This study examines 568 documents indexed in Scopus to reveal the evolution and current status of AI-enabled fuzzy logic in education. The study shows that scientific production in this field has increased significantly since 2013, with the highest productivity in 2023 and 2024. China, Greece, Turkey, India, and the USA are identified as the most active countries, with Greece standing out in terms of both productivity and citation impact. Collaborative authorship is highest, with an average of 2.88 authors per document and an international collaboration rate of 14.26%. Leading researchers such as Maria Virvou and Konstantina Chrysafiadi have been the most contributing authors in this field. Frequently used keywords (such as fuzzy logic, students, education, and AI) indicate a strong emphasis on adaptive learning, intelligent systems, and student-centered pedagogies. Despite its popularity, challenges remain regarding implementation, teacher preparation, and ethical considerations. This analysis, global trends, and key contributors will serve as a guide for future research on AI-fuzzy logic integration. Another result obtained from the research is that the most relevant source for the field is “LECTURE NOTES IN COMPUTER SCIENCE (INCLUDING SUBSERIES LECTURE NOTES IN ARTIFICIAL INTELLIGENCE AND LECTURE NOTES IN BIOINFORMATICS”.
Today, Artificial Intelligence (AI) has begun to be used at all levels of education from preschool to
higher education and lifelong learning, and has become indispensable for individuals at all levels [
Artificial intelligence (AI) is having a significant impact on our lives, from improving education,
healthcare and transportation to transforming the way we work and learn [
In the study that evaluates the opportunities and risks of artificial intelligence in higher education
and examines the efects of GenAI tools (ChatGPT, Codex, etc.) on teaching, learning, and research,
it is clearly stated that Artificial intelligence ofers significant application potential in areas such as
personalized learning, evaluation, data analytics, and academic success [
In the study, which examined academicians’ self-eficacy, perceived benefits, dificulties encountered,
usage situations, and professional development needs regarding artificial intelligence, four diferent
faculty member profiles were identified (optimistic, critical, critical reflective, and neutral), and the
lack of articfiial intelligence literacy stood out as one of the biggest challenges. Increasing equality in
education was seen as the most important benefit. The findings indicate that supporting services need
to be developed for digital transformation [
Another study examining undergraduate students’ tendencies to adopt artificial intelligence based
on the UTAUT model aims to investigate the efects of performance expectation, social influence, and
supportive conditions on attitudes and behavior [
In another study advocating the use of ethical artificial intelligence in higher education, AI teachers
examine the interaction between human instructors and students with Third Generation Activity
Theory [
Another study examining the adoption of artificial intelligence applications in universities in India
found findings based on technology acceptance models, showing that self-eficacy, perceived usefulness,
organizational support, and risk perception are important in understanding AI integration [
By examining the perception and usage levels of university students towards productive artificial
intelligence such as ChatGPT, it was found that the students had high knowledge, positive attitudes,
and a strong intention to use. However, it has been revealed that they have a moderate level of concern
about artificial intelligence [
This study was conducted to reveal the scientific production structure of AI and fuzzy logic in education. To achieve the research purpose, the following questions were sought: 1. What is the basic information on artificial intelligence-supported fuzzy logic studies in education? 2. What is the distribution of annual scientific production in this field? 3. How has the publication output of countries changed over time? 4. Who are the most relevant authors in the field? 5. What are the most frequently used keywords in the studies? 6. What are the most relevant academic sources (journals) for this field?
This study aims to determine the distribution of AI-supported Fuzzy Logic studies in education by year,
the most productive countries and their citations in the field, the most relevant authors in the field,
and the most frequently used words. The research data were obtained from the Scopus database1 on
June 17, 2025, using the keywords “AI* AND Fuzzy Logic in Education*”. The search was limited to the
“article title, abstract, keywords” in the search section of the Scopus database. In this context, studies
that included the phrases “AI* AND Fuzzy Logic in Education” in the title, abstract, and keywords of
documents published in Scopus were included in the analysis. In the analysis of the data, Bibliometrix,
which is an open-source tool for scientific measurement and quantitative research in bibliometrics,
including bibliometric analysis methods, was preferred. Developed by Aria and Cuccurullo [
Main information about artificial intelligence-supported Fuzzy Logic studies in education in the Scopus database is given in Table 1. 1Scopus https://www.scopus.com/home.uri 2Bibliometrix https://www.bibliometrix.org/home/index.php/layout/bibliometrix 3Biblioshiny https://www.bibliometrix.org/home/index.php/layout/biblioshiny
As seen in Table 1, there are 568 documents in the Scopus database regarding artificial intelligencesupported Fuzzy Logic studies in education. The studies were published in a total of 390 sources.
When the authors’ quantitative data were examined, it was determined that a total of 1440 researchers published in this field, and 65 researchers were authors of single-authored documents. When the collaboration between authors was examined, it was determined that 67 documents had a single author, the number of co-authors per document was 2.88, and international co-authorship was 14.26%. The ifndings show that researchers working in this field attach importance to collaborative studies.
The distribution of artificial intelligence-supported Fuzzy Logic studies in education published in the Scopus database by year is given in Figure 1.
As seen in Figure 1, studies on Fuzzy Logic supported by artificial intelligence in education started in 1988, and only one study was included in the Scopus database in this year. There were no studies published in this field in the Scopus database in 1989, 1990, and 1991. It was determined that studies on Fuzzy Logic supported by artificial intelligence in education started to be published in the Scopus database again in the 2000s, and that the studies increased quantitatively as of 2013. The most productive years were 2023 with 63 documents and 2024 with 61 documents. It is seen that 37 documents were published in the Scopus database in 2025. However, it is thought that this number will increase towards the end of the year.
The years in which artificial intelligence-supported Fuzzy Logic studies in education were published and the distribution of publications by year are detailed in Table 2.
The findings regarding the production over time of the countries where artificial intelligence-supported Fuzzy Logic studies in education are published in the Scopus database are given in Figure 2.
The 568 documents analyzed were conducted in “China”, “Greece”, “India”, “Turkey” and “USA”. It was determined that the artificial intelligence-supported Fuzzy Logic studies in education published in the Scopus database were conducted in the 5 countries shown in the graph between 1992-2023. When the production years of the countries were examined, it was determined that a limited number of studies were conducted only in the USA in the 1990s and that quantitative production in 5 countries started in the 2000s. In particular, it can be said that there was an increase in the scientific production of the countries in 2015 and after, and that the studies became more intense after 2023. The countries that received the most citations for artificial intelligence-supported Fuzzy Logic studies are given in Table 3. Country GREECE CHINA TURKEY SPAIN SINGAPORE
TC 869 699 469 394 316
The study also aimed to determine the most productive and most cited countries in terms of AIsupported Fuzzy Logic studies in education. The findings reveal the reputation and influence of these countries in the field of AI-supported Fuzzy Logic.
The study also aimed to determine the top 10 researchers who are most interested in the field of artificial intelligence-supported Fuzzy Logic. The findings of the research are given in Table 4.
When Table 4 is examined, the first 10 most relevant researchers in the field of artificial intelligence who supported Fuzzy logic in education were determined as “VIRVOU, MARIA”, who has the most studies and 13 studies published in the Scopus database. The other 2 most relevant researchers with 11 articles each are “CHRYSAFIADI, KONSTANTINA” and “TROUSSAS, CHRISTOS”. Another most relevant researcher with 10 documents in the Scopus database was determined as “SGOUROPOULOU, CLEO”. The other most relevant researchers in the field were determined as “HAGRAS, HANI” ( = 9), “KROUSKA, AKRIVI” ( = 9), “ALMOHAMMADI, KHALID” ( = 6), “DIAS, SOFIA B.” ( = 6), “PAPADIMITRIOU, SPYROS” ( = 6), and “BARRÓN-ESTRADA, M.L.” ( = 5). It is believed that the studies published by the aforementioned authors will provide basic resources and guidance to researchers who plan to conduct studies on Fuzzy Logic supported by artificial intelligence in the field of education.
The distribution of the most frequently used words in the 568 documents analyzed in the study is given in Table 5.
As seen in Table 5, the most frequently used keywords by researchers in their studies were determined as “fuzzy logic” (Occurrences=348), “students” (Occurrences=120), “computer circuits” (Occurrences=115), “computer aided instruction” (Occurrences=103), “learning systems” (Occurrences=91), “education” (Occurrences=83), “artificial intelligence” (Occurrences=78), “fuzzy-logic” (Occurrences=76), “educa-tion computing” (Occurrences=74) and “teaching” (Occurrences=71). The findings obtained will shed light on researchers who will conduct studies in this field, especially during the literature review process. Researchers will be able to easily access efective studies in this field by using the most frequently used keywords.
The distribution of the sources where the most published studies on artificial intelligence-supported Fuzzy Logic in education are given in Table 6.
As seen in Table 6, the source with the most publications in this field was determined as “LECTURE NOTES IN COMPUTER SCIENCE (INCLUDING SUBSERIES LECTURE NOTES IN ARTIFICIAL INTELLIGENCE AND LECTURE NOTES IN BIOINFORMATICS)” with 23 articles. The other source with the most publications was “COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE” ( = 15), and the other sources were as follows, respectively; “LECTURE NOTES IN NETWORKS AND SYSTEMS” ( = 12), “COMPUTER APPLICATIONS IN ENGINEERING EDUCATION” ( = 10), “ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING” ( = 9), “EXPERT SYSTEMS WITH APPLICATIONS” ( = 8), “IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS” ( = 8), “JOURNAL OF INTELLIGENT AND FUZZY SYSTEMS” ( = 7), “CEUR WORKSHOP PROCEEDINGS” and “PLOS ONE” ( = 6).
The study examines 568 documents indexed in Scopus to reveal the evolution and current status of
AI-supported fuzzy logic in education. The study shows that the studies has increased significantly
since 2013, with the highest productivity in 2023 and 2024. China, Greece, Turkey, India, and the USA
are the most active countries, with Greece standing out in terms of both productivity and citation
impact. Collaborative authorship is the highest, with an average of 2.88 authors per document and an
international collaboration rate of 14.26%. Leading researchers such as Maria Virvou and Konstantina
Chrysafiadi have been the authors who contributed the most to this field. The most used keywords
(such as fuzzy logic, students, education, and AI) indicate the need to focus on adaptive learning,
intelligent systems, and student-centered pedagogies. Chrysafiadi and Virvou [