Jeeheon Ryu

865 total citations
84 papers, 558 citations indexed

About

Jeeheon Ryu is a scholar working on Information Systems, Human-Computer Interaction and Safety Research. According to data from OpenAlex, Jeeheon Ryu has authored 84 papers receiving a total of 558 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Information Systems, 14 papers in Human-Computer Interaction and 12 papers in Safety Research. Recurrent topics in Jeeheon Ryu's work include Education and Learning Interventions (36 papers), Diverse Approaches in Healthcare and Education Studies (11 papers) and Education, Safety, and Science Studies (11 papers). Jeeheon Ryu is often cited by papers focused on Education and Learning Interventions (36 papers), Diverse Approaches in Healthcare and Education Studies (11 papers) and Education, Safety, and Science Studies (11 papers). Jeeheon Ryu collaborates with scholars based in South Korea and United States. Jeeheon Ryu's co-authors include Amy L. Baylor, Min-Jeong Kim, Jewoong Moon, Sanghoon Park, E. Shen, Duckhee Chae, Fengfeng Ke, Keiko Asami, Jae Yong Yoo and Ardith Z. Doorenbos and has published in prestigious journals such as Frontiers in Psychology, Sustainability and British Journal of Educational Technology.

In The Last Decade

Jeeheon Ryu

58 papers receiving 481 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jeeheon Ryu South Korea 11 167 157 124 122 112 84 558
Amanda Jarrell Canada 10 127 0.8× 139 0.9× 59 0.5× 144 1.2× 62 0.6× 15 516
Kate M. Xu Netherlands 11 222 1.3× 203 1.3× 88 0.7× 204 1.7× 117 1.0× 25 759
Mary C. Dyson United Kingdom 12 100 0.6× 130 0.8× 72 0.6× 79 0.6× 180 1.6× 47 665
Melina Klepsch Germany 7 128 0.8× 266 1.7× 130 1.0× 324 2.7× 126 1.1× 8 651
Regina Kaplan‐Rakowski United States 15 361 2.2× 156 1.0× 71 0.6× 100 0.8× 270 2.4× 48 921
Mariya Pachman Australia 10 152 0.9× 128 0.8× 69 0.6× 81 0.7× 66 0.6× 15 384
Lijia Lin China 15 314 1.9× 380 2.4× 92 0.7× 343 2.8× 114 1.0× 42 818
Eric Poitras Canada 15 268 1.6× 306 1.9× 142 1.1× 38 0.3× 54 0.5× 50 680
Jewoong Moon United States 15 249 1.5× 230 1.5× 157 1.3× 46 0.4× 74 0.7× 54 750
Filip Děchtěrenko Czechia 10 74 0.4× 164 1.0× 77 0.6× 92 0.8× 34 0.3× 52 473

Countries citing papers authored by Jeeheon Ryu

Since Specialization
Citations

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

Fields of papers citing papers by Jeeheon Ryu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeeheon Ryu

This figure shows the co-authorship network connecting the top 25 collaborators of Jeeheon Ryu. A scholar is included among the top collaborators of Jeeheon Ryu 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 Jeeheon Ryu. Jeeheon Ryu 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
1.
Park, Sanghoon, et al.. (2023). The effects of physical fidelity and task repetition on perceived task load and performance in the virtual reality‐based training simulation. British Journal of Educational Technology. 55(4). 1507–1527. 3 indexed citations
2.
Park, Sanghoon, et al.. (2022). How does Dental Students’ expertise influence their clinical performance and Perceived Task load in a virtual Dental Lab?. Journal of Computing in Higher Education. 35(2). 245–271. 5 indexed citations
3.
Chae, Duckhee, et al.. (2021). E‐learning cultural competence for public health workers: A feasibility and pilot study. Public Health Nursing. 38(5). 897–906. 4 indexed citations
4.
Ke, Fengfeng, et al.. (2020). Engagement and effectiveness of symbolic and iconic learning support for math problem representation: an eye tracking study. Interactive Learning Environments. 31(3). 1514–1531. 5 indexed citations
5.
Shin, Aram, et al.. (2020). The Effects of Computer-Based Teaching Simulation for Pre-service Teachers: a meta-analysis. Teacher Education Research. 59(3). 429–444. 2 indexed citations
6.
Park, Sanghoon, et al.. (2019). Exploring the influences of immersive virtual reality pre-service teacher training simulations on teacher efficacy. Society for Information Technology & Teacher Education International Conference. 2112–2116. 1 indexed citations
7.
Ryu, Jeeheon & Fengfeng Ke. (2018). Increasing Persona Effects: Does It Matter the Voice and Appearance of Animated Pedagogical Agent. 19(1). 61–91. 7 indexed citations
8.
Ryu, Jeeheon, et al.. (2016). Developing a 3D Virtual Environment for Hearing Impaired Learners’ Learning of CNC Machine Operation. Society for Information Technology & Teacher Education International Conference. 2016(1). 2450–2454. 1 indexed citations
10.
Ryu, Jeeheon, et al.. (2013). The Impact of Gesture and Facial Expression on Learning Comprehension and Persona Effect of Pedagogical Agent. 16(3). 281–292. 6 indexed citations
11.
Ryu, Jeeheon, et al.. (2012). Latent Mean Comparison of Digital Textbook and Gender Differences in Elementary School. The Korean Journal of Educational Methodology Studies. 24(3). 617–636. 3 indexed citations
12.
Ryu, Jeeheon. (2012). The Effect of Image Realism and Learner's Expertise on Persona Effect of Pedagogical Agent. 15(1). 47–56. 4 indexed citations
13.
Ryu, Jeeheon. (2011). Sensitivity of Cognitive Load Factors and Prediction for Learning Achievement upon the Levels of Task in Multimedia Learning. 17(3). 309–332. 2 indexed citations
14.
Ryu, Jeeheon, et al.. (2011). Research Trends on Digital Textbook and Meta-analysis on its Academic Achievement. The Korean Journal of Educational Methodology Studies. 23(3). 635–663. 3 indexed citations
15.
Ryu, Jeeheon. (2010). The Effects of Screen Layout of PDA and Types of Task on Response Time and Users' Preference. 16(1). 71–94. 1 indexed citations
16.
Ryu, Jeeheon. (2009). The Impact of Cognitive Load Factors and Arousal Levels of Galvanic Skin Response on Task Performance in Computer Based Learning. 12(3). 279–288. 1 indexed citations
17.
Park, Sanghoon, Minjeong Kim, & Jeeheon Ryu. (2004). Searching for Optimized ROI Process for E-Learning. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2004(1). 416–419. 1 indexed citations
18.
Park, Sanghoon & Jeeheon Ryu. (2004). The effects of pre-service teacher’s self-reflection and achievement on the satisfaction with E-portfolio.. Society for Information Technology & Teacher Education International Conference. 2004(1). 2528–2530. 1 indexed citations
19.
Ryu, Jeeheon, et al.. (2003). Designing Adaptive Learning Objects. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2003(1). 1152–1155. 3 indexed citations
20.
Ryu, Jeeheon, et al.. (2003). Meta-Analysis of the Effectiveness of Pedagogical Agent. EdMedia: World Conference on Educational Media and Technology. 2003(1). 479–486. 7 indexed citations

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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