Won Sug Shin

1.1k citations
21 papers · 788 indexed · h-index 12
Topics
Education and Technology Integration (7 papers)Education and Learning Interventions (5 papers)Online and Blended Learning (5 papers)

In The Last Decade

Won Sug Shin

18 papers receiving 747 citations

Peers

Won Sug Shin
Comparison fields: 5 of 85
  • Education 385
  • Information Systems 319
  • Information Systems and Management 155
  • Human-Computer Interaction 120
  • Sociology and Political Science 108
Replace Alberto Cattáneo with:
Alberto Cattáneo Switzerland
Bing Mei China
Yanjie Song Hong Kong
Fernando Martínez Abad Spain
Yong‐Ming Huang Taiwan
Maria Perifanou Greece
Rhonda Christensen United States
Yu-Sheng Su Taiwan
Hong-Ren Chen Taiwan
Maja Pušnik Slovenia
Won Sug Shin relative to Alberto Cattáneo Switzerland Alberto Cattáneo's profile →
Citations per field
00.5×3.3×
Alberto Cattáneo · 1×
Citations per year

Countries citing papers authored by Won Sug Shin

Since Specialization
Citations

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

Fields of papers citing papers by Won Sug Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Won Sug Shin. 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 Won Sug Shin. The network helps show where Won Sug Shin may publish in the future.

Co-authorship network of co-authors of Won Sug Shin

This figure shows the co-authorship network connecting the top 25 collaborators of Won Sug Shin. A scholar is included among the top collaborators of Won Sug Shin 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 Won Sug Shin. Won Sug Shin 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 41
2 166
3 26
4 7
5 16
6 16
7 82
8
An analysis of Pre-service Teachers’ Perception on the Core Competence of Teachers
0
9 170
10
Students’ Use of Notebook Computers in the College Classroom: Benefits and Pitfalls
5
11 111
12 30
13 12
14 40
15 1
16 51
17
Influence of Technology Integration Course on Preservice Teachers’ Technological Pedagogical and Content Knowledge (TPACK)
3
18
Analyses of the Satisfaction with General Education and Factors Influencing the Selection of Courses
1
19 5
20 0

About Won Sug Shin

Won Sug Shin is a scholar working on Leadership and Management, Information Systems and Management and Human-Computer Interaction, having authored 21 papers that have together received 788 indexed citations. Recurring topics across this work include Education and Technology Integration (7 papers), Education and Learning Interventions (5 papers) and Online and Blended Learning (5 papers). The work is most often cited by research in Information Systems and Management (155 citations), Human-Computer Interaction (120 citations) and Computer Science Applications (106 citations). Won Sug Shin has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Insook Han, Yujung Ko, Minseok Kang, Yong Ju Jung, Changhee Kim, Soo‐yong Byun, In‐Suk Kim, Soojeong Jeong and Seungyeon Han. Their work appears in journals such as IEEE Access, Computers & Education and Teaching and Teacher Education.

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.

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