Ray S. Perez

866 citations
24 papers · 506 indexed · h-index 11

Ray S. Perez

22 papers receiving 447 citations

Peers

Ray S. Perez
Comparison fields: 5 of 121
  • Computer Science Applications 50
  • Developmental and Educational Psychology 109
  • Neurology 63
  • Developmental Neuroscience 28
  • Experimental and Cognitive Psychology 58
Replace Fengji Geng with:
Fengji Geng China
Douglas Markant United States
Stefano Sandrone United Kingdom
Ting‐Kuang Yeh Taiwan
Gaëlle Molinari Switzerland
Daniel Klement Czechia
Demis Basso Italy
Alex Mitchell Singapore
Shu-Hsien Huang Taiwan
Reid Laughlin Skeel United States
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Citations per year

Countries citing papers authored by Ray S. Perez

Since Specialization
Citations

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

Fields of papers citing papers by Ray S. Perez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ray S. Perez. 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 Ray S. Perez. The network helps show where Ray S. Perez may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Ray S. Perez, 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 Ray S. Perez Line = papers co-authored together Ray S. Perez links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20211
2 201813
3
Tetris as Research Paradigm: An Approach to Studying Complex Cognitive Skills
20141
4 201342
5 201321
6 201317
7 201340
8 2013158
9 200857
10 20052
11 20044
12 19931
13
Using artificial intelligence in education: computer-based tools for instructional development
19904
14
Desalcoholización de vino mediante destilación en columna. Ensayos previos
19892
15 19884
16 19886
17 19887
18
Intelligent CAI: Old wine in new bottles, or a new vintage?
198727
19 19864
20
A Handbook for Evaluating ESEA Title VII Bilingual Education Programs.
19821

About Ray S. Perez

Ray S. Perez is a scholar working on Applied Psychology, Human Factors and Ergonomics and Developmental and Educational Psychology, having authored 24 papers that have together received 506 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (8 papers), Human Resource Development and Performance Evaluation (4 papers), AI-based Problem Solving and Planning (4 papers), Surgical Simulation and Training (3 papers), Visual and Cognitive Learning Processes (2 papers), Online and Blended Learning (2 papers), Human-Automation Interaction and Safety (2 papers) and Innovative Teaching and Learning Methods (2 papers). The work is most often cited by research in Computer Science Applications (50 citations), Developmental and Educational Psychology (109 citations) and Neurology (63 citations). Ray S. Perez has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Harold F. O’Neil, Alfonso Araque, R. Douglas Fields, Maiken Nedergaard, Klaus‐Armin Nave, Gary Lynch, Heidi Johansen‐Berg, Hiroaki Wake, Terrence J. Sejnowski and Eva L. Baker. Their work appears in journals such as Computers in Human Behavior, Instructional Science, Human Factors The Journal of the Human Factors and Ergonomics Society, The Neuroscientist and International Journal of STEM Education.

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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