Il‐Hyun Jo

1.3k total citations
53 papers, 802 citations indexed

About

Il‐Hyun Jo is a scholar working on Information Systems, Computer Science Applications and Education. According to data from OpenAlex, Il‐Hyun Jo has authored 53 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Information Systems, 18 papers in Computer Science Applications and 16 papers in Education. Recurrent topics in Il‐Hyun Jo's work include Online Learning and Analytics (18 papers), Education and Learning Interventions (17 papers) and Online and Blended Learning (14 papers). Il‐Hyun Jo is often cited by papers focused on Online Learning and Analytics (18 papers), Education and Learning Interventions (17 papers) and Online and Blended Learning (14 papers). Il‐Hyun Jo collaborates with scholars based in South Korea, United States and Bulgaria. Il‐Hyun Jo's co-authors include Yeonjeong Park, Meehyun Yoon, Dongho Kim, Ji Hyun Yu, Jungeun Lee, Taeho Yu, Robert Maribe Branch, Dongho Kim, Jihyun Kim and Yunmi Kim and has published in prestigious journals such as Computers & Education, The Internet and Higher Education and Educational Technology Research and Development.

In The Last Decade

Il‐Hyun Jo

43 papers receiving 746 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Il‐Hyun Jo South Korea	14	503	447	238	158	114	53	802
Arif Altun Türkiye	14	346 0.7×	401 0.9×	238 1.0×	141 0.9×	104 0.9×	74	849
Oleksandra Poquet Australia	16	700 1.4×	453 1.0×	292 1.2×	147 0.9×	157 1.4×	42	1.1k
Dan Davis Netherlands	12	508 1.0×	452 1.0×	365 1.5×	139 0.9×	133 1.2×	29	930
Meehyun Yoon South Korea	11	411 0.8×	390 0.9×	224 0.9×	100 0.6×	86 0.8×	20	660
Paula De Barba Australia	12	758 1.5×	454 1.0×	228 1.0×	119 0.8×	156 1.4×	31	1.0k
Rianne Conijn Netherlands	11	417 0.8×	351 0.8×	188 0.8×	135 0.9×	171 1.5×	29	784
Ahmed Mohamed Fahmy Yousef Egypt	16	557 1.1×	389 0.9×	175 0.7×	211 1.3×	80 0.7×	41	909
Kyungbin Kwon United States	17	366 0.7×	398 0.9×	417 1.8×	151 1.0×	84 0.7×	58	891
Rwitajit Majumdar Japan	13	394 0.8×	356 0.8×	214 0.9×	153 1.0×	125 1.1×	85	793
Young Hoan Cho South Korea	13	249 0.5×	501 1.1×	307 1.3×	143 0.9×	129 1.1×	50	945

Countries citing papers authored by Il‐Hyun Jo

Since Specialization

Citations

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

Fields of papers citing papers by Il‐Hyun Jo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Il‐Hyun Jo

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

All Works

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20 of 20 papers shown

Jo, Il‐Hyun, et al.. (2025). Evolving the 4C/ID model through learning analytics approaches: Teaching and learning system design framework for supporting learners' complex problem-solving. 611–619.

Jo, Il‐Hyun, et al.. (2024). Analyzing university students’ argumentative thinking in ill-structured problem solving with ChatGPT collaboration. Korean Association for Educational Information and Media. 30(3). 981–1003.

Jo, Il‐Hyun, et al.. (2024). A Delphi study to develop scaffolding strategies to support complex structural problem solving in web-based PBL environment. Korean Association For Learner-Centered Curriculum And Instruction. 24(14). 83–107. 1 indexed citations

Yoon, Meehyun, et al.. (2023). Task type matters: The impact of virtual reality training on training performance. Journal of Computer Assisted Learning. 40(1). 205–218. 9 indexed citations

Jo, Il‐Hyun, et al.. (2023). A meta-analysis on the Learning Effects of Problem-Based Learning (PBL) in Higher Education. Korean Association For Learner-Centered Curriculum And Instruction. 23(6). 557–579. 1 indexed citations

Huh, Yeol, et al.. (2022). Development and Validation of the Digital Education Ecosystem Quality Evaluation Model and Constructs. Journal of Educational Technology. 38(4). 1171–1222.

Lee, Jungeun, et al.. (2020). Exploration of Predictive Model for Learning Achievement of Behavior Log Using Machine Learning in Video-based Learning Environment. The Journal of Korean Association of Computer Education. 23(2). 53–64. 1 indexed citations

Jo, Il‐Hyun, et al.. (2020). The Effect of Visual Cues on Cognitive Load Depending on Self-Regulation in Video-Based Learning.. Educational Data Mining. 1 indexed citations

Lee, Jungjin, Il‐Hyun Jo, & Hyunggon Park. (2020). Data Reconfiguration Algorithm for Efficient Learning State Classifications Based on Pupil Sizes. The Journal of Korean Institute of Communications and Information Sciences. 45(10). 1756–1766. 1 indexed citations

10.

Jo, Il‐Hyun, Yeonjeong Park, & Jongwoo Song. (2017). Comparisons on Clustering Methods: Use of LMS Log Variables on Academic Courses. 18(2). 159–191. 2 indexed citations

11.

Kim, Jeonghyun, et al.. (2017). Interaction of Learning Motivation with Dashboard Intervention and Its Effect on Learning Achievement. 18(2). 73–99. 1 indexed citations

12.

Park, Yeonjeong, et al.. (2014). Predicting students' learning achievement by using online learning patterns in blended learning environments: Comparison of two cases on linear and non-linear model.. Educational Data Mining. 407–408. 3 indexed citations

13.

Jo, Il‐Hyun, Yeonjeong Park, Jeonghyun Kim, & Jongwoo Song. (2014). Analysis of Online Behavior and Prediction of Learning Performance in Blended Learning Environments. 15(2). 71–88. 13 indexed citations

14.

Jo, Il‐Hyun, et al.. (2013). Usability Study of Middle School English Digital Textbook: A Stimulated Recall Approach. 14(1). 109–136. 2 indexed citations

15.

Jo, Il‐Hyun & Yunmi Kim. (2013). Impact of Learner’s Time Management Strategies on Achievement in an e-learning Environment: A Learning Analytics Approach. 19(1). 83–107. 14 indexed citations

16.

Jo, Il‐Hyun, et al.. (2012). Learning Satisfaction Effect on Transfer of Training for Local Government Officials' Overseas Training Mediated by Change of Vocational Self-efficacy and Job Involvement. 14(2). 261–276.

17.

Jo, Il‐Hyun. (2010). "Effects of Role Division, Interaction, and Shared Mental Model on Individual Learning and Team Performance in a University Classroom". Journal of Educational Technology. 26(3). 1–20. 2 indexed citations

18.

Jo, Il‐Hyun. (2009). Effects of Communicative Competence and Social Network Centralities on Learning Performance in a College-Level Collaborative Learning Situation. 40(2). 77–98. 3 indexed citations

19.

Jo, Il‐Hyun. (2008). An Exploratory Investigation for an Instructional Design Model from the Knowledge Management Perspective. Journal of Educational Technology. 24(3). 241–267. 1 indexed citations

20.

Jo, Il‐Hyun. (2007). Correlation Between Social Network Centrality and College Students' Performance in Blended Learning Environment. The Journal of Korean Association of Computer Education. 10(2). 77–87. 1 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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