L. Kate Wright

536 total citations
31 papers, 368 citations indexed

About

L. Kate Wright is a scholar working on Education, Molecular Biology and Developmental and Educational Psychology. According to data from OpenAlex, L. Kate Wright has authored 31 papers receiving a total of 368 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Education, 15 papers in Molecular Biology and 10 papers in Developmental and Educational Psychology. Recurrent topics in L. Kate Wright's work include Genetics, Bioinformatics, and Biomedical Research (14 papers), Science Education and Pedagogy (14 papers) and Innovative Teaching Methods (5 papers). L. Kate Wright is often cited by papers focused on Genetics, Bioinformatics, and Biomedical Research (14 papers), Science Education and Pedagogy (14 papers) and Innovative Teaching Methods (5 papers). L. Kate Wright collaborates with scholars based in United States. L. Kate Wright's co-authors include Dina L. Newman, Jeffrey Nicholas Fisk, Christina M. Catavero, Christopher W. Snyder, Ian M. Dickerson, Michael G. Schrlau, Margaret A. Franzen, Kathryn G. Miller, David Gee and David R. Karger and has published in prestigious journals such as PLoS ONE, Small and Journal of Chemical Education.

In The Last Decade

L. Kate Wright

26 papers receiving 349 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
L. Kate Wright United States 10 218 136 90 52 36 31 368
Molly Bolger United States 9 289 1.3× 45 0.3× 139 1.5× 25 0.5× 24 0.7× 16 436
Sara A. Wyse United States 6 325 1.5× 64 0.5× 102 1.1× 38 0.7× 15 0.4× 11 422
Elena Bray Speth United States 12 295 1.4× 212 1.6× 142 1.6× 41 0.8× 22 0.6× 14 655
Jeffrey T. Olimpo United States 10 283 1.3× 39 0.3× 87 1.0× 67 1.3× 33 0.9× 38 422
Marc H. W. van Mil Netherlands 8 124 0.6× 101 0.7× 72 0.8× 99 1.9× 9 0.3× 18 368
Jay B. Labov United States 13 428 2.0× 105 0.8× 76 0.8× 92 1.8× 25 0.7× 31 681
Carl‐Johan Rundgren Sweden 12 372 1.7× 47 0.3× 214 2.4× 18 0.3× 61 1.7× 32 513
Julia Gouvea United States 11 356 1.6× 34 0.3× 220 2.4× 48 0.9× 16 0.4× 36 494
Aaron Rogat United States 5 232 1.1× 57 0.4× 130 1.4× 10 0.2× 19 0.5× 7 304
Lisa Montplaisir United States 12 318 1.5× 29 0.2× 141 1.6× 31 0.6× 30 0.8× 18 451

Countries citing papers authored by L. Kate Wright

Since Specialization
Citations

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

Fields of papers citing papers by L. Kate Wright

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L. Kate Wright. 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 L. Kate Wright. The network helps show where L. Kate Wright may publish in the future.

Co-authorship network of co-authors of L. Kate Wright

This figure shows the co-authorship network connecting the top 25 collaborators of L. Kate Wright. A scholar is included among the top collaborators of L. Kate Wright 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 L. Kate Wright. L. Kate Wright 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.
Wright, L. Kate, et al.. (2025). Sketchy understandings: drawings reveal where students may need additional support to understand scale and abstraction in common representations of DNA. Journal of Microbiology and Biology Education. 26(2). e0007025–e0007025. 1 indexed citations
2.
Wright, L. Kate, et al.. (2025). Visual representations of energy and chemical bonding in biology and chemistry textbooks: A case study of ATP hydrolysis. Biochemistry and Molecular Biology Education. 53(3). 274–285.
3.
Couch, Brian A., et al.. (2025). Biology exams rarely use visual models to engage higher-order cognitive skills. PLoS ONE. 20(7). e0317077–e0317077.
4.
Wright, L. Kate, et al.. (2024). Constructing analogies: Developing critical thinking through a collaborative task. Biochemistry and Molecular Biology Education. 52(5). 569–579.
5.
Newman, Dina L., et al.. (2024). Student-Generated Analogies for Learning about Information Flow. CourseSource. 11. 2 indexed citations
6.
Hsu, Jeremy, et al.. (2024). An Exploration of Spatial Visualization Skills: Investigating Students’ Use of 3D Models in Science Problems during Think-Aloud Interviews. Journal of Chemical Education. 101(9). 3624–3634. 3 indexed citations
7.
Wright, L. Kate, et al.. (2022). The DNA Landscape: Development and Application of a New Framework for Visual Communication about DNA. CBE—Life Sciences Education. 21(3). ar47–ar47. 7 indexed citations
8.
Newman, Dina L., et al.. (2021). Punnett Squares or Protein Production? The Expert–Novice Divide for Conceptions of Genes and Gene Expression. CBE—Life Sciences Education. 20(4). ar53–ar53. 12 indexed citations
9.
Newman, Dina L., et al.. (2020). An Online Interactive Video Vignette that Helps Students Learn Key Concepts of Fermentation and Respiration. Journal of Microbiology and Biology Education. 21(2). 4 indexed citations
10.
Newman, Dina L., et al.. (2020). Interactive Video Vignettes (IVVs) to Help Students Learn Genetics Concepts. CourseSource. 7. 3 indexed citations
11.
Wright, L. Kate, et al.. (2019). A Close-Up Look at PCR. CourseSource. 6. 1 indexed citations
12.
Wright, L. Kate, et al.. (2019). An examination of students' perceptions of the Kekulé resonance representation using a perceptual learning theory lens. Chemistry Education Research and Practice. 20(4). 659–666. 21 indexed citations
13.
Newman, Dina L., et al.. (2018). Physical models can provide superior learning opportunities beyond the benefits of active engagements. Biochemistry and Molecular Biology Education. 46(5). 435–444. 29 indexed citations
14.
Wright, L. Kate, et al.. (2018). Arrows in Biology: Lack of Clarity and Consistency Points to Confusion for Learners. CBE—Life Sciences Education. 17(1). ar6–ar6. 19 indexed citations
15.
Wright, L. Kate, Christina M. Catavero, & Dina L. Newman. (2017). The DNA Triangle and Its Application to Learning Meiosis. CBE—Life Sciences Education. 16(3). ar50–ar50. 7 indexed citations
16.
Wright, L. Kate, et al.. (2016). Web-Based Interactive Video Vignettes Create a Personalized Active Learning Classroom for Introducing Big Ideas in Introductory Biology.. RIT Scholar Works (Rochester Institute of Technology). 42(2). 32–43. 7 indexed citations
17.
Newman, Dina L., Christopher W. Snyder, Jeffrey Nicholas Fisk, & L. Kate Wright. (2016). Development of the Central Dogma Concept Inventory (CDCI) Assessment Tool. CBE—Life Sciences Education. 15(2). ar9–ar9. 41 indexed citations
18.
19.
Newman, Dina L., Christina M. Catavero, & L. Kate Wright. (2012). Students Fail to Transfer Knowledge of Chromosome Structure to Topics Pertaining to Cell Division. CBE—Life Sciences Education. 11(4). 425–436. 39 indexed citations
20.
Wright, L. Kate & Dina L. Newman. (2011). An interactive modeling lesson increases students' understanding of ploidy during meiosis. Biochemistry and Molecular Biology Education. 39(5). 344–351. 23 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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