Meehyun Yoon

972 citations
20 papers · 660 indexed · h-index 11
Topics
Online Learning and Analytics (10 papers)Innovative Teaching and Learning Methods (10 papers)Online and Blended Learning (10 papers)
Partner nations
South KoreaUnited States

In The Last Decade

Meehyun Yoon

17 papers receiving 624 citations

Peers

Meehyun Yoon
Comparison fields: 5 of 60
  • Computer Science Applications 411
  • Education 390
  • Developmental and Educational Psychology 224
  • Information Systems 100
  • Artificial Intelligence 86
Replace Il‐Hyun Jo with:
Il‐Hyun Jo South Korea
Hengtao Tang United States
George Gadanidis Canada
Taotao Long China
Tal Soffer Israel
Lisa-Angelique Lim Australia
Hercy N.H. Cheng Taiwan
Xian Peng China
Stephanie B. Corliss United States
Nora’ayu Ahmad Uzir Malaysia
Meehyun Yoon relative to Il‐Hyun Jo South Korea Il‐Hyun Jo's profile →
Citations per field
00.5×1.5×
Il‐Hyun Jo · 1×
Citations per year

Countries citing papers authored by Meehyun Yoon

Since Specialization
Citations

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

Fields of papers citing papers by Meehyun Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meehyun Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of Meehyun Yoon. A scholar is included among the top collaborators of Meehyun Yoon 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 Meehyun Yoon. Meehyun Yoon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 9
3 2
4 8
5 3
6 81
7 20
8 61
9 0
10 97
11 0
12 11
13
Analyzing the log patterns of adult learners in LMS using learning analytics
1
14 80
15 112
16 22
17 74
18
Constructing Proxy Variables to Measure Adult Learners' Time Management Strategies in LMS.
39
19
Effects of Communication Competence and Social Network Centralities on Learner Performance
6
20 34

About Meehyun Yoon

Meehyun Yoon is a scholar working on Computer Science Applications, Developmental and Educational Psychology and Leadership and Management, having authored 20 papers that have together received 660 indexed citations. Recurring topics across this work include Online Learning and Analytics (10 papers), Innovative Teaching and Learning Methods (10 papers) and Online and Blended Learning (10 papers). The work is most often cited by research in Computer Science Applications (411 citations), Developmental and Educational Psychology (224 citations) and Education (390 citations). Meehyun Yoon has collaborated with scholars based in South Korea and United States. Frequent co-authors include Il‐Hyun Jo, Dongho Kim, Jungeun Lee, Dongho Kim, Eulho Jung, Sanghoon Park, Robert Maribe Branch, Yeonjeong Park, Janette R. Hill and Barbara Oakley. Their work appears in journals such as Computers & Education, The Internet and Higher Education and Journal of Computer Assisted Learning.

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

Rankless by CCL
2026