Kihyun Ryoo

815 total citations
19 papers, 578 citations indexed

About

Kihyun Ryoo is a scholar working on Education, Developmental and Educational Psychology and Experimental and Cognitive Psychology. According to data from OpenAlex, Kihyun Ryoo has authored 19 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Education, 13 papers in Developmental and Educational Psychology and 7 papers in Experimental and Cognitive Psychology. Recurrent topics in Kihyun Ryoo's work include Innovative Teaching and Learning Methods (12 papers), Science Education and Pedagogy (11 papers) and Visual and Cognitive Learning Processes (7 papers). Kihyun Ryoo is often cited by papers focused on Innovative Teaching and Learning Methods (12 papers), Science Education and Pedagogy (11 papers) and Visual and Cognitive Learning Processes (7 papers). Kihyun Ryoo collaborates with scholars based in United States, Hungary and Russia. Kihyun Ryoo's co-authors include Marcia C. Linn, Bryan A. Brown, Ou Lydia Liu, Anna N. Rafferty, Libby Gerard, Kevin W. McElhaney, Jamie Rodriguez, Vanessa Svihla and Monica L. Miles and has published in prestigious journals such as Science, Journal of Educational Psychology and Journal of Research in Science Teaching.

In The Last Decade

Kihyun Ryoo

19 papers receiving 539 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kihyun Ryoo United States 12 397 326 97 62 57 19 578
Sharon K. Schulze United States 4 382 1.0× 426 1.3× 145 1.5× 26 0.4× 37 0.6× 6 609
Manoli Pifarré Spain 12 311 0.8× 302 0.9× 50 0.5× 32 0.5× 23 0.4× 41 556
Yao Ting Sung Taiwan 15 320 0.8× 247 0.8× 40 0.4× 29 0.5× 54 0.9× 36 645
Pearla Nesher Israel 16 693 1.7× 265 0.8× 115 1.2× 15 0.2× 63 1.1× 35 944
Shelley Shwu‐Ching Young Taiwan 13 253 0.6× 253 0.8× 46 0.5× 36 0.6× 85 1.5× 44 595
Teresa Secules United States 6 270 0.7× 197 0.6× 36 0.4× 39 0.6× 26 0.5× 6 454
Gregory C. Sales United States 10 269 0.7× 269 0.8× 50 0.5× 15 0.2× 49 0.9× 31 455
Mihye Won Australia 13 287 0.7× 204 0.6× 74 0.8× 26 0.4× 15 0.3× 38 521
Jaume Ametller Spain 10 323 0.8× 176 0.5× 54 0.6× 30 0.5× 11 0.2× 24 468
Roser Pintó Spain 11 394 1.0× 183 0.6× 62 0.6× 21 0.3× 9 0.2× 22 499

Countries citing papers authored by Kihyun Ryoo

Since Specialization
Citations

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

Fields of papers citing papers by Kihyun Ryoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kihyun Ryoo

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

All Works

19 of 19 papers shown
1.
Ryoo, Kihyun, et al.. (2024). Modeling Complex Data from Simulations to Assess Middle School Students’ NGSS-Aligned Science Learning. Measurement Interdisciplinary Research and Perspectives. 22(2). 200–218. 1 indexed citations
2.
Ryoo, Kihyun, et al.. (2022). Promoting equity in the peer review process of journal publication. Science Education. 106(5). 1232–1248. 8 indexed citations
3.
Ryoo, Kihyun, et al.. (2020). Using Machine Learning to Understand Students' Learning Patterns in Simulations.. ICLS. 4 indexed citations
4.
Ryoo, Kihyun, et al.. (2018). Supporting linguistically diverse students' science learning with dynamic visualizations through discourse‐rich practices. Journal of Research in Science Teaching. 56(3). 270–301. 16 indexed citations
5.
Ryoo, Kihyun, et al.. (2018). Promoting Linguistically Diverse Students’ Short-Term and Long-Term Understanding of Chemical Phenomena Using Visualizations. Journal of Science Education and Technology. 27(6). 508–522. 27 indexed citations
6.
Ryoo, Kihyun, et al.. (2017). Exploring different types of assessment items to measure linguistically diverse students’ understanding of energy and matter in chemistry. Chemistry Education Research and Practice. 19(1). 149–166. 6 indexed citations
7.
Ryoo, Kihyun, et al.. (2017). The effects of visualizations on linguistically diverse students’ understanding of energy and matter in life science. Journal of Research in Science Teaching. 54(10). 1274–1301. 21 indexed citations
8.
Ryoo, Kihyun & Marcia C. Linn. (2016). Designing automated guidance for concept diagrams in inquiry instruction. Journal of Research in Science Teaching. 53(7). 1003–1035. 18 indexed citations
9.
Gerard, Libby, Kihyun Ryoo, Kevin W. McElhaney, et al.. (2015). Automated guidance for student inquiry.. Journal of Educational Psychology. 108(1). 60–81. 48 indexed citations
10.
Ryoo, Kihyun & Marcia C. Linn. (2015). Designing and Validating Assessments of Complex Thinking in Science. Theory Into Practice. 54(3). 238–254. 17 indexed citations
11.
Liu, Ou Lydia, et al.. (2015). Measuring Knowledge Integration Learning of Energy Topics: A two-year longitudinal study. International Journal of Science Education. 37(7). 1044–1066. 21 indexed citations
12.
Linn, Marcia C., Libby Gerard, Kihyun Ryoo, et al.. (2014). Computer-Guided Inquiry to Improve Science Learning. Science. 344(6180). 155–156. 59 indexed citations
13.
Ryoo, Kihyun. (2014). Teaching Science Through the Language of Students in Technology-Enhanced Instruction. Journal of Science Education and Technology. 24(1). 29–42. 9 indexed citations
14.
Ryoo, Kihyun & Marcia C. Linn. (2013). Designing guidance for interpreting dynamic visualizations: Generating versus reading explanations. Journal of Research in Science Teaching. 51(2). 147–174. 43 indexed citations
15.
Ryoo, Kihyun & Marcia C. Linn. (2012). Can dynamic visualizations improve middle school students' understanding of energy in photosynthesis?. Journal of Research in Science Teaching. 49(2). 218–243. 78 indexed citations
16.
Ryoo, Kihyun & Marcia C. Linn. (2010). Student progress in understanding energy concepts in photosynthesis using interactive visualizations. International Conference of Learning Sciences. 480–481. 3 indexed citations
17.
Svihla, Vanessa, et al.. (2010). Energy across the curriculum: Cumulative learning using embedded assessment results. International Conference of Learning Sciences. 3 indexed citations
18.
Brown, Bryan A., Kihyun Ryoo, & Jamie Rodriguez. (2009). Pathway Towards Fluency: Using ‘disaggregate instruction’ to promote science literacy. International Journal of Science Education. 32(11). 1465–1493. 34 indexed citations
19.
Brown, Bryan A. & Kihyun Ryoo. (2008). Teaching science as a language: A “content‐first” approach to science teaching. Journal of Research in Science Teaching. 45(5). 529–553. 162 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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