Miheon Jo

13 papers receiving 437 citations

Peers

Miheon Jo
Comparison fields: 5 of 60
  • Computer Science Applications 81
  • Human-Computer Interaction 84
  • Social Psychology 233
  • Control and Systems Engineering 167
  • Computer Vision and Pattern Recognition 116
Replace Eun-Ja Hyun with:
Eun-Ja Hyun South Korea
Cansu Oranç Türkiye
Matthew Marge United States
Joachim de Greeff United Kingdom
Kai-Yi Chin Taiwan
Shizuko Matsuzoe Japan
Maddy D. Janse Netherlands
Vicky Charisi Netherlands
Jacqueline Kory Westlund United States
Sofia Serholt Sweden
Miheon Jo relative to Eun-Ja Hyun South Korea Eun-Ja Hyun's profile →
Citations per field
00.5×1.5×2.2×
Eun-Ja Hyun · 1×
Citations per year

Countries citing papers authored by Miheon Jo

Since Specialization
Citations

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

Fields of papers citing papers by Miheon Jo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Miheon Jo, 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 Miheon Jo Line = papers co-authored together Miheon Jo links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2008180
2 2006149
3 2015126
4 19966
5 20116
6 20116
7 20115
8
Robot-Assisted Learning in r-Learning
20092
9
Current Status and Problems of Communication between Teachers and Parents using SMS
20092
10
The Current Status and Causes of Elementary Students' Internet Addiction
20041
11
Design And Implementation Of The Automatic Rubric Generation System For The NEIS Based Performance Assessment Using Data Mining Technology
20051
12 20191
13 20121
14 20181
15 20180

About Miheon Jo

Miheon Jo is a scholar working on Information Systems, Computer Vision and Pattern Recognition, Control and Systems Engineering, Computer Networks and Communications and Social Psychology, having authored 15 papers that have together received 487 indexed citations. Recurring topics across this work include Education and Learning Interventions (7 papers), Augmented Reality Applications (5 papers), Robotics and Automated Systems (4 papers), Educational Research and Pedagogy (4 papers), Educational Systems and Policies (2 papers), Social Robot Interaction and HRI (2 papers), Delphi Technique in Research (1 paper) and Online and Blended Learning (1 paper). The work is most often cited by research in Computer Science Applications (81 citations), Human-Computer Interaction (84 citations), Social Psychology (233 citations), Control and Systems Engineering (167 citations) and Computer Vision and Pattern Recognition (116 citations). Miheon Jo has collaborated with scholars based in South Korea and Australia. Frequent co-authors include Jeonghye Han, Jun Hyung Jo, Sungho Kim, Eun-Ja Hyun, Hyo‐Jeong So, Namgyu Kim, Gerard Jounghyun Kim and Nam Kyu Kim. Their work appears in journals such as Computers & Education, Educational Technology Research and Development, INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences, International Journal of Digital Content Technology and its Applications and Journal of Information Processing Systems.

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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