Sunbok Lee

25 papers receiving 443 citations

Peers

Sunbok Lee
Comparison fields: 5 of 108
  • Computer Science Applications 199
  • Health Information Management 34
  • Health Informatics 6
  • Artificial Intelligence 115
  • Education 104
Replace Jae Young Chung with:
Jae Young Chung South Korea
Carlos Felipe Rodríguez-Hernández United States
Vicki Bennett Australia
Farshid Marbouti United States
Clare Baek United States
Gloria Milena Fernandez-Nieto Australia
Yalın Kılıç Türel Türkiye
Rwitajit Majumdar Japan
Nick Z. Zacharis Greece
Robin De Croon Belgium
Sunbok Lee relative to Jae Young Chung South Korea Jae Young Chung's profile →
Citations per field
00.5×
Jae Young Chung · 1×
Citations per year

Countries citing papers authored by Sunbok Lee

Since Specialization
Citations

This map shows the geographic impact of Sunbok Lee'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 Sunbok Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunbok Lee more than expected).

Fields of papers citing papers by Sunbok Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunbok Lee. 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 Sunbok Lee. The network helps show where Sunbok Lee may publish in the future.

Co-authors

The 24 scholars most cited alongside Sunbok Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sunbok Lee Line = papers co-authored together Sunbok Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018131
2 2019101
3 201935
4 201029
5 202029
6 201918
7 201516
8 201915
9 201614
10 201512
11
Detecting cheaters in MOOCs using item response theory and learning analytics
201612
12 20229
13 20238
14 20158
15 20156
16
Re-designing the structure of online courses to empower educational data mining
20185
17 20215
18 20194
19 20144
20 20212

About Sunbok Lee

Sunbok Lee is a scholar working on Management Science and Operations Research, Computer Networks and Communications, Artificial Intelligence, Computer Science Applications and Statistics and Probability, having authored 26 papers that have together received 468 indexed citations. Recurring topics across this work include Psychometric Methodologies and Testing (6 papers), Advanced Statistical Modeling Techniques (5 papers), Online Learning and Analytics (5 papers), Meta-analysis and systematic reviews (3 papers), Advanced Causal Inference Techniques (2 papers), Statistical Methods and Bayesian Inference (2 papers), Statistical Methods and Inference (2 papers) and Imbalanced Data Classification Techniques (2 papers). The work is most often cited by research in Computer Science Applications (199 citations), Health Information Management (34 citations), Health Informatics (6 citations), Artificial Intelligence (115 citations) and Education (104 citations). Sunbok Lee has collaborated with scholars based in United States, South Korea and Taiwan. Frequent co-authors include Jae Young Chung, Giora Alexandron, David E. Pritchard, Gene H. Brody, Man‐Kit Lei, Wei Liu, José A. Ruipérez‐Valiente, Qun Zhao, Jason Langley and Hanjoe Kim. Their work appears in journals such as Children and Youth Services Review, Applied Sciences, Journal of Adolescent Health, Psychological Methods and Journal of Educational Measurement.

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.

Explore authors with similar magnitude of impact