Shawn Betts

422 citations
25 papers · 282 · h-index 11

Impact in

Papers in

Shawn Betts

22 papers receiving 270 citations

Peers

Shawn Betts
Comparison fields: 5 of 55
  • Statistics and Probability 78
  • Developmental and Educational Psychology 101
  • Cognitive Neuroscience 128
  • Experimental and Cognitive Psychology 79
  • Artificial Intelligence 103
Replace Hee Seung Lee with:
Hee Seung Lee South Korea
Rebecca Boncoddo United States
Moira Rose Dillon United States
Thomas G. Holzman United States
Aryn Pyke United States
Irina V. Kapler Canada
David W. Braithwaite United States
Pablo Dartnell Chile
Otto Loberg Finland
Anselm Strohmaier Germany
Shawn Betts relative to Hee Seung Lee South Korea Hee Seung Lee's profile →
Citations per field
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Citations per year

Countries citing papers authored by Shawn Betts

Since Specialization
Citations

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

Fields of papers citing papers by Shawn Betts

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Shawn Betts, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shawn Betts Line = papers co-authored together Shawn Betts links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201050
2 201042
3 200935
4 201126
5 201921
6 201613
7 201212
8 201510
9 201510
10 201510
11 201410
12 20139
13 20149
14
When Does Provision of Instruction Promote Learning
20114
15 20214
16 20214
17 20213
18 20203
19 20232
20 20182

About Shawn Betts

Shawn Betts is a scholar working on Artificial Intelligence, Developmental and Educational Psychology, Cognitive Neuroscience, Experimental and Cognitive Psychology and Statistics and Probability, having authored 25 papers that have together received 282 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (10 papers), Visual and Cognitive Learning Processes (8 papers), Innovative Teaching and Learning Methods (6 papers), Cognitive and developmental aspects of mathematical skills (6 papers), Neural and Behavioral Psychology Studies (5 papers), Child and Animal Learning Development (5 papers), Cognitive Science and Mapping (4 papers) and Neuroscience, Education and Cognitive Function (4 papers). The work is most often cited by research in Statistics and Probability (78 citations), Developmental and Educational Psychology (101 citations), Cognitive Neuroscience (128 citations), Experimental and Cognitive Psychology (79 citations) and Artificial Intelligence (103 citations). Shawn Betts has collaborated with scholars based in United States, South Korea and Switzerland. Frequent co-authors include John R. Anderson, Jon M. Fincham, Jennifer L. Ferris, Hee Seung Lee, Daniel Bothell, Christian Lebière, Aryn Pyke, Dan Bothell, Hee Seung Lee and Jian Yang. Their work appears in journals such as Cognitive Science, Cognitive Affective & Behavioral Neuroscience, PLoS ONE, Memory & Cognition and IEEE Intelligent Systems.

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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