Carole L. Yue

476 total citations
10 papers, 346 citations indexed

About

Carole L. Yue is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience and Developmental and Educational Psychology. According to data from OpenAlex, Carole L. Yue has authored 10 papers receiving a total of 346 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Experimental and Cognitive Psychology, 7 papers in Cognitive Neuroscience and 5 papers in Developmental and Educational Psychology. Recurrent topics in Carole L. Yue's work include Memory Processes and Influences (7 papers), Visual and Cognitive Learning Processes (6 papers) and Educational Strategies and Epistemologies (3 papers). Carole L. Yue is often cited by papers focused on Memory Processes and Influences (7 papers), Visual and Cognitive Learning Processes (6 papers) and Educational Strategies and Epistemologies (3 papers). Carole L. Yue collaborates with scholars based in United States, United Kingdom and Japan. Carole L. Yue's co-authors include Robert A. Bjork, Alan D. Castel, Elizabeth Ligon Bjork, Nate Kornell, Benjamin C. Storm, Rikke Ogawa, Elena Stark, Nicholas C. Soderstrom, Sara Kim and Kenji Ikeda and has published in prestigious journals such as Journal of Educational Psychology, Memory & Cognition and Medical Education.

In The Last Decade

Carole L. Yue

10 papers receiving 323 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Carole L. Yue United States	9	173	166	120	77	54	10	346
Dung C. Bui United States	10	152 0.9×	159 1.0×	119 1.0×	105 1.4×	39 0.7×	12	364
Kathryn T. Wissman United States	10	168 1.0×	103 0.6×	233 1.9×	80 1.0×	43 0.8×	22	358
Amber E. Witherby United States	10	193 1.1×	149 0.9×	227 1.9×	126 1.6×	55 1.0×	22	440
Jan‐Louis Kruger Australia	14	143 0.8×	309 1.9×	104 0.9×	38 0.5×	31 0.6×	51	792
Kayla Morehead United States	6	185 1.1×	125 0.8×	80 0.7×	162 2.1×	32 0.6×	9	329
April Fugett United States	6	178 1.0×	109 0.7×	191 1.6×	40 0.5×	91 1.7×	10	364
Stephen Wee Hun Lim Singapore	11	106 0.6×	131 0.8×	127 1.1×	99 1.3×	35 0.6×	28	372
Srdan Medimorec Canada	9	108 0.6×	87 0.5×	146 1.2×	103 1.3×	31 0.6×	15	347
Tino Endres Germany	12	286 1.7×	232 1.4×	124 1.0×	140 1.8×	46 0.9×	24	466
Yael Sidi Israel	10	107 0.6×	110 0.7×	59 0.5×	54 0.7×	34 0.6×	19	299

Countries citing papers authored by Carole L. Yue

Since Specialization

Citations

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

Fields of papers citing papers by Carole L. Yue

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carole L. Yue

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

All Works

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10 of 10 papers shown

Yue, Carole L. & Elizabeth Ligon Bjork. (2017). Using Selective Redundancy to Eliminate the Seductive Details Effect. Applied Cognitive Psychology. 31(5). 565–571. 12 indexed citations

Ikeda, Kenji, Carole L. Yue, Kou Murayama, & Alan D. Castel. (2016). Achievement goals affect metacognitive judgments.. Motivation Science. 2(4). 199–219. 12 indexed citations

Yue, Carole L., et al.. (2016). Metacognition and proofreading: the roles of aging, motivation, and interest. Aging Neuropsychology and Cognition. 24(2). 216–226. 7 indexed citations

Bjork, Robert A. & Carole L. Yue. (2016). Commentary: Is disfluency desirable?. Metacognition and Learning. 11(1). 133–137. 16 indexed citations

Soderstrom, Nicholas C., Carole L. Yue, & Elizabeth Ligon Bjork. (2015). Metamemory and Education. Oxford University Press eBooks. 12 indexed citations

Yue, Carole L., Nicholas C. Soderstrom, & Elizabeth Ligon Bjork. (2015). Partial testing can potentiate learning of tested and untested material from multimedia lessons.. Journal of Educational Psychology. 107(4). 991–1005. 13 indexed citations

Yue, Carole L., Benjamin C. Storm, Nate Kornell, & Elizabeth Ligon Bjork. (2014). Highlighting and Its Relation to Distributed Study and Students’ Metacognitive Beliefs. Educational Psychology Review. 27(1). 69–78. 38 indexed citations

Yue, Carole L., Elizabeth Ligon Bjork, & Robert A. Bjork. (2013). Reducing verbal redundancy in multimedia learning: An undesired desirable difficulty?. Journal of Educational Psychology. 105(2). 266–277. 63 indexed citations

Yue, Carole L., et al.. (2013). Applying the cognitive theory of multimedia learning: an analysis of medical animations. Medical Education. 47(4). 375–387. 39 indexed citations

10.

Yue, Carole L., Alan D. Castel, & Robert A. Bjork. (2012). When disfluency is—and is not—a desirable difficulty: The influence of typeface clarity on metacognitive judgments and memory. Memory & Cognition. 41(2). 229–241. 134 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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