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.
Enhancing teacher AI literacy and integration through different types of cases in teacher professional development
202474 citationsAi-Chu Elisha Ding, Lehong Shi et al.SHILAP Revista de lepidopterologíaprofile →
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 Ikseon Choi'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 Ikseon Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ikseon Choi more than expected).
This network shows the impact of papers produced by Ikseon Choi. 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 Ikseon Choi. The network helps show where Ikseon Choi may publish in the future.
Co-authorship network of co-authors of Ikseon Choi
This figure shows the co-authorship network connecting the top 25 collaborators of Ikseon Choi.
A scholar is included among the top collaborators of Ikseon Choi 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 Ikseon Choi. Ikseon Choi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ding, Ai-Chu Elisha, et al.. (2024). Enhancing teacher AI literacy and integration through different types of cases in teacher professional development. SHILAP Revista de lepidopterología. 6. 100178–100178.74 indexed citations breakdown →
Choi, Ikseon, et al.. (2016). Learning Computer Programming in Context:Developing STEM-integrated Robotics Lesson Module for 5th Grade. Society for Information Technology & Teacher Education International Conference. 2016(1). 68–74.2 indexed citations
12.
Chen, Kang, et al.. (2014). Effects of transglutminase on the quality of white salted noodles made from Korean wheat cultivars.. International Food Research Journal. 21(1). 195–202.3 indexed citations
13.
Choi, Ikseon, et al.. (2010). Discovering Instructional Designers’ Reflection in Performing Instructional Design Tasks.1 indexed citations
14.
Choi, Ikseon, et al.. (2008). Designing Multimedia Case-Based Instruction Accommodating Students’ Diverse Learning Styles. Journal of educational multimedia and hypermedia. 17(1). 5–25.13 indexed citations
Choi, Ikseon & Kyunghwa Lee. (2006). A Case-Based E-Learning Environment for Facilitating Ill-Structured Problem Solving Skills: Classroom Management. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2006(1). 1894–1901.
17.
Choi, Ikseon, et al.. (2006). Physico-chemical Properties of Giant Embryo Brown Rice (Keunnunbyeo). Journal of Applied Biological Chemistry. 49(3). 95–100.20 indexed citations
18.
Choi, Ikseon, et al.. (2004). A Case-Based E-Learning Model for Professional Education: Anesthesiology for Dental Students. EdMedia: World Conference on Educational Media and Technology. 2004(1). 1285–1292.2 indexed citations
Choi, Ikseon & David H. Jonassen. (2000). Learning Objectives from the Perspective of the Experienced Cognition Framework.. Educational Technology archive. 40(6). 36–40.6 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.