Jurgen Tijms

1.4k total citations
44 papers, 949 citations indexed

About

Jurgen Tijms is a scholar working on Developmental and Educational Psychology, Cognitive Neuroscience and Statistics and Probability. According to data from OpenAlex, Jurgen Tijms has authored 44 papers receiving a total of 949 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Developmental and Educational Psychology, 25 papers in Cognitive Neuroscience and 14 papers in Statistics and Probability. Recurrent topics in Jurgen Tijms's work include Reading and Literacy Development (36 papers), Cognitive and developmental aspects of mathematical skills (14 papers) and EEG and Brain-Computer Interfaces (8 papers). Jurgen Tijms is often cited by papers focused on Reading and Literacy Development (36 papers), Cognitive and developmental aspects of mathematical skills (14 papers) and EEG and Brain-Computer Interfaces (8 papers). Jurgen Tijms collaborates with scholars based in Netherlands, Switzerland and United Kingdom. Jurgen Tijms's co-authors include Maurits W. van der Molen, Gorka Fraga González, Milene Bonte, Leo Blomert, Gojko Žarić, Patrick Snellings, Melle J. W. van der Molen, Cornelis J. Stam, Anika Bexkens and Wery P. M. van den Wildenberg and has published in prestigious journals such as PLoS ONE, Child Development and Psychophysiology.

In The Last Decade

Jurgen Tijms

43 papers receiving 920 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jurgen Tijms Netherlands 20 645 584 233 169 140 44 949
Denise H. Wu Taiwan 15 494 0.8× 623 1.1× 226 1.0× 217 1.3× 129 0.9× 34 926
Xiuhong Tong Hong Kong 20 809 1.3× 489 0.8× 290 1.2× 148 0.9× 256 1.8× 62 984
Gilberto Nunes Filho Brazil 6 604 0.9× 754 1.3× 207 0.9× 222 1.3× 109 0.8× 8 1.1k
Taeko N. Wydell United Kingdom 17 818 1.3× 584 1.0× 242 1.0× 139 0.8× 208 1.5× 35 1.0k
Susana Araújo Portugal 16 676 1.0× 394 0.7× 275 1.2× 63 0.4× 198 1.4× 34 777
Rebecca Sandak United States 12 647 1.0× 542 0.9× 216 0.9× 128 0.8× 116 0.8× 13 793
Petroula Mousikou United Kingdom 12 607 0.9× 517 0.9× 158 0.7× 194 1.1× 238 1.7× 27 976
Aibao Zhou China 9 694 1.1× 356 0.6× 319 1.4× 90 0.5× 282 2.0× 37 906
James H. Smith‐Spark United Kingdom 15 470 0.7× 438 0.8× 241 1.0× 208 1.2× 70 0.5× 42 846
Stefan Hawelka Austria 20 677 1.0× 795 1.4× 252 1.1× 147 0.9× 97 0.7× 50 1.1k

Countries citing papers authored by Jurgen Tijms

Since Specialization
Citations

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

Fields of papers citing papers by Jurgen Tijms

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jurgen Tijms

This figure shows the co-authorship network connecting the top 25 collaborators of Jurgen Tijms. A scholar is included among the top collaborators of Jurgen Tijms 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 Jurgen Tijms. Jurgen Tijms 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.
Vaessen, Anniek, et al.. (2024). The COVID generation: Online dyslexia treatment equally effective as face-to-face treatment in a Dutch sample. Annals of Dyslexia. 74(2). 187–196.
2.
Snellings, Patrick, et al.. (2023). Goal-directedness enhances letter-speech sound learning and consolidation in an unknown orthography. Child Development. 94(4). 836–852. 5 indexed citations
3.
Tierney, Adam, et al.. (2023). Attentional modulation of neural sound tracking in children with and without dyslexia. Developmental Science. 27(1). e13420–e13420. 3 indexed citations
4.
Snellings, Patrick, et al.. (2023). A randomised proof‐of‐concept trial on the effectiveness of a game‐based training of phoneme‐grapheme correspondences in pre‐readers. Journal of Computer Assisted Learning. 39(5). 1607–1619. 2 indexed citations
5.
Tijms, Jurgen, et al.. (2021). A network approach to dyslexia: Mapping the reading network. Development and Psychopathology. 35(3). 1011–1025. 12 indexed citations
6.
Tijms, Jurgen, Gorka Fraga González, Iliana I. Karipidis, & Silvia Brem. (2020). The Role of Letter-Speech Sound Integration in Normal and Abnormal Reading Development. Frontiers in Psychology. 11. 1 indexed citations
7.
González, Gorka Fraga, Iliana I. Karipidis, & Jurgen Tijms. (2019). Reply to “Dyslexia: Still Not a Neurodevelopmental Disorder”. Brain Sciences. 9(3). 61–61. 1 indexed citations
8.
Žarić, Gojko, Inge Timmers, Gorka Fraga González, et al.. (2018). Atypical White Matter Connectivity in Dyslexic Readers of a Fairly Transparent Orthography. Frontiers in Psychology. 9. 1147–1147. 15 indexed citations
9.
González, Gorka Fraga, Dirk J. A. Smit, Melle J. W. van der Molen, et al.. (2018). EEG Resting State Functional Connectivity in Adult Dyslexics Using Phase Lag Index and Graph Analysis. Frontiers in Human Neuroscience. 12. 341–341. 57 indexed citations
10.
11.
Tijms, Jurgen, et al.. (2017). Predicting Individual Differences in Reading and Spelling Skill With Artificial Script–Based Letter–Speech Sound Training. Journal of Learning Disabilities. 51(6). 552–564. 36 indexed citations
12.
Žarić, Gojko, João Correia, Gorka Fraga González, et al.. (2016). Altered patterns of directed connectivity within the reading network of dyslexic children and their relation to reading dysfluency. Developmental Cognitive Neuroscience. 23. 1–13. 28 indexed citations
13.
Tijms, Jurgen, et al.. (2014). Brain-potential analysis of visual word recognition in dyslexics and typically reading children. Frontiers in Human Neuroscience. 8. 474–474. 40 indexed citations
14.
Žarić, Gojko, Gorka Fraga González, Jurgen Tijms, et al.. (2014). Reduced Neural Integration of Letters and Speech Sounds in Dyslexic Children Scales with Individual Differences in Reading Fluency. PLoS ONE. 9(10). e110337–e110337. 59 indexed citations
15.
Snellings, Patrick, et al.. (2013). A lab-controlled simulation of a letter–speech sound binding deficit in dyslexia. Journal of Experimental Child Psychology. 115(4). 691–707. 54 indexed citations
16.
Tijms, Jurgen, et al.. (2012). The incidence of prematurity or low birth weight for gestational age among children with dyslexia. Acta Paediatrica. 101(11). e526–8. 3 indexed citations
17.
Snellings, Patrick, et al.. (2011). Specifying theories of developmental dyslexia: a diffusion model analysis of word recognition. Developmental Science. 14(6). 1340–1354. 36 indexed citations
18.
Tijms, Jurgen, et al.. (2009). Reading fluency and Dyslexia: Innovative developments in the role of Associative learning and Repetitive exposure in skill acquisition. UvA-DARE (University of Amsterdam). 3 indexed citations
19.
Tijms, Jurgen. (2004). A Process‐Oriented Evaluation of a Computerised Treatment for Dyslexia. Educational Psychology. 24(6). 767–791. 14 indexed citations
20.
Tijms, Jurgen, et al.. (2004). A computerized treatment of dyslexia: Benefits from treating lexico-phonological processing problems. Dyslexia. 11(1). 22–40. 25 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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