this is a dissertation final presentation.

1. ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: A
BIBLIOMETRIC ANALYSIS OF RESEARCH TRENDS
Presented by
Subrata Khan
Class Roll No. – 002101503017
Exam Roll No. – MPEDU23417
Reg. No. – 142119 of 2017-18
Supervised By
Dr. Lalit Lalitav Mohakud
Assistant Professor, Department Of Education
Jadavpur University, Kolkata

2. INTRODUCTION
The 21st century is frequently seen as the technological age. Today, technology is
crucial to our life.
Higher education refers to tertiary education leading to advanced learning and the
award of an academic degree (Brennan & Williams, 2008).
The evolution of technology in education has been a transformative journey that has
significantly impacted teaching and learning.
Over the last few years, the entire society has been living a paradigmatic change due
to the run of innovations related to Artificial Intelligence (AI) (Lazzeretti et al.,
2022).
 According to McCarthy et al. (2006), the term "artificial intelligence" was first used
in 1956.
Artificial Intelligence (AI), which aims to create machines that can perform
activities that typically require human intelligence, has its roots in the middle of the
20th century (Ensmenger, 2012).
Artificial Intelligence (AI) has a significant and growing relevance in higher
education. Its influence may be observed in different aspects of the educational
system, such as improved teaching, learning, and administrative processes.

3. RATIONALE OF THE STUDY
• It is evident that though many research studies have been conducted in
these fields, there are some gaps in the existing literature that need
special attention from researchers.
• Only a few studies attempted to comprehensively explore the concept
and dimensions of AI.
• Studies still need to explore the research trends of AI in higher education.
• Most of the studies were conducted abroad, but no such study was found
in India. This type of results of the previous studies aroused some
conflicts in the researcher's mind.
• As a result, a few questions arose in the researcher's mind.
• The present research trends, the existing research gaps, and the raised
questions evoked the researcher to conduct a comprehensive study to
explore research trends of AI in higher education.

4. STATEMENT OF THE PROBLEM
Based on the above rationale and the identified research gaps,
the problem for the present study can be stated as
“Artificial Intelligence in Higher Education: A Bibliometric
Analysis of Research Trends”

5. OPERATIONAL DEFINITION
Artificial Intelligence: Artificial intelligence (AI) refers to
the development of computer systems that are capable of
doing tasks that usually require human intelligence, such as
problem-solving, data learning, pattern recognition, and
judgement.
Higher Education: Higher education refers to post-
secondary educational institutions and programs offering
advanced learning opportunities beyond high school. It
includes colleges and universities where students pursue
undergraduate and postgraduate degrees, gaining
specialized knowledge and skills for their chosen careers.
Bibliometric: Bibliometrics is a statistical analysis of
books, articles, and other publications used to measure the
productivity of individuals/research teams, institutions, and
countries to identify global research networks and map the
development of new interdisciplinary fields (OECD Glossary

6. RESEARCH QUESTIONS
1. What are the current research trends on AI in HE?
2. What are the leading, influential, impactful journals,
articles, authors, and institutions on AI in HE based
on the number of publications and citations?
3. What are the most influential author’s keywords and
trending topics in the research area of AI in HE?
4. What is the structure of the network among authors
and co-authors in the field of AI in HE?
5. Country-wise, what is the structure of the document
network and co-authors' collaboration in the field of
AI in HE?

7. OBJECTIVES OF THE STUDY
1. To analyze the publication trends of articles between 2014-2023 on AI in HE;
2. To investigate the trends of published documents by subject area on AI in HE;
3. To analyze the publication trends among countries on AI in HE;
4. To identify the influential and impactful authors on AI in HE based on the number of
publications and citations;
5. To find out the leading institutions on AI in HE based on the number of publications and
citations;
6. To investigate the impactful articles on AI in HE based on the number of citations;
7. To find out the key journals on AI in HE based on the number of publications and citations;
8. To explore the network of the author’s keywords currently trending in the field of AI in HE.
9. To explore the network of the most influential authors in the field of AI in HE.
10. To explore the network of the most influential countries in the field of AI in HE.

8. DELIMITATIONS OF THE STUDY
1. The primary variable considered in the study was artificial intelligence
(AI) in higher education, focusing on its conceptualization and
measurement.
2. The study sample comprised 1,772 peer-reviewed articles selected for
analysis.
3. Only the Scopus database was used for collecting data.
4. The study focused on articles published between 2014 and 2023 to
capture recent research trends.
5. Only journal articles and review publications were selected for
analysis.
6. Limit the study to publications available only in the English language.
7. Only education-related AI keywords were used to collect data, such as

9. METHODOLOGY OF THE STUDY

10. METHODOLOGY OF THE STUDY
• Research Method: Bibliometric Analysis Method
• Keywords, Database and search String :
Identification of Keywords Identification of
Databases
Artificial intelligence, Machine learning, deep
learning, Natural language processing,
Intelligent tutoring system, Education,
teaching and learning, Pedagogy, Curriculum,
Instruction, assessment, Evaluation, Academic
achievement, higher education, Tertiary,
University, College
Scopus
Search String: (“Artificial intelligence” OR “Machine learning” OR
“deep learning” OR “Natural language processing” OR “Intelligent
tutoring system”) AND (“education*” OR “teaching and learning” OR
“Pedagogy” OR “curriculum” OR “instruction*” OR “assessment” OR
“evaluation” OR “Academic achievement”) AND (“higher educat*” OR
“Tertiary” OR “universit*” OR “College”).

11. Inclusion and Exclusion Criteria
Table: Inclusion and Exclusion Criteria
Criterion Inclusion Exclusion
Year of
Publication
Between 2014 to September 2023 Before 2014
Subject Area Social science, Arts and
Humanities, Psychology,
Multidisciplinary
Engineering, Computer Science,
Environmental Science, Nursing,
Business Management, Energy, etc.
Document
Type
Article and Review Conference paper, Book chapter, Book,
Conference review, Erratum, Note, etc.
Publication
stage
Final Article in press
Language English Non-English

12. DATA COLLECTION PROCEDURES
Table: Data Collection Procedures
Criteria Include Exclude
("Artificial intelligence" OR "Machine learning" OR "deep learning" OR "Natural
language processing" OR "Intelligent tutoring system") AND ("education*" OR
"teaching and learning" OR "Pedagogy" OR "curriculum" OR "instruction*" OR
"assessment" OR "evaluation" OR "Academic achievement") AND ("higher educat*"
OR "Tertiary" OR "universit*" OR "College")
14,484 --
Year of publication (2014 - 2023) 11,986 2,498
Subject area: Social science, Arts and Humanities, Psychology, Multidisciplinary 3,336 8,650
Document type: Article and Review 2,047 1,289
Publication stage: Final 1,897 150
Language: English 1,781 116
Erroneous records refinement 1,772 9
Total (included studies) 1,772 --

13. DATA EXTRACTION
Table 4.3: Bibliometric Characteristics Spreadsheet Headings
Author’s
(s)
Document
s
Title
Year Source
Title
Citatio
n
Count
Affiliatio
n
Geographic
al
Area
Abstract
Keyword
s
Author
Keyword
s
Database
Keyword
s
 Final selection of 1,772 studies from the Scopus database,
 Exported the dataset as a CSV file (MS Excel spreadsheet),
 This Excel spreadsheet encompassed a comprehensive range of study details,
 An illustrative example of the data extraction Excel spreadsheet is provided in Table.

14. Software, Data Management, And Data
Cleaning
Software Data Management Data Cleaning
• Excel
• VOSviewer
Data were organized into
manageable spreadsheets to allow
proper analysis
checked for duplicate
• Analysis, Interpretation, and Visualization:
• Performance Analysis
• Network Analysis and Mapping

15. RESULTS OF THE STUDY

16. 0
50
100
150
200
250
300
350
400
450
2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
71
55 51
79 89
152
210
273
407
385
No.
of
documents
Years
Publications Trends
Publication Trends of Articles Between 2014 and 2023

17. Distribution Of Documents By Subject Area

18. 0
100
200
300
400
UNITED STATESCHINA
UNITED KINGDOM
AUSTRALIA SPAIN CANADASAUDI ARABIA
GERMANY TURKEY INDIA
352
227
139
120 110
75 62 59 57 52
NO.
of
documents
Countries
Publications by Countries
Top 10 Countries with the Most Publications

19. Top 15 Authors With The Most Publications
4
4
4
4
4
4
4
4
5
5
5
5
5
6
14
0 2 4 6 8 10 12 14 16
BANERES, D.
ESLAVA-CERVANTES, A.L.
FOMUNYAM, K.G.
ILIĆ, M.P.
JESSOP, T.
KULETO, V.
MCNAMARA, D.S.
OUYANG, F.
AZEVEDO, R.
FAN, J.
GUERRERO-ROLDÁN, A.E.
LEVINE, R.A.
NUANKAEW, P.
ZHANG, F.
SALAS-RUEDA, R.A.
No. of documents
Authors
Top 15 Leading Authors

20. The Top 15 Institutions With The Most Publications
9
9
9
10
10
11
11
11
11
12
13
14
14
17
18
0 2 4 6 8 10 12 14 16 18 20
UNIVERSITAT OBERTA DE CATALUNYA
KING ABDULAZIZ UNIVERSITY
THE HONG KONG POLYTECHNIC UNIVERSITY
CHINESE UNIVERSITY OF HONG KONG
MONASH UNIVERSITY
ARIZONA STATE UNIVERSITY
STANFORD UNIVERSITY
DEAKIN UNIVERSITY
UNIVERSITY OF SOUTH AUSTRALIA
THE UNIVERSITY OF QUEENSLAND
UNIVERSIDAD DE GRANADA
THE UNIVERSITY OF HONG KONG
UNIVERSITY OF ALBERTA
TECNOLÓGICO DE MONTERREY
UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO
No. of documents
Institutions
Top 15 Leading Institutions

21. Co-occurrence Analysis With Author Keywords

22. Cluster Analysis
CLUSTER DIMENSION TERM
1-Red Teaching and learning
perspective
Active learning, Blended learning, Data Science, Educational
technology, Flipped classroom, Higher education, Learning,
Pedagogy, Student engagement , Teaching, Technology,.
2-Green Advance Educational Aids Ai, Artificial intelligence, Artificial intelligence(ai),
Assessment, Chatbot, Chatgpt, Education, Ethics, Nurel
language processing, Students.
3-Blue Learning analytics Big data, Classification, Covid-19, Data mining, Educational
data mining, Learning analytics, Machine learning,
Prediction, Random forest.
4-Yellow Self-paced learning e-learning, Feedback, Intelligent tutoring system, Intelligent
tutoring systems, Interactive learning environment, Online
learning, Self-regulated learning
5-Purple Learning enhancement Academic performance, Deep learning, Engineering
education, Learning approaches, Surface learning.

23. Co-citation Network Analysis With Authors

24. Co-authorship Analysis With Countries

25. Bibliographic Coupling Analysis With
Countries

26. THE MAJOR FINDINGS
Analysis Finding
Highest number of publications 2022
The most common subject area Social Science (42.4%)
Most productive country
(publication and citation)
USA (352)
Most leading Author (publication) Salas-Rueda, R.A. (14)
Most leading and Influential
Authors (Citation)
Zawacki-Richter O.; Marín V.I.
; Bond M. ; Gouverneur F.
(524)
Most leading Institution
(publication)
Universidad Nacional
Autónoma de México, Mexico
(18)
Most Influential Institution
(Citation)
University of Oldenburg,
Germany (524)
Most leading journal (publication) Sustainability (Switzerland)
(90)
Analysis Finding
Most Influential article "Systematic review of research on
artificial intelligence applications in
higher education - where are the
educators?" by Zawacki-Richter O.,
Marn V.I., Bond M., and Gouverneur.
(citations 524)
The most frequently
used keyword
Artificial intelligence
The most trending
keywords
ChatGPT and Chatbot
Top most Authors (Co-
citation Analysis)
Mcnamara D. S., Gasevic D., Graesser
A.C.,
Chen X., Liu Y., and so on.
Top most country (Co-
author analysis)
USA
Top most country
(Bibliographic coupling
USA

27. EDUCATIONAL IMPLICATIONS OF THE STUDY
1. Research Gap Identification
2. Journals Selection
3. Identifying Promising Research Articles
4. Keyword Selection
5. Exploring Similar Terms
6. Pedagogical Advancements
7. Global Collaboration
8. Continuous Improvement
9. Personalized Learning

28. LIMITATIONS OF THE STUDY
1. Risk of Human Error
2. Keyword Reliability
3. Subjectivity in Analysis
4. Dynamic Data
5. Reviewer Bias and Lack of External
Validation
6. Data Source Limitation
7. Surface-Level Analysis

29. 1. Use Multiple Databases
2. Multilingual Analysis
3. Publication Types
4. Time Frame Expansion
5. Interdisciplinary Approaches
6. Regional and Comparative Studies
7. Qualitative Analysis
8. Emerging AI Technologies
9. Comparative Analysis with Other Educational Levels
10.Broaden and Diversify Keyword Selection
SUGGESTIONS FOR FURTHER STUDY

30. Thank you