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Educational Technology and Assessment

Educational Technology and Assessment is a research topic within Information Systems. Science Explorer counts 35k research works in it since 1950. 9.7% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the application of fuzzy logic, data mining, genetic algorithms, and concept mapping in educational assessment, including student performance evaluation, intelligent tutoring systems, adaptive learning, and diagnosis and remedial learning. The use of fuzzy logic for evaluating students' answerscripts and learning achievement is a prominent focus, along with the development of automatic examination paper generation systems and web-based testing approaches.

  • Fuzzy Logic
  • Educational Assessment
  • Intelligent Tutoring Systems
  • Adaptive Learning
  • Concept Mapping
  • Student Performance Evaluation
  • Diagnosis and Remedial Learning
  • Data Mining
  • Genetic Algorithms
  • Web-Based Testing
Research works
35k
fractional, since 1950
In the world top 10%
3.4k
per year above
Top-10% rate
9.7%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+64%
the tick is no change
Largest producer
China
55% of the 10 largest, 2022-now
Educational Technology and Assessment

Which countries lead Educational Technology and Assessment research?

By volume, China and Indonesia publish the most (2.1k and 502 works in 2022-now).

By volume, 2022-now

  1. 1 China 2.1k works
  2. 2 Indonesia 502 works
  3. 3 India 377 works
  4. 4 United States 255 works
  5. 5 Japan 122 works
  6. 6 Malaysia 116 works
  7. 7 Türkiye 86 works
  8. 8 Vietnam 82 works
  9. 9 Philippines 79 works
  10. 10 ?? 70 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.

China: 55.2%Indonesia: 13.3%India: 10.0%United States: 6.8%6 others listed: 14.7%55%largest
China2,079 · 55.2%Indonesia502 · 13.3%India377 · 10.0%United States255 · 6.8%6 others listed555 · 14.7%

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

Which institutions lead Educational Technology and Assessment research?

By volume in 2022-now, Shandong Institute of Commerce & Technology publishes the most Educational Technology and Assessment research, followed by China West Normal University and Chinese Academy of Sciences.

Who are the leading researchers in Educational Technology and Assessment?

The most-cited researchers publishing on Educational Technology and Assessment include Kai You Wang, Francisco Herrera and Philip S. Yu.

  1. 1 Kai You Wang China 224k citations
  2. 2 Francisco Herrera Spain 141k citations
  3. 3 Philip S. Yu United States 141k citations

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

What are the most cited papers in Educational Technology and Assessment?

The most cited paper in Educational Technology and Assessment is "The partial least squares approach for structural equation modeling." (Wynne W. Chin, 1998), with 11,711 citations. Next come "Principles and practice of structural equation modeling, 2nd ed." (6,120) and "Principles and practice of structural equation modeling, 3rd ed." (5,310).

Most cited papers
#PaperReleasedCitations
1 The partial least squares approach for structural equation modeling. Wynne W. Chin 1998 11,711
2 Principles and practice of structural equation modeling, 2nd ed. Rex B. Kline 2005 6,120
3 Principles and practice of structural equation modeling, 3rd ed. Rex B. Kline 2011 5,310
4 Principles and practice of structural equation modeling, 4th ed. Rex B. Kline 2016 3,416
5 Feature selection for classification Manoranjan Dash, Hua Liu · Intelligent Data Analysis 1997 2,613
All 100 most cited papers, with filters and sorting

Where is Educational Technology and Assessment research done?

The largest centres of Educational Technology and Assessment research in 2022-now are Beijing (China), Wuhan (China), Guangzhou (China) and Jinan (China). Among places with at least 20 works in it, it is an unusually large share of all research in Nanchong.

Largest cities, 2022-now

  1. 1 BeijingChina 202 works
  2. 2 WuhanChina 98 works
  3. 3 GuangzhouChina 92 works
  4. 4 JinanChina 84 works
  5. 5 ShanghaiChina 82 works
  6. 6 Xi'anChina 71 works
  7. 7 ChengduChina 69 works
  8. 8 NanjingChina 57 works
  9. 9 ChongqingChina 55 works
  10. 10 JakartaIndonesia 52 works

Where it is the local speciality

  1. NanchongCN · 20.0 works17×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Educational Technology and Assessment than the world average.

See Educational Technology and Assessment on the map

Where is the best place to study Educational Technology and Assessment?

Among universities, judged by research, Amrita Vishwa Vidyapeetham, Binus University and National University of Malaysia 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%20%40%mean 17.72%fractional works in this field (log) →share of work in the world top 10% →Amrita Vishwa Vidyap…National University …Binus UniversityBeijing Normal Unive…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Amrita Vishwa VidyapeethamIndia 73.944.6%5.9×12 +238.1%
2Binus UniversityIndonesia 57.519.9%6.9×15 +266.3%
3National University of MalaysiaMalaysia 53.621.1%3.1×8 -4.1%
4Beijing Normal UniversityChina 52.413.5%4.5×14 +29.7%
5Vietnam National University Ho Chi Minh CityVietnam 52.123.2%5.5×10 +110.5%
6State University of MalangIndonesia 51.418.5%3.7×14 +98.1%
7Shandong Institute of Commerce & TechnologyChina 50.90.1%142.3×25 +1096.7%
8Central China Normal UniversityChina 49.012.2%11.5×12 +33.9%
9Saveetha UniversityIndia 48.324.1%2.6×10 -
10China West Normal UniversityChina 47.40.0%43.3×20 +189.2%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Educational Technology and Assessment, country by country

Is Educational Technology and Assessment research growing?

Output in 2022-2025 was 64% higher than in 2018-2021, peaking in 2011. The fastest-growing topics are Educational Technology and Assessment.

still counting19801990200020102020
grewheldshrank

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

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Educational Technology and Assessment as a percentage of every work published that year, 0.028% in 2024.

still counting0.050%0.10%Educational Technology and Assessment0.021% in 202519801990200020102020

Fractional works of Educational Technology and Assessment over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Educational Technology and Assessment10.1% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

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.

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