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Visual and Cognitive Learning Processes

Visual and Cognitive Learning Processes is a research topic within Experimental and Cognitive Psychology. Science Explorer counts 14k research works in it since 1950. 26.3% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on Cognitive Load Theory and its application in multimedia learning, instructional design, and educational technology. It explores strategies to reduce cognitive load, optimize learning from multimedia content, and enhance instructional efficiency. The research also delves into the use of eye-tracking technology, pedagogical agents, and self-explanation prompts to improve learning outcomes.

  • Cognitive Load Theory
  • Multimedia Learning
  • Instructional Design
  • Cognitive Architecture
  • Interactive Multimedia
  • Educational Technology
  • Learning Efficiency
  • Eye-Tracking Research
  • Pedagogical Agents
  • Self-Explanation
Research works
14k
fractional, since 1950
In the world top 10%
3.8k
per year above
Top-10% rate
26.3%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+12%
the tick is no change

Which countries lead Visual and Cognitive Learning Processes research?

By volume, the United States and Germany publish the most (477 and 241 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 477 works
  2. 2 Germany 241 works
  3. 3 China 221 works
  4. 4 United Kingdom 89 works
  5. 5 Indonesia 77 works
  6. 6 Japan 69 works
  7. 7 Australia 57 works
  8. 8 Canada 56 works
  9. 9 Türkiye 54 works
  10. 10 France 50 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 34.3%Germany: 17.3%China: 15.9%United Kingdom: 6.4%6 others listed: 26.1%34%largest
United States477 · 34.3%Germany241 · 17.3%China221 · 15.9%United Kingdom89 · 6.4%6 others listed363 · 26.1%

Shares of the rows listed above, not of the whole node.

Which institutions lead Visual and Cognitive Learning Processes research?

By volume in 2022–2025, Central China Normal University publishes the most Visual and Cognitive Learning Processes research, followed by Beijing Normal University and Utrecht University.

By volume, 2022–2025

  1. 1 Central China Normal University China 15 works
  2. 2 Beijing Normal University China 11 works
  3. 3 Utrecht University Netherlands 10 works
  4. 4 Shaanxi Normal University China 10 works
  5. 5 National Taiwan Normal University Taiwan 10 works
  6. 6 Technical University of Munich Germany 10 works
  7. 7 UNSW Sydney Australia 10 works
  8. 8 University of Duisburg-Essen Germany 9 works
  9. 9 Ludwig-Maximilians-Universität München Germany 8 works
  10. 10 Pennsylvania State University United States 7 works

Who are the leading researchers in Visual and Cognitive Learning Processes?

The most-cited researchers publishing on Visual and Cognitive Learning Processes include Richard E. Mayer, Ann L. Brown and Alan Baddeley.

  1. 1 Richard E. Mayer 4.7k citations
  2. 2 Ann L. Brown 3.5k citations
  3. 3 Alan Baddeley 2.9k citations
  4. 4 John Sweller 2.9k citations
  5. 5 S. S. Stevens 2.9k citations
  6. 6 Walter Kintsch 2.6k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Visual and Cognitive Learning Processes research done?

The largest centres of Visual and Cognitive Learning Processes research in 2022–2025 are Beijing (China), Wuhan (China), Munich (Germany) and Taipei (Taiwan).

Largest cities, 2022–2025

  1. 1 Beijing China 32 works
  2. 2 Wuhan China 25 works
  3. 3 Munich Germany 22 works
  4. 4 Taipei Taiwan 21 works
  5. 5 Tokyo Japan 20 works
  6. 6 Sydney Australia 18 works
  7. 7 Shanghai China 18 works
  8. 8 London United Kingdom 18 works
  9. 9 Xi'an China 16 works
  10. 10 Paris France 15 works
See Visual and Cognitive Learning Processes on the map

Where is the best place to study Visual and Cognitive Learning Processes?

Among universities, judged by research, Central China Normal University, Utrecht University and UNSW Sydney score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%25%50%mean 38.675%fractional works in this node (log) →share in the world top 10% →Central China Normal University: 15, 32.5%Utrecht University: 10, 33.1%UNSW Sydney: 10, 59.5%Shaanxi Normal University: 10, 37.2%University of Duisburg-Essen: 9, 39.5%Beijing Normal University: 11, 34.7%Technical University of Munich: 10, 40.9%National Taiwan Normal University: 10, 32.0%UNSW SydneyShaanxi Normal Unive…Utrecht UniversityCentral China Normal…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1Central China Normal University China 53.032.5%30.1×15
2Utrecht University Netherlands 51.933.1%9.8×10 +141.2%
3UNSW Sydney Australia 43.159.5%5.8×10 -59.1%
4Shaanxi Normal University China 41.937.2%18.1×10
5University of Duisburg-Essen Germany 40.339.5%14.1×9 +1.4%
6Beijing Normal University China 39.034.7%7.9×11 +162.7%
7Technical University of Munich Germany 38.340.9%6.1×10 +213.6%
8National Taiwan Normal University Taiwan 36.932.0%44.3×10 +0.3%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Visual and Cognitive Learning Processes research growing?

Output in 2018–2022 was 12% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Visual and Cognitive Learning Processes.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.