Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Supporting students’ self-regulated learning in online learning using artificial intelligence applications
2023109 citationsSung-Hee Jin, Mina Yoo et al.International Journal of Educational Technology in Higher Educationprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Sung-Hee Jin'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 Sung-Hee Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sung-Hee Jin more than expected).
This network shows the impact of papers produced by Sung-Hee Jin. 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 Sung-Hee Jin. The network helps show where Sung-Hee Jin may publish in the future.
Co-authorship network of co-authors of Sung-Hee Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Sung-Hee Jin.
A scholar is included among the top collaborators of Sung-Hee Jin 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 Sung-Hee Jin. Sung-Hee Jin is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Jin, Sung-Hee, et al.. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education. 20(1).109 indexed citations breakdown →
Yoo, Mina & Sung-Hee Jin. (2020). Development and Evaluation of Learning Analytics Dashboards to Support Online Discussion Activities.. Educational Technology & Society. 23(2). 1–18.19 indexed citations
Jin, Sung-Hee, et al.. (2019). A Study on design and development of adult learner-friendly curriculum for general education. The Korean Association of General Education. 13(3). 147–177.
9.
Jin, Sung-Hee. (2018). Collaborative instructional models for teaching community service to engineering students. International journal of engineering education. 34(6). 1897–1909.2 indexed citations
10.
Jin, Sung-Hee. (2017). Using Visualization to Motivate Student Participation in Collaborative Online Learning Environments.. Educational Technology & Society. 20(2). 51–62.32 indexed citations
11.
Sung, Eunmo, et al.. (2016). Learning Activities and Learning Behaviors for Learning Analytics in e-Learning Environments. 17(2). 175–202.2 indexed citations
12.
Jin, Sung-Hee, et al.. (2015). A Performance-Based Evaluation Rubric for Assessing and Enhancing Engineering Design Skills in Introductory Engineering Design Courses. International journal of engineering education. 31(4). 1007–1020.9 indexed citations
13.
Sung, Eunmo & Sung-Hee Jin. (2015). The Factor Analysis of Information and Communication Technology Literacy for Primary School Students in South Korea. 16(2). 231–247.
14.
Lee, Young‐Tae & Sung-Hee Jin. (2014). Rolling Discussion Technique for Facilitating Collaborative Engineering Design Activities. International journal of engineering education. 30(2). 449–457.1 indexed citations
Jin, Sung-Hee, et al.. (2012). The Effect of Teacher Feedback to Students’ Question-asking in Large-sized Engineering Classes: A Perspective of Instructional Effectiveness and Efficiency. The Asia-Pacific Education Researcher. 21(3). 1–1.2 indexed citations
17.
Jin, Sung-Hee & Eunmo Sung. (2012). The Relationships among Major Satisfaction, Career Search Efficacy, Career Exploration Behavior with College Students in Engineering Department of a University Using the Structural Equation Modeling. Korean Society for the Study of Vocational Education. 31(1). 1–18.6 indexed citations
18.
Sung, Eunmo & Sung-Hee Jin. (2012). The Effects of Cell Phone Use According to the Adolescence Gender Differences on Self-Regulated Learning and Achievement. 18(4). 441–467.9 indexed citations
19.
Lee, Insook, Eunmo Sung, Junghoon Leem, & Sung-Hee Jin. (2006). A Study on the Development of Collaborative Learning Model and Behavioral Elements in e-Learning Environment. The Journal of Korean Association of Computer Education. 9(2). 27–36.2 indexed citations
20.
Lee, Insook, et al.. (2004). Analysis of Collaborative Learning Behaviors and the Roles of Collaborative Learning Agent. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2004(1). 2748–2754.1 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.