Analyses of Who Does What in MOOCs. | 2016 | 3 |
| 14 | 2012 | 1 | |
| 15 | 2026 | 0 |
About Yanjin Long
Yanjin Long is a scholar working on Developmental and Educational Psychology, Artificial Intelligence, Computer Science Applications, Experimental and Cognitive Psychology and Infectious Diseases, having authored 15 papers that have together received 338 indexed citations. Recurring topics across this work include Innovative Teaching and Learning Methods (13 papers), Intelligent Tutoring Systems and Adaptive Learning (12 papers), Online Learning and Analytics (8 papers), Educational and Psychological Assessments (3 papers), Educational Games and Gamification (2 papers), Visual and Cognitive Learning Processes (1 paper) and Learning Styles and Cognitive Differences (1 paper). The work is most often cited by research in Computer Science Applications (203 citations), Developmental and Educational Psychology (227 citations), Artificial Intelligence (193 citations), Human-Computer Interaction (14 citations) and Education (61 citations). Yanjin Long has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Vincent Aleven, Kenneth Holstein, Kenneth R. Koedinger, Carrie Demmans Epp, Christian D. Schunn, F.B. Li, Susanne P. Lajoie, Lin Shi, Philip H. Winne and Benjamin Goldberg. Their work appears in journals such as ACM Transactions on Computer-Human Interaction, User Modeling and User-Adapted Interaction, Lecture notes in computer science, Water Research X and Educational Data Mining.
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.