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RESEARCH ARTICLE
Higher education students’ perceptions of
ChatGPT: A global study of early reactions
Dejan Ravs
ˇeljID
1☯
*, Damijana Kerz
ˇičID
1☯
*, Nina Tomaz
ˇevičID
1☯
*, Lan Umek
1☯
*,
Nejc Brezovar
1☯
, Noorminshah A. Iahad
2☯
, Ali Abdulla AbdullaID
3☯
, Anait AkopyanID
4☯
,
Magdalena Waleska Aldana SeguraID
5,6☯
, Jehan AlHumaid
7☯
, Mohamed Farouk Allam
8☯
,
Maria Allo
´
9☯
, Raphael Papa Kweku Andoh
10☯
, Octavian AndronicID
11☯
, Yarhands
Dissou Arthur
12☯
, Fatih Aydın
13☯
, Amira Badran
14☯
, Roxana Balbontı
´n-AlvaradoID
15☯
,
Helmi Ben SaadID
16☯
, Andrea BencsikID
17,18☯
, Isaac Benning
19☯
, Adrian BesimiID
20☯
,
Denilson da Silva BezerraID
21☯
, Chiara Buizza
22☯
, Roberto BurroID
23☯
,
Anthony Bwalya
24☯
, Cristina Cachero
25☯
, Patricia Castillo-BricenoID
26☯
,
Harold CastroID
27☯
, Ching Sing Chai
28☯
, Constadina Charalambous
29☯
, Thomas K.
F. Chiu
30☯
, Otilia ClipaID
31☯
, Ruggero ColombariID
32☯
, Luis Jose
´H. Corral Escobedo
33☯
,
Elı
´sio CostaID
34☯
, Radu George Crețulescu
35☯
, Marta Crispino
36☯
, Nicola Cucari
37☯
,
Fergus Dalton
38☯
, Meva Demir KayaID
39☯
, Ivo Dumić-ČuleID
40☯
, Diena Dwidienawati
41☯
,
Ryan EbardoID
42☯
, Daniel Lawer Egbenya
43☯
, MoezAlIslam Ezzat Faris
44☯
,
Miroslav Fečko
45☯
, Paulo Ferrinho
46☯
, Adrian FloreaID
35☯
, Chun Yuen Fong
47☯
,
Zoe
¨FrancisID
38☯
, Alberto Ghilardi
22☯
, Belinka Gonza
´lez-Ferna
´ndezID
48☯
,
Daniela HauID
49☯
, Md. Shamim Hossain
50☯
, Theo Hug
51☯
, Fany Inasius
52☯
, Maryam
Jaffar IsmailID
53☯
, Hatidz
ˇa Jahić
54☯
, Morrison Omokiniovo JessaID
55☯
,
Marika Kapanadze
56☯
, Sujita Kumar Kar
57☯
, Elham Talib Kateeb
58☯
, Feridun KayaID
39☯
,
Hanaa Ouda KhadriID
59☯
, Masao Kikuchi
60☯
, Vitaliy Mykolayovych KobetsID
61☯
, Katerina
Metodieva Kostova
62☯
, Evita Krasmane
63☯
, Jesus Lau
64☯
, Wai Him Crystal Law
47☯
,
Florin Lazăr
65☯
, Lejla Lazović-Pita
54☯
, Vivian Wing Yan Lee
66☯
, Jingtai Li
67☯
, Diego
Vinicio Lo
´pez-AguilarID
68☯
, Adrian Luca
69☯
, Ruth Garcia LucianoID
70☯
, Juan D. Machin-
MastromatteoID
71☯
, Marwa Madi
7☯
, Alexandre Lourenc¸o MangueleID
72☯
, Rube
´n
Francisco ManriqueID
27☯
, Thumah Mapulanga
73☯
, Frederic MarimonID
32☯
, Galia
Ilieva MarinovaID
62☯
, Marta Mas-Machuca
32☯
, Oliva Mejı
´a-Rodrı
´guez
74☯
, Maria Meletiou-
Mavrotheris
29☯
, Silvia Mariela Me
´ndez-PradoID
75☯
, Jose
´Manuel Meza-CanoID
76☯
,
Evija Mirk¸e
77☯
, Alpana Mishra
78☯
, Ondrej Mital
45☯
, Cristina Mollica
79☯
, Daniel
Ionel MorariuID
35☯
, Natalia Mospan
80☯
, Angel MukukaID
81☯
, Silvana Guadalupe Navarro
Jime
´nezID
33☯
, Irena NikajID
82☯
, Maria Mihaylova NishevaID
83☯
, Efi Nisiforou
84☯
,
Joseph NjikuID
85☯
, Singhanat Nomnian
86☯
, Lulzime Nuredini-Mehmedi
87☯
,
Ernest NyamekyeID
88☯
, Alka ObadićID
89☯
, Abdelmohsen Hamed OkelaID
90☯
, Dorit Olenik-
Shemesh
91☯
, Izabela Ostoj
92☯
, Kevin Javier Peralta-Rizzo
75☯
, Almir Pes
ˇtekID
54☯
,
Amila Pilav-Velić
54☯
, Dilma Rosanda Miranda Pires
93☯
, Eyal RabinID
91☯
,
Daniela RaccanelloID
23☯
, Agustine Ramie
94☯
, Md. Mamun ur Rashid
95☯
, Robert A.
P. ReuterID
49☯
, Valentina ReyesID
96☯
, Ana Sofia Rodrigues
97☯
, Paul Rodway
98☯
,
Silvia Ručinska
´ID
45☯
, Shorena SadzaglishviliID
99☯
, Ashraf Atta M. S. SalemID
100☯
,
Gordana SavićID
101☯
, Astrid Schepman
98☯
, Samia Mokhtar ShahpoID
102☯
,
Abdelmajid Snouber
103☯
, Emma Soler
32☯
, Bengi SonyelID
104☯
, Eliza Stefanova
83☯
,
Anna StoneID
105☯
, Artur StrzeleckiID
106☯
, Tetsuji Tanaka
107☯
, Carolina Tapia Cortes
108☯
,
Andrea Teira-Fachado
9,109☯
, Henri TilgaID
110☯
, Jelena Titko
111☯
, Maryna TolmachID
112☯
,
Dedi Turmudi
113☯
, Laura Varela-Candamio
9☯
, Ioanna Vekiri
29☯
, Giada VicentiniID
23☯
,
Erisher Woyo
114☯
, O
¨zlem Yorulmaz
115☯
, Said A. S. Yunus
53☯
, Ana-Maria Zamfir
116,117☯
,
Munyaradzi Zhou
118☯
, Aleksander AristovnikID
1☯
*
1Faculty of Public Administration, University of Ljubljana, Ljubljana, Slovenia, 2Department of Information
Systems, Faculty of Management, Universiti Teknologi Malaysia, Skudai, Johor Bahru, Malaysia,
3Department of Computer Science and IT, State University of Zanzibar (SUZA), Zanzibar, Tanzania,
4Department of English for the Humanities, Southern Federal University, Rostov-on-Don, Russia,
5Education Department, Galileo University, Guatemala, Guatemala, 6Physics Department, San Carlos de
Guatemala University, Guatemala, Guatemala, 7Department of Preventive Dental Sciences, College of
PLOS ONE
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OPEN ACCESS
Citation: Ravs
ˇelj D, Kerz
ˇičD, Tomaz
ˇevičN, Umek
L, Brezovar N, A. Iahad N, et al. (2025) Higher
education students’ perceptions of ChatGPT: A
global study of early reactions. PLoS ONE 20(2):
e0315011. https://doi.org/10.1371/journal.
pone.0315011
Editor: Chengliang Wang, East China Normal
University, CHINA
Received: September 9, 2024
Accepted: November 19, 2024
Published: February 5, 2025
Copyright: ©2025 Ravs
ˇelj et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: The data presented in
this study, including a questionnaire, are available
in a public repository: Ravs
ˇelj D, Aristovnik A,
Kerz
ˇičD, Tomaz
ˇevičN, Umek L, Brezovar N, et al.
Higher education students’ early perceptions of
ChatGPT: Global survey data. Mendeley Data.
2024. Available from: https://doi.org/10.17632/
ymg9nsn6kn.
Funding: The authors acknowledge the financial
support from the Slovenian Research and
Innovation Agency (research core funding No. P5-
Dentistry, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia, 8Department of Family
Medicine, Ain Shams University, Cairo, Egypt, 9Department of Economics, Faculty of Economics and
Business, University of A Coruna, A Coruna, Spain, 10 Directorate of Research, Innovation and Consultancy,
University of Cape Coast, Cape Coast, Ghana, 11 Innovation and eHealth Center, Carol Davila University of
Medicine and Pharmacy, Bucharest, Romania, 12 Department of Mathematics Education, Faculty of Applied
Sciences and Mathematics Education, Akenten Appiah Menka University of Skills Training and
Entrepreneurial Development (AAMUSTED), Kumasi, Ghana, 13 Faculty of Education, Sivas Cumhuriyet
University, Sivas, Tu¨rkiye, 14 Faculty of Dentistry, Ain Shams University, Cairo, Egypt, 15 Faculty of
Education and Humanities, University of Bı
´o Bı
´o, Chilla
´n, Chile, 16 Research Laboratory LR12SP09 “Heart
Failure”, Faculty of Medicine of Sousse, University of Sousse, Sousse, Tunisia, 17 Department of
Management, University of Pannonia, Veszprem, Hungary, 18 Department of Management, J. Selye
University, Komarno, Slovakia, 19 Department of Mathematics & ICT Education, University of Cape Coast,
Cape Coast, Ghana, 20 Faculty of Contemporary Sciences and Technologies, South East European
University, Tetovo, Republic of North Macedonia, 21 Department of Oceanography and Limnology. Federal
University of Maranhão, São Luis, Brazil, 22 Department of Clinical and Experimental Sciences, University of
Brescia, Brescia, Italy, 23 Department of Human Sciences, University of Verona, Verona, Italy,
24 Department of Biological Sciences, Kwame Nkrumah University, Kitwe, Zambia, 25 Languages and
Computer Systems, University of Alicante, Alicante, Spain, 26 EBIOAC Lab, Faculty of Life Sciences and
Technologies, Universidad Laica Eloy Alfaro de Manabi ULEAM, Manta, Ecuador, 27 Department of Systems
and Computing Engineering, Universidad de los Andes, Bogota, Colombia, 28 Centre for Learning Sciences
and Technologies, Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China, 29 Department of
Education, European University Cyprus, Nicosia, Cyprus, 30 Department of Curriculum and Instruction,
Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China, 31 Science of Education, Stefan cel
Mare University of Suceava, Suceava, Romania, 32 Department of Economics and Social Sciences,
International University of Catalonia, Barcelona, Spain, 33 IAM, Physics Department, CUCEI, University of
Guadalajara, Guadalajara, Mexico, 34 Competence Center on Active and Healthy Ageing and
CINTESIS@Rise, Faculty of Pharmacy, University of Porto, Porto, Portugal, 35 Computer Science and
Electrical Engineering Department, Faculty of Engineering, Lucian Blaga University of Sibiu, Sibiu, Romania,
36 Independent Researcher, Rome, Italy, 37 Department of Management, Faculty of Economics, Sapienza
University of Rome, Rome, Italy, 38 Department of Psychology, University of the Fraser Valley, Abbotsford,
Canada, 39 Faculty of Letters, University of Ataturk, Erzurum, Turkiye, 40 Department of Nursing, University
North, Varaz
ˇdin, Croatia, 41 BINUS Business School, Bina Nusantara University, Jakarta, Indonesia,
42 Department of Information Technology, De La Salle University, Manila, Philippines, 43 College of Health
and Allied Sciences, University of Cape Coast, Cape Coast, Ghana, 44 Faculty of Allied Medical Sciences,
Applied Sciences Private University, Jordan, Jordan, 45 Faculty of Public Administration, Pavol Jozef S
ˇafa
´rik
University in Kos
ˇice, Kos
ˇice, Slovakia, 46 Global Health and Tropical Medicine (GHTM), Associate
Laboratory in Translation and Innovation Towards Global Health (LA-REAL), Instituto de Higiene e Medicina
Tropical (IHMT), Nova University of Lisbon, Lisbon, Portugal, 47 International College of Liberal Arts,
Yamanashi Gakuin University, Kofu, Japan, 48 Department of Sciences and Engineering, Ibero-American
University Puebla, Puebla, Mexico, 49 Department of Education and Social Work, University of Luxembourg,
Belval Esch-sur-Alzette, Luxembourg, 50 Department of Marketing, Hajee Mohammad Danesh Science and
Technology University, Dinajpur, Bangladesh, 51 Department of Media, Society and Communication,
University of Innsbruck, Innsbruck, Austria, 52 School of Accounting, Bina Nusantara University, Jakarta,
Indonesia, 53 School of Education, State University of Zanzibar (SUZA), Zanzibar, Tanzania, 54 School of
Economics and Business, University of Sarajevo, Sarajevo, Bosnia and Herzegovina, 55 Guidance and
Counselling, Delta State University Abraka, Abraka, Nigeria, 56 School of Business Technology and
Education, Ilia State University, Tbilisi, Georgia, 57 Department of Psychiatry, King George’s Medical
University, Lucknow, India, 58 Oral Health Research and Promotion Unit, Al-Quds University. Jerusalem,
Palestine, 59 Faculty of Education, Ain Shams University, Cairo, Egypt, 60 Department of Public
Management. Meiji University, Tokyo, Japan, 61 Computer Science and Software Engineering Department,
Kherson State University, Kherson, Ukraine, 62 Department of Technologies and Management of
Communication Systems, Faculty of Telecommunications, Technical University of Sofia, Sofia, Bulgaria,
63 Department of Education, Alberta College, Riga, Latvia, 64 Faculty of Pedagogy, Universidad
Veracruzana, Veracruz, Mexico, 65 Sociology and Social Work, University of Bucharest, Bucharest,
Romania, 66 Centre for Learning Enhancement and Research (CLEAR), Chinese University of Hong Kong,
Shatin, Hong Kong SAR, China, 67 School of Foreign Languages, Jiaying University, Meizhou, China,
68 Languages Department, Indoamerica Technological University, Ambato, Ecuador, 69 Department of
Applied Psychology and Psychotherapy, Faculty of Psychology and Educational Sciences, University of
Bucharest, Bucharest, Romania, 70 College of Information and Communications Technology, Nueva Ecija
University of Science and Technology, Cabanatuan City, Nueva Ecija, Philippines, 71 Faculty of Philosophy
and Letters, Autonomous University of Chihuahua, Chihuahua, Mexico, 72 Health Sciences Department,
Higher Institute of Health Sciences, Maputo, Mozambique, 73 African Centre of Excellence for Innovative
Teaching and Learning Mathematics and Science, University of Rwanda, Kayonza, Rwanda, 74 Medicine
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Higher education students’ perceptions of ChatGPT: A global study of early reactions
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0093 and project No. Z5-4569). The funders had
no role in study design, data collection and
analysis, decision to publish, or preparation of the
manuscript.
Competing interests: The authors have declared
that no competing interests exist.
School, Vasco de Quiroga University, Morelia, Mexico, 75 Faculty of Social Sciences and Humanities,
ESPOL Polytechnic University, Guayaquil, Ecuador, 76 Faculty of Higher Education Iztacala, National
Autonomous University of Mexico, State of Mexico, Mexico, 77 Institute of Digital Humanities, Faculty of
Computer Science, Information Technology and Energy, Riga Technical University, Riga. Latvia,
78 Department of Community Medicine, Kalinga Institute of Medical Science. Bhubaneswar, India,
79 Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy, 80 Department of
Linguistics and Translation, Borys Grinchenko Kyiv University, Kyiv, Ukraine, 81 Department of Mathematics,
Science and Technology Education, Mukuba University, Kitwe, Zambia, 82 Faculty of Education & Philology,
University Fan S. Noli Korc¸a, Korc¸a, Albania, 83 Faculty of Mathematics and Informatics, Sofia University
St. Kliment Ohridski, Sofia, Bulgaria, 84 Department of Education, University of Nicosia, Nicosia, Cyprus,
85 Educational Psychology and Curriculum Studies, Dar es Salaam University College of Education,
University of Dar es Salaam, Dar es Salaam, Tanzania, 86 Research Institute for Languages and Cultures of
Asia, Mahidol University, Salaya, Thailand, 87 Data Analysis Office, South East European University, Tetovo,
Republic of North Macedonia, 88 Department of Arts Education, University of Cape Coast, Cape Coast,
Ghana, 89 Faculty of Economics and Business, University of Zagreb, Zagreb, Croatia, 90 Faculty of Specific
Education, Minia University, Minia, Egypt, 91 Education & Psychology, The Research Center for Innovation
in Learning Technologies, Open University of Israel, Raanana, Israel, 92 Department of Economics, Faculty
of Economics, University of Economics in Katowice, Katowice, Poland, 93 Faculty of Science and
Technology, University of Cape Verde, Praia, Cape Verde, 94 Nursing Department, Health Polytechnic of
Banjarmasin, Banjarbaru, Indonesia, 95 Department of Agricultural Extension and Rural Development,
Patuakhali Science and Technology University, Patuakhali, Bangladesh, 96 Facultad de Economı
´a y
Negocios, Universidad de Chile, Santiago, Chile, 97 Polytechnic Institute of Viana do Castelo, Viana do
Castelo, Portugal, 98 Division of Psychology, Faculty of Health, Medicine and Society, University of Chester,
Chester, United Kingdom, 99 Research Center for Advancing Science in the Social Services and
Interventions, Social Work Program, Faculty of Arts and Science, Ilia State University, Tbilisi, Georgia,
100 College of Languages & Translation, Sadat Academy for Management Sciences, Alexandria, Egypt,
101 Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia, 102 Department of Early
Childhood, College of Sciences and Humanities Studies, Imam Abdulrahman Bin Faisal University,
Dammam, Saudi Arabia, 103 Faculty of Medicine, University of Oran1, Oran, Algeria, 104 Department of
Educational Sciences, Eastern Mediterranean University, Famagusta, Cyprus, 105 School of Psychology,
University of East London, London, United Kingdom, 106 Department of Informatics, University of Economics
in Katowice, Katowice, Poland, 107 Department of Economics, Meiji Gakuin University, Tokyo, Japan,
108 Department of Education and Humanities, University of Monterrey, Monterrey, Mexico, 109 Public Law,
Faculty of Law, University of A Coruna, A Coruna, Spain, 110 Institute of Sport Sciences and Physiotherapy,
University of Tartu, Tartu. Estonia, 111 EKA University of Applied Sciences, Riga, Latvia, 112 Faculty of
Distance Learning, Kyiv National University of Culture and Arts, Kyiv, Ukraine, 113 English Education Study
Program, Faculty of Teachers’ Training and Education, Muhammadiyah University of Metro, Metro,
Indonesia, 114 Faculty of Business & Law, Manchester Metropolitan University, Manchester, United
Kingdom, 115 Department of Econometrics & Statistics, Faculty of Economics, Istanbul University, Istanbul,
Tu¨rkiye, 116 Faculty of Business and Administration, University of Bucharest, Bucharest, Romania,
117 National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania,
118 Information and Marketing Sciences, Midlands State University, Gweru, Zimbabwe
☯These authors contributed equally to this work.
*dejan.ravselj@fu.uni-lj.si (DR); damijana.kerzic@fu.uni-lj.si (DK); nina.tomazevic@fu.uni-lj.si (NT); lan.
umek@fu.uni-lj.si (LU); aleksander.aristovnik@fu.uni-lj.si (AA)
Abstract
The paper presents the most comprehensive and large-scale global study to date on how
higher education students perceived the use of ChatGPT in early 2024. With a sample of
23,218 students from 109 countries and territories, the study reveals that students primarily
used ChatGPT for brainstorming, summarizing texts, and finding research articles, with a
few using it for professional and creative writing. They found it useful for simplifying complex
information and summarizing content, but less reliable for providing information and sup-
porting classroom learning, though some considered its information clearer than that from
peers and teachers. Moreover, students agreed on the need for AI regulations at all levels
due to concerns about ChatGPT promoting cheating, plagiarism, and social isolation.
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Higher education students’ perceptions of ChatGPT: A global study of early reactions
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However, they believed ChatGPT could potentially enhance their access to knowledge and
improve their learning experience, study efficiency, and chances of achieving good grades.
While ChatGPT was perceived as effective in potentially improving AI literacy, digital com-
munication, and content creation skills, it was less useful for interpersonal communication,
decision-making, numeracy, native language proficiency, and the development of critical
thinking skills. Students also felt that ChatGPT would boost demand for AI-related skills and
facilitate remote work without significantly impacting unemployment. Emotionally, students
mostly felt positive using ChatGPT, with curiosity and calmness being the most common
emotions. Further examinations reveal variations in students’ perceptions across different
socio-demographic and geographic factors, with key factors influencing students’ use of
ChatGPT also being identified. Higher education institutions’ managers and teachers may
benefit from these findings while formulating the curricula and instructions/regulations for
ChatGPT use, as well as when designing the teaching methods and assessment tools.
Moreover, policymakers may also consider the findings when formulating strategies for
secondary and higher education system development, especially in light of changing labor
market needs and related digital skills development.
Introduction
Artificial Intelligence (AI), originating in the 1950s, began as an exploration of machines mim-
icking human behavior and cognition [1,2]. This pursuit led to diverse fields like machine
learning, natural language processing (NLP), computer vision, and robotics, each advancing
AI’s capacity to emulate human reasoning, learning, and discernment [3]. To date, ChatGPT
stands out as the most popular interactive generative AI model based on Natural Language
Processing (NLP), a field of AI that enables computers to understand, interpret, and generate
human language. It leverages Large Language Models (LLMs), which are advanced algorithms
trained on vast amounts of text data to generate human-like responses and perform a wide
range of language tasks with high accuracy and versatility [4,5].
Developed by OpenAI, a globally recognized AI research organization, a conversational
chatbot ChatGPT was first released on November 30, 2022, with the primary objectives of
enhancing human-AI interaction and expanding AI applications in practical domains [6]. As a
fine-tuned GPT model for conversational tasks, ChatGPT is freely accessible on multiple plat-
forms, enabling users to interact seamlessly for conversations, answers, and content creation
in various styles and languages [7–9]. Due to the wide possibilities of ChatGPT’s use, teachers
and students in higher education also started using ChatGPT immediately after its release. At
the same time, many researchers became curious about what ChatGPT can and cannot do,
how students interact with ChatGPT for better learning results, and how teachers collaborate
with ChatGPT within their teaching methods [10–13]. In our research, we focused only on stu-
dents’ perspectives, which will be elaborated further in the paper.
ChatGPT offers significant applications in higher education by providing continuous, on-
demand support, personalized tutoring, enhanced revision tools, and accessibility aid, especially
benefiting students who require flexible learning options, customized explanations, or language
assistance. Additionally, its capabilities for generating practice questions, summarizing content,
and assisting in academic writing make it a valuable tool for student learning and self-directed
study. However, these advantages are accompanied by challenges, including concerns about
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Higher education students’ perceptions of ChatGPT: A global study of early reactions
PLOS ONE | https://doi.org/10.1371/journal.pone.0315011 February 5, 2025 4 / 53
academic integrity due to the potential for misuse in assignments and exams, the risk of overre-
liance that may hinder critical thinking development, and occasional inaccuracies in responses
that can mislead students lacking strong foundational knowledge. Privacy and data security
concerns add to the complexity, as students are unsure about data handling practices, and the
AI’s lack of emotional and contextual understanding limits its effectiveness in addressing the
nuanced needs of learners. Furthermore, ChatGPT’s quick, compartmentalized answers risk
promoting fragmented learning rather than fostering comprehensive conceptual understand-
ing, underscoring the need for a balanced integration of AI that encourages ethical use while
preserving the educational rigor and integrity essential in higher education [14].
Therefore, ChatGPT has the potential to foster or hinder students’ learning. It can reduce
cognitive load by handling complex tasks, freeing up working memory and supporting critical
thinking, but it may also lead to dependency and cognitive overload by replacing deep think-
ing [15]. For instance, some students could use ChatGPT’s diverse writing and learning assis-
tance capabilities to support self-regulated learning (SRL) by aiding in goal-setting and
preparation (forethought), promoting active engagement through note-taking, question prep-
aration and practice (performance), and enhancing comprehension through self-assessment
and peer discussions (self-reflection) [16]. Others, however, might use it to complete academic
assignments without developing a critical understanding of the task or engaging in meaningful
learning [17]. The effectiveness of learning how to use ChatGPT thus depends on the students’
AI competency [18,19]. Students with strong AI competency have the confidence, knowledge,
and skills to apply ChatGPT effectively and responsibly, leveraging it for new perspectives and
feedback to enhance their learning. This competency involves not only understanding the
capabilities of ChatGPT but also recognizing its limitations, making informed and ethical deci-
sions on its use, and interpreting AI-generated content critically to ensure meaningful learning
outcomes. Moreover, students’ learning is significantly influenced by instructional design and
assessment approaches. This dual role of teachers involves developing assessment designs that
integrate AI tools like ChatGPT for educational purposes and guiding students in using these
tools responsibly, effectively, and ethically. The ability of teachers to create AI-supported
assessments and instruct students on best practices in AI usage plays a critical role in shaping
students’ learning experiences [20,21]. As students will likely interact with AI tools like
ChatGPT in their future careers, building their confidence and competence in using AI is
essential for their professional development.
Research objectives
The main goal of the paper is to present a comprehensive global study on higher education stu-
dents’ perceptions of different aspects of ChatGPT use related to their study and career devel-
opment challenges. The study focuses on various aspects of ChatGPT, including its usage and
capabilities, regulation and ethical concerns, satisfaction with and attitudes towards ChatGPT,
study issues and outcomes associated with its use, skills development, labor market and skills
mismatch, and emotions related to the use of ChatGPT. The main purpose of our research was
to explore the perspectives of students worldwide on ChatGPT and to propose recommenda-
tions for higher education teachers, managers, and policymakers regarding curriculum design,
diverse teaching and assessment methods, and regulations and strategies to support effective
AI integration in education.
While the release of ChatGPT has garnered significant attention from educators globally,
there have been only a few attempts in the literature to explore students’ perceptions of
ChatGPT in higher education, capturing the perspective of students from different countries
and regions. Analyzing Twitter data from over 16 million tweets and more than 5.5 million
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Higher education students’ perceptions of ChatGPT: A global study of early reactions
PLOS ONE | https://doi.org/10.1371/journal.pone.0315011 February 5, 2025 5 / 53
users, Fu¨tterer et al. [22] explored global perceptions and reactions to ChatGPT in the context
of education, revealing that education was the most frequently tweeted topic related to
ChatGPT. However, there were also attempts to examine this topic through student surveys.
Bouteraa et al. [23] recruited 921 students from Asian countries to explore ChatGPT usage,
capabilities, satisfaction, attitudes, study issues, skills development, and personal anxiety,
although they neglected other important issues such as regulation, ethical concerns, labor mar-
ket implications, and broader emotional responses. Ibrahim et al. [24] recruited 1,601 students
from large countries, including Brazil, India, Japan, the United Kingdom, and the United
States, focusing on ChatGPT usage, capabilities, satisfaction, and attitude, but omitted regula-
tion, skills development, labor market implications, and emotional responses. Abdaljaleel et al.
[25] recruited 2,240 students from Arabic countries, offering a more comprehensive view on
ChatGPT usage and capabilities but only briefly addressing labor market implications and
skills mismatch. Our study fills the research gap by providing a global perspective on students’
perceptions of ChatGPT, covering a wide range of aspects. Accordingly, the following research
question was formulated:
RQ1: How do students perceive different aspects of ChatGPT related to its usage, capabilities,
regulation and ethical concerns, satisfaction and attitude, study issues and outcomes, skills
development, labor market and skills mismatch, and emotional responses?
Despite the growing body of research on students’ perceptions of ChatGPT, studies specifi-
cally examining the impact of socio-demographic characteristics remain limited and inconclu-
sive. Some researchers suggest that students’ perceptions of ChatGPT are influenced by factors
such as country of residence, age, type of university, and recent academic performance [25].
However, other research indicates that perceptions of ChatGPT usage among higher education
students do not significantly differ based on gender, academic programs, or educational
streams [26]. Some research has even found mixed results regarding the moderating effect of
gender and study level on the acceptance and use of generative AI by higher education stu-
dents [27]. None of these studies, however, have yet addressed the importance of academic dis-
cipline (i.e., field of study) and income regions in the context of students’ experiences with
ChatGPT. Accordingly, the following research question was formulated:
RQ2: How do students’ perceptions of various ChatGPT aspects differ across fields of study,
income regions, and other selected socio-demographic and geographic characteristics,
including gender, level of study, mode of study, area of living, and economic status?
The acceptance and use of ChatGPT have been relatively well documented, revealing that
performance expectancy, effort expectancy, social influence, and facilitating conditions signifi-
cantly influence behavioral intention and actual use across diverse educational contexts [28].
However, it remains unclear how various factors related to ChatGPT influence students’ usage
patterns, especially due to the lack of empirical analysis on a large global scale. Accordingly,
the following research question was formulated:
RQ3: How do selected factors related to ChatGPT aspects influence students’ usage patterns of
ChatGPT for various tasks, including brainstorming, summarizing, and academic writing?
The adoption of ChatGPT in higher education presents both opportunities and challenges
for students. While it enhances learning, engagement, and skills development, it also raises
concerns about academic integrity, emotional impacts, and labor market implications. To
maximize benefits and mitigate drawbacks, it is crucial to understand student perceptions
from all these perspectives. Feedback from students, particularly early adopters who are typi-
cally the most enthusiastic and influential users, provides valuable insights for the effective and
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responsible integration of ChatGPT into higher education, ultimately enhancing the overall
learning experience.
Literature review
The existing literature offers valuable insights into eight aspects of ChatGPT, including usage,
capabilities, regulatory and ethical concerns, user satisfaction and attitudes, academic issues
and outcomes, skills development, labor market dynamics and skills mismatches, and emo-
tional responses. These topics are briefly outlined below, providing a foundation for a more
in-depth exploration of each specific aspect.
Research on ChatGPT highlights its potential to enhance learning [2]. Students’ adoption
of ChatGPT is influenced by factors beyond ease of use, including perceived usefulness, social
presence, the tool’s legitimacy, enjoyment, and motivation [29]. Engaging with functionalities
that improve learning are particularly valued. Several studies highlight the potential of
ChatGPT usage in higher education, especially for supporting assessment preparation, transla-
tion, linguistic training, argumentative writing, research and analysis, programming, and sci-
entific writing. In assessment preparation, ChatGPT offers interactive problem-solving and
explanations, helping students better understand complex concepts. It supports translation
and linguistic training by providing real-time feedback on grammar and vocabulary, which is
valuable in multilingual settings. For argumentative writing, ChatGPT assists in structuring
and refining arguments, while in research, it helps with organizing ideas and synthesizing
information. In programming, it offers debugging and coding tips, fostering skill development,
and in scientific writing, it guides students in adhering to formal conventions and managing
citations. These applications showcase ChatGPT’s adaptability in enhancing personalized
learning across diverse academic areas [30–36].
Regarding its capabilities, ChatGPT is a versatile tool that enhances the learning experience
in higher education by understanding and responding in human language, providing clear
explanations, simplifying complex topics, and offering structured guidance. Acting as both a
virtual peer and an assessor, ChatGPT supports critical thinking, resource identification, and
content refinement, complementing both traditional classroom and online learning environ-
ments [31,37,38]. Its conversational abilities foster engagement and enable it to bridge digital
and in-person learning, making it a valuable partner in blended (hybrid) learning [29]. How-
ever, recognizing its limitations, such as potential misinformation, untested response accuracy,
data quality issues, and ethical considerations, is essential for maximizing its positive impact
on student learning outcomes [2,32,39–42]. By addressing these challenges, educators and
students can leverage ChatGPT to support a more personalized and efficient educational jour-
ney [42,43].
The presence of ChatGPT has also sparked regulation and ethical concerns surrounding aca-
demic integrity in higher education. Most higher education institutions lack rules for its use.
Despite the controversies surrounding ChatGPT’s impact, stakeholders view it as an opportu-
nity to enhance student learning and access. This perspective is evident from workshops
focused on using ChatGPT legally and avoiding plagiarism in scientific writing. Opinions on
generative AI tools like ChatGPT are divided: some emphasize the increased ease and comfort
in learning, while others express concerns about potential cheating and academic integrity
issues if regulations are not established [9]. Further research and discussion on the implica-
tions of AI tools, ethical use in scientific writing, and innovative teaching practices are needed.
Some institutions have banned ChatGPT from writing articles and research due to concerns
about academic integrity, content bias, and ethical issues related to patient privacy, as well as
the need for thorough screening before widespread adoption, particularly in clinical research
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and medical practice [44–46]. Studies addressing ethical concerns and regulation highlight the
necessity of minimizing risks and unintended consequences while integrating AI into educa-
tion through ongoing dialogue and research [47].
In general, students report high satisfaction and positive attitude with ChatGPT for its
instant, detailed responses and assistance in understanding complex topics [48,49]. Higher
knowledge and positive attitudes correlate with increased ChatGPT usage, especially among
final-level students [50]. Satisfaction arises from the perceived efficiency and personalized
learning experiences that these technologies offer. ChatGPT also enhances research capabili-
ties, contributing to academic satisfaction through quicker access to scholarly materials.
However, concerns about the reliability and accuracy of ChatGPT’s information persist,
necessitating cross-verification and cautious use [51]. Computer science students suggest
clearer guidelines for effective utilization [52]. Additionally, ChatGPT’s inability to respond
to emotional cues limits its effectiveness compared to human tutors [48–54]. These mixed
feelings underscore the need for guidelines and training on the ethical use of AI tools. While
higher education students generally have a positive attitude towards ChatGPT, educators
must address ethical concerns and the risk of dependency. Integrating AI tools responsibly
into the curriculum can maximize benefits while mitigating drawbacks, and effective use
should be complemented by the development of critical thinking and information literacy
skills.
Research suggests that ChatGPT can effectively support students in addressing study issues
and improving learning outcomes, with evidence showing a positive correlation between its use
and enhanced academic performance. This positive impact is driven particularly by the per-
sonalized feedback and interactive experiences AI chatbots provide, which have proven to
boost motivation, engagement, and self-efficacy while reducing learning anxiety [55]. Students
report significant improvements in academic performance due to quick responses and relevant
resources, especially outside regular classroom hours [56], as well as immediate assistance for
academic tasks [57]. Students in scientific disciplines particularly noted its role in enhancing
their understanding of complex subjects [48]. Responses to ChatGPT vary across cultural and
linguistic backgrounds, necessitating nuanced approaches to its use [58]. To ensure the effec-
tive use of ChatGPT, students should embrace emerging technologies while being trained to
apply AI outputs responsibly, avoiding overreliance or academic misconduct. Clear guidance
on AI misuse, aligned with teaching information literacy, is crucial [53,59]. Ngo [56] suggests
that reducing integrity risks, such as assessing information quality and citing sources accu-
rately, can improve study outcomes. Strategies like verifying responses, providing clear usage
guidelines, and promoting academic integrity are essential for the ethical use of AI in acade-
mia. Javaid et al. [60] highlight ChatGPT’s potential in tutoring and personalized learning.
However, balancing the convenience of AI with encouraging independent application of
knowledge and skills is essential for effective integration into educational contexts.
Research shows ChatGPT enhances skills development by offering an interactive environ-
ment and extensive knowledge [61,62]. Lee [33] found that its use in medical education cre-
ates interactive virtual learning environments, improving learning and communication skills
[63–66]. ChatGPT also enhances students’ writing skills by providing real-time grammar cor-
rection, vocabulary enrichment, and compositional feedback [67–69]. Effective incorporation
into education requires balancing AI assistance with fostering intrinsic writing skills [9,70].
Engaging higher education students in problem-solving tasks improves knowledge transfer,
critical thinking, and idea generation [71–73]. Studies show that smart personal assistants sup-
port problem-solving skills [74,75]. Essien et al. [76] suggest that AI-driven learning promotes
critical thinking and encourages new teaching methods. Urban et al. [77] found that ChatGPT
improves complex problem-solving performance and self-efficacy but has an unclear impact
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on task interest and metacognitive monitoring. Concerns exist about AI disrupting problem-
solving processes by generating diverse solutions [78–80], but evidence regarding ChatGPT’s
impact on actual performance is limited [81].
Studying labor market and skills mismatch issues related to ChatGPT in higher education
is crucial [82]. Chen et al. [83] suggest that jobs involving writing and programming are
more susceptible to replacement by language models, with higher-paying positions at greater
risk. They conclude that learning ChatGPT skills offers a competitive advantage in the labor
market. ChatGPT can simulate human thinking, understand and generate language, and
assist in task completion more efficiently. In China, 28% of occupations require ChatGPT
skills, especially in high-paying industries like technology and sales, where algorithm engi-
neers benefit from improved efficiency [83,84]. However, Shoufan [85] claims that senior
computer engineering students view ChatGPT as a job threat but notes that the perceived
negative impact of ChatGPT on job opportunities is moderate, aligning with its role as a
complementary tool. Despite this, ChatGPT is seen as a complementary resource rather than
a replacement for human intelligence, prompting universities to integrate it into curricula
[86–88]. Huseynov [89] finds that US students exhibit pessimistic shifts after negative
ChatGPT discussions, with female students particularly concerned. Addressing skills mis-
matches is critical, and AI like ChatGPT can help by identifying skill gaps and recommend-
ing targeted training [84,90].
Adopting new technologies like ChatGPT elicits both positive and negative emotions in stu-
dents. Under significant academic pressure, students are more inclined to use ChatGPT for its
immediate unburdening effect [91]. A study by Hadi Mogavi et al. [92] found mixed emotions
among early adopters in education: excitement about its benefits and convenience, alongside
apprehension about dependency. Mamo et al. [93] analyzed social media posts from higher
education faculty and found mostly neutral (51%), positive (40%), and some negative (9%)
sentiments. Trust and joy were common positive emotions, while anger and fear were the pri-
mary negative ones. Fu¨tterer et al. [22] revealed that emotional reactions to ChatGPT are het-
erogeneous and change over time. AI significantly reduces work burdens, making academic
tasks easier, but it may potentially affect academic integrity [94]. ChatGPT use may also cause
memory-related issues and procrastination, negatively impacting academic performance and
increasing stress and anxiety [91,95]. This highlights the need for cautious and responsible use
of AI tools like ChatGPT.
While the current literature provides valuable insights into various aspects of ChatGPT use
in higher education, several critical research gaps remain. First, although existing studies
explore ChatGPT’s impact on learning outcomes, skill development, and ethical concerns,
they often lack a global perspective that captures diverse cultural, economic, and educational
contexts. This limitation reduces the generalizability of findings and overlooks how regional
variations shape students’ experiences with ChatGPT. Second, while much of the research
focuses on satisfaction, study outcomes, and technical capabilities, it largely neglects key areas
like regulatory issues, labor market implications, and comprehensive emotional responses
associated with ChatGPT use, all of which are essential to fully understanding the integration
of AI in educational settings. Third, there is limited analysis of how socio-demographic factors,
such as field of study, income region, and other socio-economic characteristics, influence stu-
dents’ perceptions and experiences with ChatGPT. By considering geographic diversity, a vari-
ety of ChatGPT aspects, and different student characteristics, this study seeks to fill these gaps
by offering a broader view of students’ perceptions of ChatGPT to provide insights that sup-
port meaningful integration and enrich learning experiences while preparing students for
future challenges.
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Materials and methods
Study participants and procedure
Our global study targeted higher education students who are currently enrolled at any level in
a higher education institution, are at least 18 years old, and have the legal capacity to provide
free and voluntary consent to participate in an anonymous online survey. Survey participants
were recruited using a convenience sampling method, which involved promoting the survey in
classrooms and through advertisements on university communication systems. This method
proved effective due to its practical nature, allowing for easy access to potential participants
who were readily available and willing to participate in the survey. The survey was initially
designed in English. Due to the lack of systematic evidence on students’ early perceptions of
ChatGPT, the content of the questionnaire was developed in collaboration with international
partners, focusing on the most important aspects related to ChatGPT. This approach ensured
that the questionnaire addressed diverse perspectives and captured a comprehensive view of
students’ perceptions of ChatGPT in the context of higher education. The preliminary version
of the questionnaire was validated with students from Slovenia (see Aristovnik et al. [11]), and
the final version was refined based on feedback from pilot testing, enhancing its reliability and
relevance for the target population. In order to ensure and achieve a global reach, the question-
naire was later translated into six additional languages, including Italian, Spanish, Turkish,
Japanese, Arabic, and Hebrew, by native speakers proficient in English.
The survey was developed using the web application 1KA (One Click Survey; https://www.
1ka.si/d/en), which complies with the General Data Protection Regulation (GDPR), ensuring
informed consent, anonymity, and confidentiality for all participants. The survey was pub-
lished online on 9 October 2023 as a prerequisite for submitting requests for ethical procedures
to relevant ethics committees/Institutional Review Boards. All participating international part-
ners adhered to local regulations and guidelines regarding ethical approvals. The survey was
conducted at varying time intervals by international partners, depending on when ethical
approval was obtained in their respective institutions or countries. In cases where ethical
approval was not required, the survey followed the first approval granted on 24 October 2023.
The survey remained open for data collection until 29 February 2024. This coordinated
approach ensured that the survey maintained ethical integrity across all participating regions.
Given that ChatGPT was introduced to the general public in November 2022, the survey thus
captured early student experiences with a conversational AI chatbot.
By the end of February, 23,218 students from 109 different countries and territories had
participated in the survey. Since participants were not required to complete the entire ques-
tionnaire, the number of responses varied across questions. The participation was unequally
distributed across different countries and territories as follows: 1) over 1,000 responses were
collected in each of 4 countries (Ecuador, Spain, Mexico, and Italy); 2) between 500 and 1,000
responses were gathered in each of 9 countries (Romania, Egypt, Tanzania, Ghana, Chile, Pal-
estinian State, Turkey, Cyprus, and Latvia); 3) between 200 and 500 responses were collected
in each of 24 countries; and 4) fewer than 200 responses were collected in each of 72 countries.
In order to capture the specifics between countries with similar economic development pat-
terns, the participants were grouped into four income regions: low income, lower middle
income, upper middle income, and high income, based on the World Bank classification of
countries [96].
The sample was dominated by female students, with a considerable majority being first-
level students. Most students were studying social sciences and applied sciences, while fewer
were studying natural and life sciences, and arts and humanities. A large share of students was
engaged either in traditional learning or blended learning. The majority of students resided in
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urban areas and came from average economic backgrounds. While students from high income
and upper middle income regions prevailed, those from lower middle income regions were
less represented, with students from low income regions being represented the least. A detailed
overview of the socio-demographic and geographic characteristics of the survey participants is
presented in Table 1.
Measures
The data were collected through an online questionnaire consisting of 42 primarily closed-
ended questions aimed at capturing students’ perspectives on their early experiences with
ChatGPT. The questionnaire was structured in the form of 11 sections. In addition to socio-
demographic characteristics (12 questions from Q1 to Q12), the questionnaire covered several
aspects relevant to ChatGPT, including usage (6 questions from Q13 to Q18), capabilities (1
question, Q19), regulation and ethical concerns (4 questions from Q20 to Q23), satisfaction
and attitude (2 questions, Q24 and Q25), study issues and outcomes (2 questions, Q26 and
Table 1. Socio-demographic and geographic characteristics of the survey participants.
Socio-demographic and geographic characteristics Number Share (%)
Gender
Male 9,346 41.2
Female 13,365 58.8
Level of study
First 18,935 83.4
Second 2,867 12.6
Third 912 4.0
Field of study
Arts and humanities 2,740 12.1
Social sciences 9,356 41.4
Applied sciences 7,809 34.5
Natural and life sciences 2,717 12.0
Mode of study
Traditional learning 10,754 47.3
Online learning 2,159 9.5
Blended learning 9,833 43.2
Area of living
Urban 11,404 64.3
Suburban 3,513 19.8
Rural 2,823 15.9
Economic status
Significantly below average 1,179 6.6
Below average 3,504 19.7
Average 9,910 55.8
Above average 2,749 15.5
Significantly above average 424 2.4
Income region
High income 9,391 41.1
Upper middle income 8,090 35.4
Lower middle income 5,223 22.9
Low income 140 0.6
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Q27), skills development (2 questions, Q28 and Q29), labor market and skills mismatch (2
questions, Q30 and Q31) and emotions (1 question, Q32). Moreover, the questionnaire also
covered general study and personal information (8 questions from Q33 to Q40), including
additional socio-demographic elements not directly related to ChatGPT, while the last ques-
tion was about general reflections on ChatGPT (1 question, Q41). Finally, participants were
given the option to agree to receive the results of the survey (Q42). However, since the ques-
tionnaire required participants to have prior experience with ChatGPT, it was offered in full
only to those who had used ChatGPT. Participants who had not used ChatGPT were offered
only questions about socio-demographic characteristics, additional study and personal infor-
mation, and the option to agree to receive the results of the survey. Except for single-choice
and open-ended questions, individual statements within a question asking about frequency
and agreement were measured on a 5-point Likert scale from 1 (strongly disagree / never) to 5
(strongly agree / always) [97]. A full version of the questionnaire and the dataset are available
in the Mendeley Data repository (see Ravs
ˇelj et al. [98]).
Statistical analysis
Data preparation, including merging and cleaning, was conducted using the Python program-
ming language, specifically with the Pandas and NumPy libraries [99]. Data was analyzed with
several statistical approaches. Using the mentioned Python libraries, descriptive statistics,
including sample description, top two box scores (i.e., the percentage of students who
answered with the highest two responses on the 5-point Likert scale), and mean values of stu-
dent responses were calculated. Moreover, the written responses from students (Q41) were
compiled into a word cloud, which was created using the Python Wordcloud Library [100]. To
further examine the mean differences between students with varying socio-demographic and
geographic characteristics across different aspects, statistical tests, including independent sam-
ples t-test and analysis of variance (ANOVA), were performed using the Python Library SciPy
[101].
Finally, to analyze the factors influencing the specific usage of ChatGPT among students,
an ordinal logistic regression analysis was conducted. This methodological approach was cho-
sen because it is well-suited for examining ordinal outcomes, such as the frequency of different
ChatGPT usage. Consequently, it allows us to effectively understand how various factors influ-
ence these outcomes across ordered categories, making it the most appropriate technique for
analyzing the ordinal dependent variables related to specific ChatGPT usage (Q18e, Q18g,
Q18a). The standard interpretation of the ordinal logit coefficient is that for every one-unit
increase in the independent variable, the dependent variable is expected to change by its corre-
sponding regression coefficient on the ordinal log-odds scale, assuming the other variables in
the model remain constant. In other words, a positive coefficient indicates that students with
higher scores on the independent variable are more likely to fall into a higher category. Con-
versely, a negative coefficient indicates that students with lower scores on the independent
variable are more likely to fall into a lower category [102]. Moreover, several independent vari-
ables were included in the ordinal regression analysis, covering selected ChatGPT-related fac-
tors across different aspects (capabilities (Q19g, Q19f), regulation and ethical concerns (Q23d,
Q21c), satisfaction and attitude (Q25b, Q25d), study issues and outcomes (Q26a, Q26b), skills
development (Q29i, Q28i), labor market and skills mismatch (Q30e, Q30i), and emotions
(Q32l, Q32e)), with socio-demographic and geographic characteristics (presented in Table 1)
included as control variables. While the main independent variables of interest were measured
on a 5-point Likert scale, most of the control variables were nominal, meaning they were cate-
gorical with no inherent order. Therefore, dummy coding was employed to recode these
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categorical predictors, enabling the regression coefficients of the newly created dummy vari-
ables to meaningfully identify between-group differences [103]. The ordinal regression analy-
sis, along with proportional odds and multicollinearity testing (Spearman correlation and
multicollinearity diagnostics, including variance inflation factor (VIF) and tolerance (TOL)),
was performed using SPSS 28.0 [104].
As already mentioned, since participants were not required to complete the entire question-
naire, the number of responses varied across questions. Accordingly, a complete case analysis
approach was applied to address issues with missing data [105]. Assuming "missing completely
at random," meaning that the complete cases are a random sample of the originally identified
set of cases, this approach is the most common method for handling missing data in many
fields of research, including educational research, with statistical packages such as SPSS being
the default method supported for a large number of statistical procedures [106].
Ethical considerations
All participants in the global ChatGPT student survey were provided with detailed information
about the study. Participation was anonymous and voluntary, with students having the option
to withdraw at any time without any consequences. To ensure data protection, the online sur-
vey was only available to individuals aged 18 or older who were enrolled in a higher education
institution. Before starting the survey, the participants were required to provide a written
agreement to the terms of participation by clicking ’Next page’ on the introductory page of the
online questionnaire, thereby consenting to the outlined conditions and agreeing to participate
in the survey. This consent procedure was reviewed and approved by the relevant ethics com-
mittees/Institutional Review Boards as part of the ethical review process, ensuring that it meets
the necessary ethical standards for participant consent. The procedures of this study complied
with the provisions of the Declaration of Helsinki for research involving human participants.
Ethical committees of several involved higher education institutions approved this study,
including the University of Oran 1, Algeria (Ethical Clearance Number: 03/CED/FACMED/
2023); the University of Nicosia and the European University Cyprus, Cyprus (Ethical Clear-
ance Number: EEBK EII 2023.01.318); the Polytechnic University, Ecuador (Ethical Clearance
Number: C-22); the University of Verona, Italy (Ethical Clearance Number: 2023_25); Yama-
nashi Gakuin University, Japan (Ethical Clearance Number: 23–010); the University of Lux-
embourg, Luxembourg (Ethical Clearance Number: ERP 23–101 StuPer ChatGPT SA/cd);
Imam Abdulrahman Bin Faisal University, Saudi Arabia (Ethical Clearance Numbers: IRB-
2024-02-091 and IRB-2024-10-316); the University of Chester, United Kingdom (Ethical
Clearance Number: ASCHPR0211/23); and the University of East London, United Kingdom
(Ethical Clearance Number: ETH2324-0028). Additional information regarding the ethical,
cultural, and scientific considerations specific to inclusivity in global research is included in
the Supporting Information (S1 Checklist).
Results
A first insight into early student experiences with ChatGPT revealed that most students (71%)
had already used ChatGPT, providing valuable insights into their early experiences with the
tool during its first year of existence. While only the students who have used ChatGPT are fur-
ther elaborated on, a profile of the students who have not used ChatGPT can still be extracted,
revealing the characteristics of this subgroup. According to the socio-demographic and geo-
graphic characteristics of those who have not used ChatGPT, the majority were female (68%),
first-level students (84%), students studying social sciences (46%), engaged in traditional
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learning (52%), residing in urban areas (60%), from average economic backgrounds (58%),
and studying in high income (39%) and upper middle income (34%) regions.
Overview of the survey results
The global survey results include student perceptions of ChatGPT, highlighting the most and
least emphasized elements (statements) across various aspects (Fig 1). In terms of satisfaction
and attitude, most students (70%) found ChatGPT interesting to use, while only a quarter
found it easier to interact with ChatGPT than with colleagues. For study issues and outcomes,
the majority of students (69%) reported that ChatGPT can improve their general knowledge,
whereas only about one-third indicated it can facilitate completing their internships. Regard-
ing capabilities, most students (68%) valued its ability to simplify complex information,
whereas 41% noted its support for traditional classroom learning. Under regulation and ethical
concerns, most students (66%) were aware of taking appropriate measures to protect personal
information, compared to slightly less than one-quarter who were concerned about privacy
invasion. In the labor market and skills mismatch aspect, most students (61%) saw that
ChatGPT would increase the demand for employees with AI-related skills, while fewer (36%)
acknowledged its potential to reduce skills shortages. For skills development, about half of the
students (53%) perceived ChatGPT as an effective tool to improve their AI literacy skills, while
less than one-third (31%) believed it was effective in enhancing their interpersonal communi-
cation skills. Emotions-wise, about half of the students felt curious using ChatGPT, while only
6% felt sad. Lastly, regarding usage, less than a third of students (29%) used it for brainstorm-
ing, and only a few (11%) for creative writing.
Moreover, general views about students’ perceptions of ChatGPT were gathered from stu-
dents’ written responses by asking them to write down their views on how they see ChatGPT.
As illustrated in the word cloud visualization (Fig 2), the results highlight several key themes
and insights relevant to ChatGPT’s application and perception among students. The most
prominent words are "good," "helpful," "tool," and "student," indicating that students view
ChatGPT as a valuable tool for their activities. The emphasis on "work," "task," "assignment,"
and "studies" shows its usefulness in managing coursework. Key themes like "learning,"
"knowledge," and "understand" highlight its role in enhancing comprehension. Frequent
Fig 1. Most and least exposed statements across ChatGPT aspects.
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mentions of "question" and "answer" suggest its utility in providing quick responses, while
words like "idea," "thinking," and "interesting" indicate its ability to stimulate creativity. Posi-
tive terms such as "great," "improve," "amazing," and "future" underscore its value and potential
in education. Words like "technology," "AI," "innovation," and "app" reflect recognition of
ChatGPT as a cutting-edge tool. Terms like "easy," "efficient," "fast," and "reliable" show it is
user-friendly and dependable. Words like "academic," "university," "professor," and "reference"
suggest it is seen as a credible aid in higher education. Negative terms like "cheat," "plagiarism,"
and "lazy" indicate some ethical concerns, but these are less prominent. Overall, the word
cloud illustrates that students view ChatGPT as a beneficial, innovative tool that enhances
their academic experience and holds promise for the future of education.
The supporting information (S1 File) includes a comprehensive table with detailed empiri-
cal results for each aspect of ChatGPT. The table is organized by different aspects, clearly indi-
cating which statement pertains to each aspect along with the mean and top two box values for
the total sample for each statement, allowing for the identification of the most and least
exposed statements across aspects by both criteria. Moreover, the table presents comparisons
between different students’ groups based on diverse socio-demographic and geographic char-
acteristics. Specifically, the comparison includes: 1) information about the highest and lowest
mean values achieved in specific groups of students; 2) mean differences between the highest
and lowest mean values, supplemented by the significance of these differences; 3) information
on which group of students (based on socio-demographic and geographic characteristics)
reported the highest and lowest mean values; and 4) information on which group of students
(based on socio-demographic and geographic characteristics) reported the highest and lowest
top two box scores. The results of the comprehensive analysis are systematically presented in
the following subsections.
Usage. The possibilities and uses of ChatGPT offer a wide range of options to the students
in their learning process. However, how students use the opportunities offered by the new
Fig 2. Word cloud of students’ perceptions of ChatGPT.
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technology varies according to their abilities, interests, affection and integrity (e.g., Bouteraa
et al. [23], Garrel & Mayer [107], Shoufan [85]). In the first section of the questionnaire, stu-
dents were asked how often they used ChatGPT for different tasks, from more general tasks
such as proofreading, translating, or asking for advice on different topics to more specific tasks
such as help with academic writing or coding (Fig 3). On average, students’ responses ranged
from 1.92 to 2.76. Students most frequently reported using ChatGPT for brainstorming, with
almost 30% (2.76), followed by using ChatGPT for summarizing long texts, which was sup-
ported by 27% of students (2.64), finding articles for research, supported by 25% of students
(2.63), and writing texts, chosen by 22% of students (2.64), which is partially consistent with
Chan and Hu’s [30] findings. The lowest number of students used ChatGPT for professional
writing, supported by 12% of students (1.96), and creative writing, chosen by 11% of students
(1.92). As both these writings are very personal in nature, this could mean that students still
prefer to express themselves personally rather than leave it to the AI.
Unlike Garrel and Mayer [107], who found that engineering, mathematics, and science stu-
dents used ChatGPT most frequently, the responses in our survey showed that the frequency
of use differed between disciplines on average from 1.75 and 2.88 (Fig 4). Arts and humanities
students were more likely to use it for creative writing, proofreading, brainstorming, transla-
tion, and personal support, while applied sciences students were more likely to use it for aca-
demic and professional writing, summarising, calculating and coding, as well as for study and
research support. Focusing on the student’s field of study, the largest difference (0.84) between
the highest and lowest mean was found in coding support for programming, which is not sur-
prising since the difference observed is between students of applied sciences with almost 32%
engagement, where programming is more often a compulsory subject, and those of social sci-
ence, where students are not often interested in coding computer programs (10%). In fact, this
is where the largest differences were found in the whole questionnaire. Coding assistance also
showed one of the larger gender differences (0.58), with males scoring higher. As there are
more men than women studying programming or related computer studies, this is not surpris-
ing. The use of ChatGPT for generating new ideas and brainstorming is the most popular
among students, varying between 25% and 33% depending on the field of study. In fact, a third
of arts and humanities students have used it, but the average usage was still low (2.88). When
Fig 3. ChatGPT usage frequency (top two box scores and average values).
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students were looking for information to write a research paper, the smallest difference was
found between the fields (0.11), with almost a quarter of students using ChatGPT, regardless
of their field of study.
In general, according to the income region, there was a notable gap between the demo-
graphic groups (Fig 5). Interestingly, in almost all cases, the highest scores were achieved by
students from low and lower middle income regions, while those from high income regions
scored lowest on all statements. Hence, the largest difference was found for using ChatGPT to
help with learning (0.64), followed by personal help with various tasks (0.54), for using
ChatGPT to help with coding (0.51) and academic writing (0.41). Overall, we can summarize
that the tasks for which students used ChatGPT, supported by 25% or more of the students
regardless of income region, were generating new ideas, summarizing long texts concisely, and
helping with research writing.
Fig 4. Differences in ChatGPT usage frequency (top two box scores by field of study).
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Fig 5. Differences in ChatGPT usage frequency (top two box scores by income region).
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However, if we look at the results according to different demographic factors, the results
show that significantly lower scores for usage were achieved by males, in traditional education,
by students with a lower than average economic status and also by students from the low
income regions. If, in the first two, it is still possible to speculate about the personal approach,
then the last two demographic groups may indicate that this type of writing is not often used
by students from economically disadvantaged backgrounds. It is also notable that students
from rural backgrounds demonstrated the highest usage of ChatGPT, regardless of the task.
However, the differences between demographic groups based on their place of residence were
minimal. This pattern is also observed for students with significantly abovenaverage economic
status, where the differences were more pronounced. Additionally, there were no major differ-
ences between the groups when considering the level of study, except for the use of ChatGPT
as a study assistant, reported by 22% of students in the first level of study. This might be
because students at higher levels encountered ChatGPT later in their academic journey, by
which time they had already developed their own learning strategies.
Capabilities. Students were generally aware of ChatGPT’s capabilities, particularly in sim-
plifying complex information (68%) and summarizing extensive content (67%) (Fig 6). This
awareness highlights students’ recognition of ChatGPT as a valuable tool for breaking down
difficult concepts and condensing large amounts of information into more manageable forms.
However, respondents were least likely to believe that ChatGPT could provide reliable infor-
mation (41%) and support traditional classroom learning (41%). This discrepancy implies that
while students appreciate the strengths of ChatGPT in making information easier to under-
stand and summarizing content, they remain skeptical about its reliability and usefulness in a
traditional classroom setting. This skepticism is also reflected in the findings of Mai et al.
[108], who noted similar concerns about the reliability and classroom integration of AI tools
like ChatGPT.
To some extent, academic discipline seems to influence perceptions of ChatGPT’s capabili-
ties, particularly its ability to respond in human language (Fig 7). Despite lacking feelings,
unique experiences, or subjective viewpoints, ChatGPT is designed to simulate human-like
interaction and respond naturally, creating the perception of a human touch [28]. Applied sci-
ences students (64%) found this ability more beneficial, as ChatGPT’s capability in simplifying
Fig 6. Agreement on ChatGPT capabilities (top two box scores and average values).
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and clarifying complex technical information aligns with their field’s emphasis on clear and
accurate communication. In contrast, arts and humanities students (53%), who prioritize
nuanced and interpretive language, might be more critical of ChatGPT’s ability to capture the
depth and subtleties of human expression. This indicates that while ChatGPT is valued for its
technical prowess in certain disciplines, its perceived shortcomings in handling more abstract
and subjective content limit its acceptance among students in fields that demand such
capabilities.
Larger gaps in perceiving ChatGPT’s capabilities were observed across income regions,
with students from low income regions (57%) being the most aware of ChatGPT’s potential to
support traditional classroom learning, while students from high income regions are the least
aware (38%), confirmed by the largest mean difference (0.44) (Fig 8). This could be due to the
greater reliance of students from low income regions on cost-effective digital tools to
Fig 7. Differences in agreement on ChatGPT capabilities (top two box scores by field of study).
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Fig 8. Differences in agreement on ChatGPT capabilities (top two box scores by income region).
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supplement their lack of educational resources [109]. Conversely, students from high income
regions (64%) seem to be the most aware of ChatGPT’s capability to understand instructions
given in human language, while students from low income regions (45%) perceived it the least.
This finding aligns with the observation that developed countries have already implemented
modern learning approaches emphasizing personalized learning, making ChatGPT’s capability
to understand human language more appreciated by students from developed countries com-
pared to those from developing countries [110]. Thus, the economic context significantly
shapes how students perceive and utilize AI tools in their educational pursuits.
While gender and area of living had only minor implications for student perceptions of
ChatGPT’s capabilities, more noticeable differences could be observed in other socio-
demographic characteristics. Compared to others, students of above average economic sta-
tus largely agreed that ChatGPT can understand instructions given in human language
(66%). This agreement likely stems from their exposure to and familiarity with advanced
technological tools and educational resources. Additionally, blended learning students
largely agreed that ChatGPT could facilitate blended learning (58%), highlighting the tool’s
potential to support hybrid educational models that combine online and face-to-face
instruction. Finally, despite relatively lower percentages across levels of study, undergradu-
ate students largely agreed that ChatGPT could provide reliable information (42%). This
indicates a cautious optimism among undergraduates about the potential of AI tools to
enhance their learning experience despite prevailing concerns about their reliability.
Regulation and ethical concerns. There is a consensus in academia about different ways
of regulating AI usage, as proposed by several studies [111,112]. The results of our study also
reflected this consensus among students regarding the need for international and government
regulation of AI systems like ChatGPT, with mean values of 3.32 and 3.14 (Fig 9). Particularly
relevant to students, there was a strong agreement on the necessity of ethical guidelines from
universities, faculties, or employers, as indicated by mean scores of 3.44 and 3.34. This agree-
ment on ethical guidelines aligned closely with the students’ awareness of potential issues asso-
ciated with ChatGPT. They were concerned that ChatGPT could promote unethical behaviors,
especially cheating and plagiarism, reflected in mean values of 3.15 and 3.14, respectively.
Additionally, there were fears that these systems might compromise the ethics of study and
Fig 9. Agreement on ChatGPT regulation and ethical concerns (top two box scores and average values).
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mislead users with inaccurate information. This heightened awareness among students was
supported by numerous studies testing the accuracy of information produced by AI [111,113].
On the other hand, students also expressed concerns about the social impacts of ChatGPT,
including privacy invasion, reduced human interaction, and increased social isolation. Overall,
the findings underlined the importance of balancing the potential benefits and risks of AI.
While AI has the potential to revolutionize industries [114], the necessity of protecting per-
sonal information is clear, as emphasized by a considerable share of students (66%).
While limited research has been conducted on how regulatory and ethical concerns regard-
ing ChatGPT vary across academic disciplines, our study found that opinions on this matter
differ remarkably among these groups (Fig 10). Students from arts and humanities showed the
strongest inclination toward regulatory support across all settings, particularly in the belief
that ChatGPT should be subject to university and faculty ethical guidelines (57%). Although
approximately 50% of students from applied sciences supported regulation in academic set-
tings, their support was consistently the lowest across various contexts, including interna-
tional, government, academic, and employment regulations. Students from arts and
humanities and social sciences generally expressed greater concern about whether ChatGPT
encourages cheating, plagiarism, and unethical behavior compared to those from applied sci-
ences and natural and life sciences, as indicated by significant differences ranging between
0.14 and 0.15. Although relatively fewer students were concerned about whether ChatGPT
might invade privacy, replace formal education, or increase social isolation, those from arts
and humanities and social sciences still demonstrated greater concern compared to students
from applied sciences and natural and life sciences. In terms of ethical considerations, a larger
proportion of students from arts and humanities believed they should consult (55%) or dis-
close their usage of ChatGPT to their teachers (45%), which was significantly higher than in all
other disciplines. In general, students from applied sciences and natural and life sciences tend
to have lower concerns about ethical and regulatory issues regarding ChatGPT usage, which
could stem from their comfort with and understanding of technological tools [115–117]. This
familiarity with new technologies may lead these students to adjust their ethical attitudes about
regulations in a way that aligns with their personal interests, a behavior explained by cognitive
dissonance theory, which posits that individuals modify their beliefs to reduce discomfort
Fig 10. Differences in agreement on ChatGPT regulation and ethical concerns (top two box scores by field of
study).
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from conflicting attitudes [118], in contrast to students from arts and humanities, and social
sciences who may demonstrate greater caution or skepticism.
Students from high income regions showed significantly less support for official govern-
ment regulation (36%), university guidelines (49%), and employer guidelines (42%) (Fig 11).
Similarly, they were least likely (29%) to report unethical use of ChatGPT by colleagues to
their teachers, compared to students from other income regions. An interesting trend observed
was that as the income level of a region increases, so does the concern about the potential for
misleading information due to AI. High income regions showed the greatest concern (48%),
followed by upper middle (42%), lower middle (38%), and low income regions (33%). Addi-
tionally, low income regions were notably more worried about social issues such as increased
social isolation and reduced human interaction, as indicated by significant mean differences of
0.29 and 0.24, respectively.
A consistently higher percentage of female students compared to male students believed
that there should be ethical guidelines and regulations at the international, government, uni-
versity, and employer levels. They also consistently expressed more ethical concerns about
ChatGPT, including issues related to ethics and social impact. The heightened moral concerns
among females, observed across different cultures, may be attributed to various socio-cultural
factors [119,120]. Another trend consistently appeared across most statements measuring
concern about regulations and ethical issues, indicating that students with more advanced lev-
els of study typically exhibit a heightened awareness of the implications of AI use, which devel-
ops over their time in college. Finally, the area of residence seemed to influence concerns, i.e.,
students living in urban and suburban areas were slightly more concerned that ChatGPT
encourages cheating and plagiarism (approximately 45%), compared to about 40% of students
from rural areas.
Satisfaction and attitude. On average, students’ satisfaction ranged from 2.62 to 3.83. In
comparison, the ratings for the attitude statements were somewhat higher, ranging from 3.35
to 3.81 (Fig 12). Almost 70% of students agreed or strongly agreed that using ChatGPT is inter-
esting. A good half of students agreed that ChatGPT is helpful in their daily lives (58%), that
they can control it (57%), and that they are satisfied with the level of its assistance (56%).
Fig 11. Differences in agreement on ChatGPT regulation and ethical concerns (top two box scores by income
region).
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Conversely, only 25% of students agreed or strongly agreed that it is easier to interact with
ChatGPT than with colleagues and that the information obtained from ChatGPT is clearer
than that provided by their teachers. The preference for human interaction, noted by Rodway
and Schepman [121], can be attributed to the lack of social presence in AI interactions [122].
This theory suggests that personal connection and interaction quality are often lower in com-
puter-mediated communication than in face-to-face interactions, making students less com-
fortable with an AI tool. The low percentage of students agreeing that ChatGPT provides
clearer information than their teachers may stem from a "human favoritism" bias rather than
an aversion to AI [123,124]. This bias means content created by humans is rated higher
despite AI-generated content sometimes matching or exceeding human quality. Overall, in
our study, students were generally satisfied with ChatGPT’s usefulness and assistance but pre-
ferred human interaction and communication clarity, highlighting areas for AI improvement.
Examining the data by field of study reveals significant differences in student satisfaction
and attitudes towards ChatGPT (Fig 13). In general, students in applied sciences consistently
reported higher levels of satisfaction with all statements compared to their peers in other sub-
ject areas but did not deviate from the results regarding the proportions of agreement men-
tioned above. The differences in satisfaction might be explained by the nature of the
disciplines and the inherent demands of students’ academic work. Students in applied sciences
often use digital tools and technologies as part of their curriculum, which requires them to
interact with software, coding, and data analysis tools. The pedagogical approach in applied
sciences emphasizes practical applications and problem-solving, where ChatGPT can be signif-
icantly supportive. ChatGPT’s ability to provide clear, factual, and technical support meets
these needs, increasing perceived usefulness and satisfaction [125]. Conversely, social sciences
and humanities involve subjective analysis, critical reflection, and personal interpretation,
areas where human educators excel. Thus, students in these disciplines may show lower satis-
faction and more negative attitudes towards ChatGPT.
Additionally, significant rating differences were found between students from different
income regions (Fig 14). Students from high income regions were more likely to emphasise
their interest in using ChatGPT (72%), with a mean score of 3.85. In contrast, students from
low income regions focused more on the benefits of everyday life (74%, 3.87). This highlights a
Fig 12. Agreement on ChatGPT satisfaction and attitude (top two box scores and average values).
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difference in how students from different income regions perceive and use ChatGPT, with
high income students valuing its innovative aspects and low income students valuing its practi-
cal help. These differences can be attributed to varying levels of access to technology, expecta-
tions, and educational support. Moreover, students from low or lower middle income regions
rate ChatGPT as the most useful, easy to use, quality, accurate, and important source of infor-
mation. This may be because it fills critical gaps in their educational resources, which are often
limited. On the other hand, students from high income regions feel the most in control, possi-
bly due to their higher familiarity with technology and more robust support systems. The larg-
est difference between the mean maximum and minimum values (0.71) was found in the
interaction with ChatGPT compared to their peers, where students from low income regions
showed higher agreement, with 37% agreeing or strongly agreeing.
Fig 14. Differences in agreement on satisfaction and attitude (top two box scores by income region).
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Fig 13. Differences in agreement on ChatGPT satisfaction and attitude (top two box scores by field of study).
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Furthermore, the results highlight significant differences in satisfaction and attitudes
towards ChatGPT based on various demographic factors. Male students reported higher levels
of satisfaction and more positive attitudes than female students in all statements, echoing find-
ings by Schepman and Rodway [126], who reported more positive AI attitudes in men, which
may be due to greater comfort with technology. First level students generally reported higher
levels of satisfaction and more positive attitudes regarding ChatGPT than students at later lev-
els. Blended learning students and those living in urban areas find ChatGPT more useful and
easier to interact with, probably due to better access to digital resources. Economically disad-
vantaged students reported high levels of satisfaction with the accuracy and usefulness of
ChatGPT, indicating its central role in bridging educational gaps but also the risk of a social/
digital divide. These differences highlight the importance of tailoring AI tools to meet the
diverse needs of students from different demographic backgrounds. One of the main concerns
with using ChatGPT is satisfaction with its accuracy for academic tasks, particularly with com-
plex or context-specific queries and issues related to academic integrity [50]. Results of our
study showed that 38% (3.16) of students were satisfied with the accuracy of the information
provided by ChatGPT. Satisfaction with the accuracy of ChatGPT was higher among male stu-
dents and first level students. More positive attitudes towards AI may be associated with male
satisfaction. On the other hand, the satisfaction of first level students may be explained by the
fact that younger students have less experience with alternative academic tools in contrast to
higher level students, who have more experience with academic resources and be more critical
of the accuracy of the information they receive.
Study issues and outcomes. Using ChatGPT may have several benefits for students, as
they may receive personalized instruction and feedback as well as support for various types of
academic tasks [56]. However, there are also concerns about the limitations, challenges, and
possible negative effects of ChatGPT use, such as student access to unreliable information and
overreliance on the technology [56,127,128]. In our study, the average level of student agree-
ment regarding the benefits of using ChatGPT for various learning tasks and outcomes ranged
from 3.11 (facilitating completion of internship and improving employability) to 3.75
(improving general knowledge) (Fig 15). Most students tended to agree that ChatGPT could
improve their general knowledge, with nearly 69%. This was followed by the view that
Fig 15. Agreement on study issues and outcomes related to ChatGPT (top two box scores and average values).
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ChatGPT could improve their specific knowledge and enhance their access to knowledge
sources, both endorsed by nearly 63% of the students. Most students also agreed that ChatGPT
could increase their study efficiency (59%), enhance their learning experience (58%), improve
their ability to meet assignment deadlines, improve the quality of their assignments, and facili-
tate completing their studies, as emphasized by 57% of students.
Students in all fields of study agreed at rates exceeding 50% that using ChatGPT could
improve their general and specific knowledge, enhance their access to knowledge sources,
their ability to meet assignment deadlines, and their learning experience, increase their study
efficiency, improve their assignment quality, and facilitate completion of activities outside the
classroom and their academic development (Fig 16). On the other hand, less than 40% of stu-
dents in all disciplines thought that ChatGPT could help them complete their internships or
improve their employability. Students in applied sciences exhibited the highest scores among
disciplines for all statements on study-related issues and outcomes, while those in social sci-
ences and in arts and humanities tended to show the lowest scores. The largest mean difference
in agreement levels was currently observed in ChatGPT enhancement of learning experience,
with a score of 0.20 higher for applied sciences compared to social sciences students. Other
large and significant differences between the same group of students include completion of
activities (0.19) and an increase in study efficiency (0.17). In addition, applied sciences stu-
dents expressed more positive views than arts and humanities students about ChatGPT
enhancing knowledge access (0.20), improving exam readiness (0.19), and improving grades
(0.18). Finally, a large difference was found in improving employability, with a score of 0.19
higher for students in applied compared to those in natural and life sciences.
Statistically significant differences in scores could also be observed when considering the
income regions (Fig 17). Overall, students from low income regions tended to express higher
levels of agreement with the statements compared to students from high income regions. The
highest agreement scores for statements related to improving engagement in class discussions,
facilitating internship completion, and supporting personal development were observed
among students from low income regions, while the lowest scores were found among students
from high income regions. The most significant differences between these groups were in the
areas of improving class discussion engagement (0.62), facilitating internship completion
Fig 16. Differences in agreement on study issues and outcomes related to ChatGPT (top two box scores by field of
study).
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(0.58), and supporting personal development (0.57). Independent of the income group,
approximately 69% of students used ChatGPT to improve their general knowledge. Rural stu-
dents exhibited significantly higher scores regarding ChatGPT facilitating their personal devel-
opment and providing personal education compared to urban students, but the difference is
small.
There were significant gender differences favoring male students in all statements. Regard-
ing study issues, the largest mean score difference was found in providing students with per-
sonalized education and improving study efficiency (0.18). When examining statements
relevant to student personal and professional development, we found the largest differenceđin
improving employability (0.21). Many of the answers given to study issues and outcomes (for
11 out of 20 statements) were significantly affected by the level of study of the participating stu-
dents. However, differences in mean scores tend to be small. In significant differences, out-
comes of using ChatGPT were pointed to the greatest extent by first-level students. Almost all
the possible study outcomes listed were selected in the smallest degree by third-level students.
The difference determined by the level of study was the largest, 0.28 (the mean score is 3.37 for
first-level students and 3.09 for third-level students), regarding the possibility of ChatGPT
improving student’s grades. For all other potential study outcomes, the difference varied
between 0.01 (facilitating personal development) and 0.19 (improving the quality of
assignments).
Skills development. Skills development using a single powerful instrument, such as
ChatGPT, could provide a revolutionary alternative to traditional learning [6,129–131]. Bit-
zenbauer [132] discusses some fascinating applications of such inventive learning in the devel-
opment of skills required to comprehend complicated subjects in the classroom. Our results
revealed ChatGPT’s potential effectiveness in enhancing various skills, though to varying
extents, as also suggested by the previous research [133–136]. More than 50% of students
agreed that ChatGPT has the potential to improve their AI literacy, digital communication,
and digital content creation skills (Fig 18). Conversely, less than 40% of students agreed that
ChatGPT has the potential to improve interpersonal communication, decision-making skills,
numeracy, native language proficiency, and critical thinking skills. The varying effectiveness of
Fig 17. Differences in agreement on study issues and outcomes related to ChatGPT (top two box scores by income
region).
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ChatGPT in enhancing different skills is due to its strong alignment with digital skills, which
involve information processing and content generation. In contrast, interpersonal communi-
cation, decision-making, and critical thinking require nuanced human interactions, emotional
intelligence, and higher-order cognitive processes that are challenging for AI to fully replicate.
Additionally, learning these complex skills often benefits from diverse, hands-on experiences
and human feedback, which ChatGPT may not adequately provide.
The perceptions of ChatGPT’s potential to facilitate skills development varied significantly
by field of study, impacting all skills except creativity (Fig 19). Overall, applied sciences stu-
dents viewed ChatGPT as having a higher potential for facilitating the development of various
skills compared to students from other fields. This was especially true for programming skills,
where the difference between applied sciences students and arts and humanities students was
Fig 18. Agreement on the ChatGPT potential for skills development (top two box scores and average values).
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Fig 19. Differences in agreement on the ChatGPT potential for skills development (top two box scores by field of
study).
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most pronounced (0.34), followed by AI skills (0.16) and numeracy proficiency (0.14). How-
ever, despite generally perceiving a lower overall potential for skills development, arts and
humanities students believed ChatGPT could significantly enhance interpersonal, critical
thinking, and decision-making skills. The variations in perceptions of ChatGPT’s potential to
facilitate skills development across different fields are influenced by the nature of the skills
emphasized in each field. Applied sciences students viewed ChatGPT as highly beneficial for
technical skills like programming, AI, and numeracy due to its ability to provide concrete
assistance. In contrast, arts and humanities students, despite perceiving a lower overall poten-
tial for skills development, recognized ChatGPT’s significant enhancement of interpersonal,
critical thinking, and decision-making skills, which are crucial in their curricula.
In general, students from lower and lower middle income regions found more potential in
ChatGPT for skills development compared to students from high and upper middle income
regions, particularly regarding interpersonal communication (0.62), critical thinking (0.57),
decision-making (0.47), and creativity skills (0.46), except for facilitating foreign language pro-
ficiency, which was not significant (Fig 20). The variance in perception of ChatGPT’s potential
for skills development between students from different income regions could be attributed to
disparities in access to educational resources and support systems. Students from high and
upper middle income regions often have access to private tutoring, advanced technology, and
well-funded schools, reducing their reliance on tools like ChatGPT. Conversely, students from
lower and lower middle income regions may find ChatGPT particularly valuable for develop-
ing skills such as interpersonal communication, critical thinking, decision-making, and crea-
tivity, as they have fewer alternative resources.
The rest of the demographic factors present insightful results. Contrasting to findings from
Hu et al. [137], Park [49], Strzelecki [36], and Xu et al. [53], in our research, statistically signifi-
cant differences according to gender have been observed. Males perceived ChatGPT to provide
more overall support than females in various types of skills development, except for academic
writing, typing proficiency, and digital communication abilities, where the results were not sig-
nificant. Resonating with Moro-Egido’s [138] findings, gender differences were more pro-
nounced in analytical and problem-solving skills, while communication skills showed
comparable values across genders. The level of study revealed differences among students,
Fig 20. Differences in agreement on the ChatGPT potential for skills development (top two box scores by income
region).
https://doi.org/10.1371/journal.pone.0315011.g020
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aligning with Hu et al. [137] and Xu et al. [53]. First-level students tended to state that
ChatGPT provides stronger support for analytical and problem-solving skills, whereas third-
level students saw its potential in developing academic writing and foreign language profi-
ciency. Regarding the mode of study, online and blended learning students generally perceive
greater potential in ChatGPT for skills development compared to those in traditional modes,
aligning with Jiang and Cheong [139]. Moreover, students in rural areas saw greater potential
in ChatGPT for skills development, except for academic writing proficiency, which was more
emphasized by urban students. In terms of economic position, an interesting “u-curve” is
observed, with ‘significantly below average’ and ‘significantly above average’ having the great-
est values and ‘average’ frequently in the middle. This is evident in interpersonal communica-
tion, native language proficiency, decision-making, and critical thinking skills. This
perspective adds to studies such as Scherr et al. [140], which identified ChatGPT as increas-
ingly useful for lower economic statuses.
Labor market and skills mismatch. AI, including ChatGPT, as an important component
of technological change, has various impacts on the labor market [83,87,141]. In our survey,
students were asked about general challenges in the labor market connected with ChatGPT
and the ability of ChatGPT to address potential skills mismatch (Fig 21). Students believed
that the wide implementation of AI is likely to modify the future labor market. The highest
percentage of students agreed that ChatGPT increases the demand for employees with AI-
related skills (61%), facilitates remote work (60%), and requires employees to acquire new
skills (59%). Besides, students believed that ChatGPT changes the nature of jobs (59%),
requires employees to possess knowledge about AI (59%), which is consistent with the findings
of Acemoglu et al. [141], Zarifhonarvar [142] and Cedefop [143]. However, students did not
consider that implementing AI in various economic sectors could affect the unemployment
rate in the labor market (37%). Consequently, the findings are in line with other studies sug-
gesting that the primary impact of AI is to redesign parts of the working tasks rather than
replacing entire jobs [144]. Due to changing tasks and the emergence of new job roles, workers
need to acquire new or updated skills [143,145,146]. Regarding other aspects of the labor
markets, only a minority of students considered that ChatGPT enhances the connection
between higher education and the labor market (43%) and increases inequality between
Fig 21. Agreement on the ChatGPT potential for labor market and skills mismatch (top two box scores and
average values).
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younger and older employees (47%), contradicting previous findings that jobs of young people
are most exposed to automation [145]. Regarding skills mismatch, only a minority of students
agreed with the statement that ChatGPT resolves skills gaps (41%) and skills obsolescence
(38%), and reduces under-skilling (37%), and skill shortages (36%). However, the research by
Komp-Leukkunen [87] has shown an ambivalent scenario where ChatGPT can replace soft-
ware engineers to a large extent.
Ratings of challenges in the labor market of ChatGPT between representatives of different
fields of study varied from 2.97 to 3.63 (Fig 22). The largest difference between fields of study
concerned the statement that ChatGPT improves employee productivity (0.13) between stu-
dents of applied sciences and social sciences. Arts and humanities students frequently noted
that ChatGPT increases the demand for employees with AI-related skills (62%) and requires
AI knowledge (62%). The popularity of AI knowledge requirements varied between 58% and
62%, depending on the field. Applied sciences students viewed ChatGPT most positively, cit-
ing benefits like facilitating remote work (61%), requiring new skills (60%), changing job
nature (60%), improving productivity (59%), and reducing workload (58%), but they were less
positive about reducing inequality (44%), resolving skills gaps (42%), and addressing skills
shortages (37%). Social sciences students were positive about increased demand for AI-related
skills (61%) and reduced skills shortages (37%) but concerned about increased inequality
(49%) and job reduction (39%). They saw improved productivity (53%) as a moderate benefit.
Arts and humanities students were optimistic about ChatGPT creating new jobs (53%),
improving innovation (52%), and connecting education to the labor market (44%), but skepti-
cal about reducing the workload (55%), resolving skill obsolescence (36%), and reducing
underskilling (35%). Natural and life sciences students were generally negative, with fewer see-
ing benefits like job creation (46%) and innovation improvement (48%). The smallest percep-
tion gap was between applied sciences and natural and life sciences students (0.06), with over
40% using ChatGPT across fields. Differences likely stem from varying views on ChatGPT’s
role in developing critical thinking skills [76].
Concerning income region, students most often indicated that ChatGPT increases demand
for employees with skills related to AI, namely the highest from the high income regions (64%)
and the lowest from the low income (52%) (Fig 23). Students from high income regions
Fig 22. Differences in agreement on the ChatGPT potential for labor market and skills mismatch (top two
box scores by field of study).
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believed that ChatGPT would require employees to acquire new skills, while students in the
upper middle income regions were facilitating remote work (61%), but students from the low
income regions most frequently declared that ChatGPT reduces employee workload (64%).
The two largest differences between high and low income regions were found in the agreement
that ChatGPT has an impact on: (1) the need for new skills (0.30), where 63% of high income
students agreed, and only 46% of low income students agreed, and (2) improving employee
innovation (0.23), where low income students (61%) had higher confidence than high income
students (50%).
Gender differences showed that males were more likely than females to select ‘agree’ or
‘strongly agree’ for all statements with statistically significant differences. This may reflect
greater awareness among male students of the impact on the future labor market. Significant
differences in terms of the level of study could be seen in only half of the statements. Specifi-
cally, the most significant difference was observed in the challenge that ChatGPT alters the
nature of jobs (0.24) and necessitates employees to acquire new skills (0.27), with third level
students experiencing this impact more strongly compared to those at the first level. Regarding
the area in which they live, particularly in relation to the labor market, the urban area consis-
tently received the highest scores across all statements, while the rural area scored highest on
skills mismatch, but only in five statements.
Emotions. ChatGPT has been depicted by previous studies as a tool that arouses mixed
feelings in its users [22,92,93]. Therefore, our research aimed to explore also how often stu-
dents felt eight positive (i.e., hope, calmness, relief, happiness, pride, surprise, curiosity, excite-
ment) and seven negative emotions (i.e., boredom, sadness, shame, anger, anxiety, confusion,
frustration) while using ChatGPT (Fig 24). On average, positive emotions ranged from 2.54 to
3.43, and negative emotions from 1.73 to 2.54. It can be concluded that the students do not
experience a big change in their emotions. In most cases, they answered rarely or sometimes
on average. The most frequently experienced emotions were curiosity (52%), calmness (47%),
hope (39%), and happiness (39%), while sadness (6%), shame (8%), and anger (8%) were those
experienced least frequently. Among positive emotions, pride was the least frequent (23%),
and among negative emotions, confusion was the most frequent (18%). Such results suggest
Fig 23. Differences in agreement on the ChatGPT potential for labor market and skills mismatch (top two
box scores by income region).
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that, overall, while using ChatGPT, students tend to feel more positively than negatively,
which is also in line with previous findings [93]. Curiosity is the prevalent emotion, a result
that can be explained by the relative novelty of this tool and AI in general.
The results comparing the emotions experienced by students from different fields of study
when using ChatGPT show clear differences in percentage between positive and negative emo-
tions, with a prevalence of the former, in general, tending to feel more positively than nega-
tively (Fig 25). For all emotions considered, the percentages in the different fields of study
were relatively uniform. Considering positive emotions, the highest percentages were found
for students from applied sciences. For example, they got the highest percentages in feelings
such as curiosity (55%), calmness (50%), happiness (41%), hope (41%), relief (38%), excite-
ment (35%), and surprise (31%). Contrastingly, when considering negative feelings, data
showed that students from arts and humanities seemed to be more likely to experience
Fig 24. Frequency of emotions felt when using ChatGPT (top two box scores and average values).
https://doi.org/10.1371/journal.pone.0315011.g024
Fig 25. Differences in frequency of emotions felt when using ChatGPT (top two box scores by field of study).
https://doi.org/10.1371/journal.pone.0315011.g025
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emotions such as anxiety (13%), boredom (13%), shame (9%), anger (8%), and sadness (8%)
when using ChatGPT. Finally, it is important to mention that the largest difference between
the fields of study was for calmness (0.21), with the highest values for applied sciences and the
lowest for natural and life sciences. We could speculate that specific technical competences of
students of the applied sciences could increase their perception of control when using
ChatGPT and, in turn, favor their calmness. This interpretation should be further investigated
by examining other data.
In addition, the results showed notable differences between the specific type of positive
emotions experienced depending on the income region type (Fig 26). Interestingly, low and
lower middle income regions, compared with high and upper middle income regions, experi-
enced more frequently activating positive emotions such as happiness and excitement. Also,
students from low and lower middle income regions, compared with those from high and
upper middle income regions, reported to feel more hopeful and proud. On the other hand,
the most frequently experienced emotions for high and upper middle income regions were
curiosity (55% and 50%) and calmness (51% and 40%). Overall, these results indicate that the
experience associated with the use of ChatGPT is generally positive, generating primarily posi-
tive rather than negative emotions in students, regardless of income. However, using AI might
be more stimulating for lower than higher income groups as they probably are less likely to be
exposed to these types of experiences.
The results comparing the emotions experienced by students from different modes of study
showed that students from traditional, online, and blended modes felt mostly positive emo-
tions. However, we found out that students involved in traditional learning contexts usually
felt worse than others when using ChatGPT despite experiencing anxiety less frequently. Liv-
ing in urban areas affected students’ emotions in mixed ways. Negative emotions such as bore-
dom, sadness, shame, anger, anxiety, confusion, and frustration were significantly lower for
students living in urban areas compared to those living in rural or suburban areas; neverthe-
less, the same trend was also found for positive emotions such as hope, calmness, happiness,
pride, and surprise, with lower scores for students living in urban areas. These findings could
suggest a somewhat more intense emotional engagement for these students, combining
together both positive and negative feelings with related effects. However, students who lived
Fig 26. Differences in frequency of emotions felt when using ChatGPT (top two box scores by income region).
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in urban areas, as well as suburban and rural areas, declared that they experienced positive feel-
ings more frequently than negative feelings; for all of them, the most frequent emotions were
calmness, happiness, and hope. Finally, regarding gender, females tended to show higher levels
of positive emotions and lower levels of negative emotions compared to males, with some
exceptions (i.e., anger and frustration).
Regression analysis results
Ordinal logistic regression was utilized to empirically validate the impact of various factors
associated with ChatGPT aspects on students’ usage patterns for specific academic tasks, par-
ticularly those most frequently used by students, such as brainstorming, summarizing, and
academic writing, as suggested by the highest mean values from the first part of the analysis.
Therefore, different ordinal regression models (Eq 1) with three dependent variables were esti-
mated (Y
1
=Brainstorming,Y
2
=Summarizing and Y
3
=Academic writing) with 14 main inde-
pendent variables of interest (X
1
=Simplify complex information,X
2
=Summarize extensive
information,. . .,X
14
=Calm). Moreover, socio-demographic and geographic characteristics
were used as control variables in all three estimated models. The models estimated the condi-
tional probability P(Y
i
�j|X
1
, X
2
,. . ., X
p
) that dependent variables were less or equal to jgiven
the values of independent variables (X
1
, X
2
,. . ., X
p
). The value jranges from 1 to k−1 where k
is the number of ordered categories of the dependent variables Y
i
. In this case, there are 5 cate-
gories in the individual dependent variable (k= 5) as their values range from 1 = never 1 to 5 =
always. Accordingly, the models estimate coefficients associated with independent variables
(β
1i
,β
2i
,. . .,β
pi
) and the intercepts (α
ji
) for j= 1, 2, . . .,k−1. Since the interpretation of control
variables and intercepts is not the main focus in this context, they are omitted from the presen-
tation of the ordinal regression results.
P Yi�jjX1;X2;. . . ;Xp
¼expðaji þb1iX1þb2iX2þ. . . þbpiXpÞ
1þexpðaji þb1iX1þb2iX2þ. . . þbpi XpÞfor i ¼1;2;3ð1Þ
Prior to parameter estimation, two key assumptions of ordinal logistic regression were veri-
fied, namely the proportional odds assumption and multicollinearity. The proportional odds
assumption was tested using the test of parallel lines, which was significant (p <0.001) for all
three estimated ordinal logistic regression models, indicating that the regression slopes differ
significantly across the levels of the dependent variable for all models [147]. However, this test
is considered anti-conservative because it almost always results in rejecting the proportional
odds assumption [148], especially when there are many independent variables [149] or when
the sample size is large [150]. Moreover, multicollinearity was tested using several approaches.
Initially, a Spearman correlation between the independent variables presented in the support-
ing information (S1 Table) did not indicate any strong relationship between them, suggesting
there were no issues of multicollinearity. The severity of multicollinearity was further tested
using multicollinearity diagnostics. The VIF values ranged between 1.1 and 2.0, and TOL val-
ues ranged between 0.5 and 0.9. Since VIF should not exceed 10 and TOL should be above 0.1,
all of the values were considerably within the acceptable thresholds, confirming the absence of
multicollinearity [151].
Due to the complete case analysis approach adopted in the ordinal regression, the number
of valid full student responses varied across the ordinal logistic regression models. The model
predicting ChatGPT usage for brainstorming included 11,333 responses, for summarizing
included 11,339 responses, and for academic writing included 11,343 responses. Assuming
that the data were missing at random, parameter estimation was carried out. Finally, the good-
ness-of-fit statistics for the proposed empirical model proved to be adequate, as suggested by
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Nagelkerke R
2
values of 0.134, 0.170, and 0.156 for each model, respectively [152]. The results
of the ordinal logistic regression are presented in Table 2.
The results of the ordinal logistic regression revealed key insights into the influence of
selected factors related to ChatGPT on students’ usage patterns across different use cases, such
as brainstorming, summarizing, and academic writing. Specifically, the ability to simplify com-
plex information consistently showed significant positive effects on the frequency of using
ChatGPT across all three use cases, while the ability to summarize extensive information had a
significant positive impact on two of the use cases. Both factors had the most substantial impact
on the frequency of using ChatGPT for summarizing (β= 0.220; p <0.001 and β= 0.402;
p<0.001, respectively). Conversely, the potential of ChatGPT to enhance access to sources of
knowledge appeared to have a negative and statistically significant impact on using ChatGPT
for summarizing (β= -0.057; p <0.05), while it had a positive and statistically significant impact
on academic writing (β= 0.108; p <0.001). Additionally, the potential of ChatGPT to improve
general knowledge had a positive and significant effect on the frequency of using ChatGPT
across all three use cases, with the highest impact observed in brainstorming (β= 0.124;
p<0.001). This was likely because simplifying complex information and summarizing extensive
information directly enhanced comprehension and efficiency, making these skills particularly
valuable for summarizing tasks. In contrast, accessing knowledge sources might have introduced
more information than necessary for summarizing, but it was beneficial for in-depth academic
writing while improving general knowledge broadly supported brainstorming activities.
Table 2. Ordinal logistic regression for factors influencing the ChatGPT usage.
ChatGPT aspect Selected ChatGPT-related factor ChatGPT Usage
Brainstorming Summarizing Academic writing
Coeff. Std.
Error
Coeff. Std.
Error
Coeff. Std.
Error
Capabilities ChatGPT can simplify complex information. 0.190*** 0.027 0.220*** 0.027 0.180*** 0.027
ChatGPT can summarize extensive information. 0.032 0.027 0.402*** 0.027 0.160*** 0.027
Regulation and ethical
concerns
Students should take appropriate measures to protect their own
personal information.
-0.104*** 0.020 -0.132*** 0.020 -0.222*** 0.020
ChatGPT should be subject to university/faculty ethical guidelines. -0.002 0.017 -0.069*** 0.017 -0.090*** 0.017
Satisfaction and attitude Using ChatGPT is interesting to me. 0.215*** 0.025 0.150*** 0.025 0.215*** 0.025
ChatGPT can help with things in everyday life. 0.163*** 0.020 0.173*** 0.020 0.123*** 0.020
Study issues and outcomes ChatGPT can enhance my access to the sources of knowledge. -0.019 0.026 -0.057*0.026 0.108*** 0.026
ChatGPT can improve my general knowledge. 0.124*** 0.028 0.085** 0.028 0.105*** 0.028
Skills development ChatGPT can improve my artificial intelligence literacy skills 0.079*** 0.021 0.104*** 0.021 0.136*** 0.022
ChatGPT can improve my digital content creation skills 0.130*** 0.022 0.103*** 0.022 0.089*** 0.022
Labor market and skills
mismatch
ChatGPT will increase the demand for employees with skills related
to artificial intelligence.
0.048*0.022 0.004 0.022 0.025 0.022
ChatGPT will facilitate remote work. 0.027 0.022 0.008 0.022 -0.015 0.022
Emotions Curiosity 0.107*** 0.017 0.075*** 0.017 0.008 0.017
Calmness 0.069*** 0.015 0.067*** 0.015 0.072*** 0.015
Nagelkerke R
2
0.134 0.170 0.156
N 11,333 11,339 11,343
Note:
*p<0.05;
** p<0.01;
*** p<0.001.
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In most examined cases, regulation and ethical concerns seemed to have a negative impact
on the frequency of ChatGPT use. Students’ belief that they should take appropriate measures
to protect personal information had a negative and statistically significant impact on the fre-
quency of using ChatGPT across all three use cases, with the strongest negative impact
observed in academic writing (β= -0.222; p <0.001). Despite still being statistically significant,
the impact of the belief that ChatGPT should be subject to university/faculty ethical guidelines
on academic writing and summarizing was not as prominent. Regulation and ethical concerns
negatively impacted ChatGPT use among students, particularly in academic writing, due to
heightened awareness and caution around data privacy and academic integrity. These con-
cerns led students to limit their ChatGPT use, especially for tasks requiring originality and
intellectual effort, to avoid potential academic misconduct and focus on their own develop-
ment. Conversely, the impact on tasks like summarizing was less pronounced, indicating some
comfort in using AI for less critical academic activities.
The perceived ability of ChatGPT to potentially facilitate skills development had significant
implications for the frequency of its use in all three use cases. The most pronounced effects
were observed in two specific instances. The first instance was the impact of ChatGPT’s per-
ceived ability to enhance AI literacy skills, which was associated with an increased frequency
of using ChatGPT for academic writing (β= 0.136; p <0.001). The second instance was the
impact of ChatGPT’s perceived ability to enhance digital content creation skills, which was
associated with an increased frequency of using ChatGPT for brainstorming (β= 0.130;
p<0.001). On the other hand, the least prominent effects were observed for ChatGPT’s per-
ceived ability to enhance AI skills on the use of ChatGPT for brainstorming (β= 0.079;
p<0.001) and its perceived ability to enhance digital content creation skills on academic writ-
ing (β= 0.089; p <0.001). However, regarding labor market and skills mismatch, there was
only one instance where the perceived potential of ChatGPT to increase demand for employ-
ees with AI-related skills had a significantly positive effect on using ChatGPT for brainstorm-
ing (β= 0.048; p <0.05). The varying impacts of ChatGPT’s perceived ability to facilitate skills
development depended on how well the skills aligned with specific activities. Users who saw
ChatGPT as enhancing AI literacy used it more for academic writing, while those who believed
it improved digital content creation used it more for brainstorming. Weaker effects were
observed when the skills and activities were less directly related, while the labor market effect
suggested users utilized ChatGPT for brainstorming to develop marketable AI skills.
Finally, emotional factors played a significant role in determining the frequency of
ChatGPT usage, with an exception in the context of the impact of curiosity on academic writ-
ing. Students who felt curious and calm while interacting with ChatGPT tended to use it more
frequently, with curiosity having the highest observed effect on the use of ChatGPT for brain-
storming (β= 0.107; p <0.001), while its impact on other use cases was less pronounced. The
exploratory nature of brainstorming aligned well with curiosity, leading to this high impact,
while it had a lesser effect on using ChatGPT for academic writing, which requires a more
structured and focused approach. Additionally, feeling calm when using ChatGPT generally
enhanced user engagement across various tasks.
Discussion
The introduction of ChatGPT in November 2022 marked a pivotal moment for the integration
of AI in higher education. Within its first year, ChatGPT gained widespread popularity among
students due to its advanced natural language processing capabilities, which enable smooth
and intuitive user interactions [153]. In order to capture early perceptions of higher education
students, a global survey was conducted between October 2023 and February 2024, offering a
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comprehensive global perspective on its initial acceptance and potential impact within educa-
tional and broader contexts from a students’ point of view. After a year and a bit more of
ChatGPT’s existence, most students have used ChatGPT, which points to its popularity within
the higher education context.
Students used ChatGPT mainly for brainstorming, summarizing texts, finding research
articles, and writing. These use cases align with the tool’s strengths in generating ideas, orga-
nizing content, and providing feedback on drafts. For instance, Menon and Shilpa [28] high-
light that AI tools such as ChatGPT can assist in formulating research questions, summarizing
information, and offering writing support in academic contexts. The less frequent use for pro-
fessional and creative writing could be due to the personal and nuanced nature of these tasks,
which often require a human touch. Students found ChatGPT particularly useful in simplify-
ing complex information and summarizing extensive content, thereby enhancing their under-
standing and managing large volumes of information more efficiently and effectively. These
findings are supported by Bouteraa et al. [23] and Chan and Hu [30], who noted the tool’s
effectiveness in clarifying technical details and summarizing vast amounts of data. However,
students expressed concerns about the reliability of the information provided by ChatGPT and
its support for traditional classroom learning, echoing sentiments in studies by Biswas [31]
and Mai et al. [108]. There is a unanimous agreement among students on the need for AI sys-
tem regulations at various levels (international, national, organizational, and faculty) due to
concerns about ChatGPT promoting cheating, plagiarism, and social isolation. These concerns
are well-documented in the literature. For instance, AlAfnan et al. [1] and Fu¨tterer et al. [22]
discuss the ethical implications and potential misuse of ChatGPT in academic settings, empha-
sizing the importance of establishing clear guidelines and regulatory frameworks.
In everyday life, students generally found ChatGPT interesting and useful, with over half
valuing its control and assistance features. However, some students preferred information
from peers and teachers, which indicates a preference for human expertise and interaction
over AI-generated content. This preference is discussed in studies by Sullivan et al. [9] and
Castonguay et al. [154], which highlight the mixed feelings students have towards AI tools in
educational settings. In our research, ChatGPT was perceived to enhance students’ knowledge,
access to knowledge sources, learning experiences, study efficiency, and chances of getting
good grades. Most students agreed that ChatGPT could improve their general and specific
knowledge, enhance their learning experience, and increase their study efficiency. This is sup-
ported by findings from Strzelecki [36], which emphasizes the tool’s potential to positively
impact academic performance when used appropriately.
Students viewed ChatGPT as an efficient tool for potentially improving AI literacy, digital
communication, and digital content creation skills. However, its effectiveness was less promi-
nent in enhancing interpersonal communication, decision-making skills, numeracy, native
language proficiency, and critical thinking skills. Studies by Tiwari et al. [29] and Chiu [18]
support these findings, highlighting ChatGPT’s strengths in digital competencies while noting
the areas where traditional learning methods remain superior. Regarding the labor market,
students from our research believed that AI would increase the demand for related skills and
facilitate remote work without significantly affecting unemployment rates. They emphasized
the importance of acquiring new skills to remain competitive in a technologically evolving job
market. Research by Chen et al. [83] and Komp-Leukkunen [87] indicates that jobs involving
writing and programming are more susceptible to being impacted by AI, underscoring the
need for new competencies in the workforce. Emotionally, students generally felt more posi-
tive than negative while using ChatGPT, with curiosity and calmness being the most common
emotions. This positive emotional response suggests that students are open to integrating AI
tools like ChatGPT into their academic and daily routines. Abbas et al. [91] and Mamo et al.
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[93] report similar findings, noting that the immediate benefits and convenience of using
ChatGPT contribute to its positive reception among students.
However, students’ perceptions of various ChatGPT aspects were found to differ across
fields of study and income regions, as well as other selected socio-demographic and geographic
characteristics, with the most notable differences further discussed. Applied sciences students
showed higher satisfaction with ChatGPT, appreciating its capabilities in simplifying complex
information and providing clear technical support. They found ChatGPT particularly useful
for technical communication and problem-solving tasks. In contrast, students in the arts and
humanities were more critical of ChatGPT’s ability to handle nuanced and interpretive lan-
guage, reflecting a preference for human interaction in these fields. Social sciences students
also exhibited lower satisfaction with ChatGPT compared to their peers in applied sciences
due to the subjective analysis required in their disciplines [23]. Perceptions of ChatGPT also
varied significantly across income regions. Students from low income regions tended to
express higher agreement with the benefits of ChatGPT, particularly in improving class discus-
sion engagement, facilitating internship completion, and aiding personal development. These
students relied more on cost-effective digital tools like ChatGPT to supplement their limited
educational resources. Conversely, students from high income regions valued ChatGPT’s
innovative aspects and its capability to understand and follow human instructions, indicating
a higher familiarity and comfort with advanced technological tools, as pointed out by Han and
Kumwenda [109] or Alharbi [110].
Gender differences were evident in students’ perceptions of ChatGPT. Male students gen-
erally reported higher levels of satisfaction and more positive attitudes towards ChatGPT
compared to female students. This difference might be attributed to a greater comfort and
familiarity with technology among male students. Female students, on the other hand,
expressed more concerns about the ethical implications and potential misuse of ChatGPT,
such as facilitating plagiarism and spreading misinformation, which is in line with the find-
ings of Xu et al. [53] and Schepman and Rodway [126]. The level of study also influenced
students’ perceptions of ChatGPT. First level students were more likely to perceive ChatGPT
as beneficial for their academic development, improving grades, and enhancing study effi-
ciency. This can be attributed to their greater need for academic support and their openness
to adopting new technologies. In contrast, higher level students who have developed their
own learning strategies and have more experience with academic tools tend to be more criti-
cal of ChatGPT’s accuracy and reliability, aligning with the findings of Kelly et al. [155] and
Xu et al. [53]. Students engaged in online and blended learning programs reported finding
ChatGPT more useful and easier to interact with than those in traditional learning environ-
ments. This may be due to the higher integration of digital tools in online education, which
aligns well with ChatGPT’s functionalities. As suggested by Jiang and Cheong [139], these
students appreciate the personalized learning experience and real-time feedback provided
by ChatGPT, which enhances their learning outcomes and study efficiency. Students from
rural areas demonstrated higher usage of ChatGPT and perceived greater benefits from its
use compared to urban students. This higher perception among rural students is likely due
to limited access to educational resources, making ChatGPT a valuable tool for supplement-
ing their learning. However, the differences between urban and rural students’ perceptions
were generally small, similarly as noted by Javaid et al. [60]. Economic status significantly
shapes students’ perceptions of ChatGPT. Students from economically disadvantaged back-
grounds tended to use ChatGPT more frequently and reported higher levels of satisfaction
with its capabilities, particularly in enhancing their study efficiency and providing personal-
ized support. In contrast, students from higher economic backgrounds showed a greater
appreciation for ChatGPT’s ability to handle complex instructions and its innovative
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Higher education students’ perceptions of ChatGPT: A global study of early reactions
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features, reflecting their familiarity with advanced technological tools, as also pointed out by
Scherr et al. [140].
Additionally, several other factors highlighted in the existing literature can explain students’
interaction and engagement with ChatGPT, including performance expectancy, effort expec-
tancy, social influence, facilitating conditions, privacy concerns, perceived interactivity, per-
ceived human touch, and more [28]. The results of the ordinal logistic regression in our
research showed that various factors had significantly influenced ChatGPT usage across the
tasks for which students used it most frequently, such as brainstorming, summarizing, and
academic writing. Students who were more aware of ChatGPT’s capabilities, such as simplify-
ing complex information and summarizing extensive content, more frequently used ChatGPT,
particularly for summarizing. While ChatGPT’s potential to enhance access to knowledge neg-
atively affected its use for summarizing, it positively impacted its use for academic writing, and
its potential to improve general knowledge boosted usage across all tasks, especially brain-
storming. Moreover, students who expressed greater regulation and ethical concerns about
ChatGPT less frequently used ChatGPT across all tasks, particularly for academic writing, due
to data privacy and academic integrity concerns. While the perceived ability of ChatGPT to
facilitate skills development (AI literacy and digital content creation skills) positively affected
the frequency of its use across all three cases, its perceived potential to increase demand for
employees with AI-related skills had a positive effect only on using ChatGPT for brainstorm-
ing. Finally, emotional factors, such as curiosity and feeling calm, also enhance the frequency
of students’ ChatGPT engagement, especially for brainstorming. The results confirm that stu-
dents’ usage patterns of ChatGPT varied across different factors, supplementing the findings
from other studies (e.g., Bouteraa et al. [23], Garrel & Mayer [107], Romero-Rodrı
´guez et al.
[156], Shoufan [85], Strzelecki [41]) that found relationships between usage and students’ per-
sonal traits, such as habit, hedonic motivation, and personal innovativeness.
Conclusion
The global study reveals how higher education students perceive ChatGPT in its early stages.
Students view ChatGPT as a valuable tool primarily for brainstorming, summarizing texts, and
academic writing, appreciating its ability to simplify complex information. However, they
express skepticism about its reliability and effectiveness in traditional classroom settings, rais-
ing concerns about cheating, plagiarism, and privacy issues. While students report a positive
attitude towards ChatGPT, finding it interesting and helpful, they still prefer human interac-
tion, underscoring the importance of personal connections in learning. They believe that
ChatGPT can enhance study efficiency and knowledge acquisition but acknowledge the risks
of dependency that may undermine critical thinking skills. Although it is seen as beneficial for
developing AI literacy and digital content creation skills, it is less effective in fostering interper-
sonal communication. Students anticipate increased demand for tech-related skills in the labor
market due to AI’s rise, highlighting the need for ongoing skill development without expecting
significant impacts on unemployment rates. Overall, students experience positive emotions,
such as curiosity and calmness, when using ChatGPT, indicating a readiness to integrate AI
into their academic lives while remaining aware of its limitations.
However, students’ perceptions varied by socio-demographic and geographic factors.
Applied Sciences students value ChatGPT for its technical clarity, while Arts and Humanities
students prefer human interaction and express concerns about the tool’s ability to capture
nuanced insights. Social Sciences students find ChatGPT limited in providing subjective
insights necessary for their disciplines. In low-income regions, students appreciate ChatGPT
as essential support where resources are scarce, whereas those in high-income regions focus
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Higher education students’ perceptions of ChatGPT: A global study of early reactions
PLOS ONE | https://doi.org/10.1371/journal.pone.0315011 February 5, 2025 40 / 53
more on its innovative features and advanced functionalities. Male students report higher sat-
isfaction with ChatGPT, while female students express greater ethical concerns regarding its
use, including issues of cheating and privacy. First-year students tend to view ChatGPT as a
helpful tool for learning, while advanced students question its reliability and relevance to their
more complex academic needs. Online learners benefit more from ChatGPT’s digital align-
ment with their study practices, finding it easier to integrate into their learning routines, while
traditional learners often find it less relevant in face-to-face educational contexts. Additionally,
students from urban areas generally utilize ChatGPT more than those in rural settings, where
access to technology may be limited. Economic status also plays a role, as students from lower
economic backgrounds tend to rely on ChatGPT for support in navigating their academic
challenges, highlighting its importance in bridging educational gaps.
The factors related to ChatGPT significantly influence how students use it for tasks such as
brainstorming, summarizing, and academic writing. Its ability to simplify complex informa-
tion encourages frequent use, especially for summarizing, while access to extensive informa-
tion can aid academic writing but may complicate summarizing due to potential overload.
Concerns about privacy and academic integrity often reduce students’ use of ChatGPT, partic-
ularly in writing tasks. However, students who recognize the potential for skills development,
like improving AI literacy, are more inclined to use it for academic writing, while those who
feel it enhances their digital content creation skills tend to use it for brainstorming. Emotional
factors also play a role, with curiosity and calmness increasing engagement, particularly in
brainstorming activities. Overall, these cognitive, ethical, and emotional elements interact to
shape how students engage with ChatGPT in their academic work.
Implications for practice and policy
The core contribution of the study lies in its comprehensive global analysis of higher education
students’ early perceptions regarding the use of ChatGPT. It explores how students initially
engage with ChatGPT by identifying the benefits and challenges associated with its use in aca-
demic settings, highlighting variations in perceptions based on socio-demographic and geo-
graphic factors, and examining how various factors significantly influence student usage.
While the results reveal strong student interest and perceived benefits, a deeper critical engage-
ment with these early perceptions, particularly the differences across socio-demographic and
geographic characteristics, highlights several significant implications for higher education
practice and policy.
The varied perceptions of ChatGPT among students provide valuable insights for higher
education practice (i.e., managers and teachers) seeking to implement AI thoughtfully across
diverse socio-demographic and geographic contexts. Tailoring ChatGPT to specific disciplines
can enhance its educational impact, support technical problem-solving in applied sciences,
and foster idea generation in arts and humanities. Customizing AI approaches by income
region helps bridge resource gaps by equipping students from low income regions with train-
ing for academic support and offering advanced functionalities to high-income students. Gen-
der-based initiatives, such as peer-led tech roles for male students and responsible AI
workshops for female students, foster inclusivity and confidence in AI use. First-year students
benefit from foundational skills training, while advanced students gain guidance on critically
assessing AI content. Integrating ChatGPT as a core tool in online and blended settings and as
supplementary support in traditional learning optimizes its adaptability across environments.
Addressing geographic and economic distinctions through targeted training ensures ChatGPT
becomes a valuable educational resource for rural and economically disadvantaged students
while enabling wealthier students to explore more advanced features.
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For higher education policy (i.e., policymakers), equitable access to AI in education is
essential to prevent the widening of the digital divide. However, paywall restrictions on the lat-
est ChatGPT versions risk leaving students from low income regions and rural areas with out-
dated tools, limiting the quality of their learning and digital skill development. This gap also
affects gender equity, as limited access can hinder female students from building AI literacy
and confidence. Addressing these disparities requires funding for subsidized access, institu-
tional licenses, and digital literacy programs in underserved areas, alongside gender-inclusive
initiatives like responsible AI workshops. Establishing curriculum guidelines that integrate AI
across all learning stages creates a balanced, inclusive approach that enriches traditional educa-
tion and prepares students for an AI-driven workforce.
Limitations
Although the study’s large and diverse global sample of students is a notable strength of our
research, several limitations must be acknowledged. First, the use of convenience sampling for
recruiting participants led to uneven representation across various socio-demographic sub-
groups, with geographical coverage being a prime example. Despite including participants
from over 100 countries and/or territories, less than 1% came from low income countries.
Therefore, some findings may be biased to some extent, and caution should be exercised when
generalizing the results to countries and/or territories not adequately represented in the sam-
ple. Second, the study captured only early impressions and experiences of students with
ChatGPT. As generative AI technologies evolve and students become more familiar with their
strengths and limitations, these initial impressions may not fully align with their future opin-
ions on ChatGPT. Third, the questionnaire relied on students’ self-reports, which can be sub-
ject to information bias. Therefore, it is plausible that some students may have either
underestimated or overestimated their early perceptions of ChatGPT in various aspects.
Finally, the identified socio-demographic and geographic differences in students’ early percep-
tions may also reflect factors beyond ChatGPT that were not covered in the questionnaire,
such as variations in the digital transformation of higher education, economic development,
cultural and religious backgrounds, and political circumstances.
Future research
Despite the above limitations, our global study is extremely important as it fills a gap in
comparative studies analyzing students’ early perceptions of ChatGPT and highlights ave-
nues for future research. First, enhancing sampling methods by employing stratified or ran-
dom sampling techniques could improve representation across socio-demographic and
geographic subgroups, including underrepresented low income countries. Second, con-
ducting longitudinal studies would allow researchers to track changes in students’ percep-
tions of ChatGPT over time as AI technologies evolve. Third, to counteract potential
information bias from self-reports, future studies could incorporate a mix of quantitative
and qualitative data sources, such as behavioral data and expert evaluations, alongside self-
reports. Finally, investigating a broader range of contextual factors, including the digital
transformation of higher education, economic conditions, cultural and religious back-
grounds, and political environments, could provide deeper insights into how these factors
influence students’ perceptions. These approaches would help build on the current study’s
findings and offer a more comprehensive understanding of students’ views on generative
AI technologies.
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Supporting information
S1 Checklist. Inclusivity in global research.
(DOCX)
S1 File. Comparative analysis.
(XLSX)
S1 Table. Spearman correlation between main independent variables of interest.
(DOCX)
Acknowledgments
The authors acknowledge the exceptional assistance of numerous international partners in
translating the questionnaire and/or collecting data within the CovidSocLab initiative, specifi-
cally the global ChatGPT student survey (https://www.covidsoclab.org/chatgpt-student-
survey/), which served as a collaborative working platform. More information about the inter-
national partners is available in the Mendeley Data repository (https://doi.org/10.17632/
ymg9nsn6kn). Moreover, the authors express their gratitude to the anonymous higher educa-
tion students who participated in the global ChatGPT student survey for providing valuable
insights into their early perceptions of ChatGPT. Finally, in the preparation of this manuscript,
the authors utilized ChatGPT, version 4o, developed by OpenAI, for limited and supplemen-
tary purposes. Specifically, ChatGPT was employed to assist with checking the grammar,
enhancing clarity, and polishing the language in certain sections of the manuscript. It must be
stressed that the role of the ChatGPT was minor and purely supportive in nature. The core
content of the manuscript, including all scientific interpretations, conclusions, and critical
revisions, is the exclusive output of the human authors. ChatGPT did not contribute to the
intellectual content or scientific insights of the manuscript.
Author Contributions
Conceptualization: Aleksander Aristovnik.
Data curation: Dejan Ravs
ˇelj, Lan Umek.
Formal analysis: Dejan Ravs
ˇelj, Damijana Kerz
ˇič, Lan Umek.
Funding acquisition: Dejan Ravs
ˇelj, Aleksander Aristovnik.
Investigation: Dejan Ravs
ˇelj, Damijana Kerz
ˇič, Nina Tomaz
ˇevič, Lan Umek, Nejc Brezovar,
Noorminshah A. Iahad, Ali Abdulla Abdulla, Anait Akopyan, Magdalena Waleska Aldana
Segura, Jehan AlHumaid, Mohamed Farouk Allam, Maria Allo
´, Raphael Papa Kweku
Andoh, Octavian Andronic, Yarhands Dissou Arthur, Fatih Aydın, Amira Badran, Roxana
Balbontı
´n-Alvarado, Helmi Ben Saad, Andrea Bencsik, Isaac Benning, Adrian Besimi,
Denilson da Silva Bezerra, Chiara Buizza, Roberto Burro, Anthony Bwalya, Cristina
Cachero, Patricia Castillo-Briceno, Harold Castro, Ching Sing Chai, Constadina Charalam-
bous, Thomas K. F. Chiu, Otilia Clipa, Ruggero Colombari, Luis Jose
´H. Corral Escobedo,
Elı
´sio Costa, Radu George Crețulescu, Marta Crispino, Nicola Cucari, Fergus Dalton, Meva
Demir Kaya, Ivo Dumić-Čule, Diena Dwidienawati, Ryan Ebardo, Daniel Lawer Egbenya,
MoezAlIslam Ezzat Faris, Miroslav Fečko, Paulo Ferrinho, Adrian Florea, Chun Yuen
Fong, Zoe¨Francis, Alberto Ghilardi, Belinka Gonza
´lez-Ferna
´ndez, Daniela Hau, Md. Sha-
mim Hossain, Theo Hug, Fany Inasius, Maryam Jaffar Ismail, Hatidz
ˇa Jahić, Morrison
Omokiniovo Jessa, Marika Kapanadze, Sujita Kumar Kar, Elham Talib Kateeb, Feridun
Kaya, Hanaa Ouda Khadri, Masao Kikuchi, Vitaliy Mykolayovych Kobets, Katerina
PLOS ONE
Higher education students’ perceptions of ChatGPT: A global study of early reactions
PLOS ONE | https://doi.org/10.1371/journal.pone.0315011 February 5, 2025 43 / 53
Metodieva Kostova, Evita Krasmane, Jesus Lau, Wai Him Crystal Law, Florin Lazăr, Lejla
Lazović-Pita, Vivian Wing Yan Lee, Jingtai Li, Diego Vinicio Lo
´pez-Aguilar, Adrian Luca,
Ruth Garcia Luciano, Juan D. Machin-Mastromatteo, Marwa Madi, Alexandre Lourenc¸o
Manguele, Rube
´n Francisco Manrique, Thumah Mapulanga, Frederic Marimon, Galia
Ilieva Marinova, Marta Mas-Machuca, Oliva Mejı
´a-Rodrı
´guez, Maria Meletiou-Mav-
rotheris, Silvia Mariela Me
´ndez-Prado, Jose
´Manuel Meza-Cano, Evija Mirk¸e, Alpana Mis-
hra, Ondrej Mital, Cristina Mollica, Daniel Ionel Morariu, Natalia Mospan, Angel Mukuka,
Silvana Guadalupe Navarro Jime
´nez, Irena Nikaj, Maria Mihaylova Nisheva, Efi Nisiforou,
Joseph Njiku, Singhanat Nomnian, Lulzime Nuredini-Mehmedi, Ernest Nyamekye, Alka
Obadić, Abdelmohsen Hamed Okela, Dorit Olenik-Shemesh, Izabela Ostoj, Kevin Javier
Peralta-Rizzo, Almir Pes
ˇtek, Amila Pilav-Velić, Dilma Rosanda Miranda Pires, Eyal Rabin,
Daniela Raccanello, Agustine Ramie, Md. Mamun ur Rashid, Robert A. P. Reuter, Valen-
tina Reyes, Ana Sofia Rodrigues, Paul Rodway, Silvia Ručinska
´, Shorena Sadzaglishvili, Ash-
raf Atta M. S. Salem, Gordana Savić, Astrid Schepman, Samia Mokhtar Shahpo,
Abdelmajid Snouber, Emma Soler, Bengi Sonyel, Eliza Stefanova, Anna Stone, Artur Strze-
lecki, Tetsuji Tanaka, Carolina Tapia Cortes, Andrea Teira-Fachado, Henri Tilga, Jelena
Titko, Maryna Tolmach, Dedi Turmudi, Laura Varela-Candamio, Ioanna Vekiri, Giada
Vicentini, Erisher Woyo, O
¨zlem Yorulmaz, Said A. S. Yunus, Ana-Maria Zamfir, Munyar-
adzi Zhou, Aleksander Aristovnik.
Methodology: Dejan Ravs
ˇelj, Damijana Kerz
ˇič, Nina Tomaz
ˇevič, Aleksander Aristovnik.
Project administration: Dejan Ravs
ˇelj, Nina Tomaz
ˇevič, Aleksander Aristovnik.
Resources: Dejan Ravs
ˇelj, Damijana Kerz
ˇič, Nina Tomaz
ˇevič, Lan Umek, Nejc Brezovar,
Noorminshah A. Iahad, Ali Abdulla Abdulla, Anait Akopyan, Magdalena Waleska Aldana
Segura, Jehan AlHumaid, Mohamed Farouk Allam, Maria Allo
´, Raphael Papa Kweku
Andoh, Octavian Andronic, Yarhands Dissou Arthur, Fatih Aydın, Amira Badran, Roxana
Balbontı
´n-Alvarado, Helmi Ben Saad, Andrea Bencsik, Isaac Benning, Adrian Besimi,
Denilson da Silva Bezerra, Chiara Buizza, Roberto Burro, Anthony Bwalya, Cristina
Cachero, Patricia Castillo-Briceno, Harold Castro, Ching Sing Chai, Constadina Charalam-
bous, Thomas K. F. Chiu, Otilia Clipa, Ruggero Colombari, Luis Jose
´H. Corral Escobedo,
Elı
´sio Costa, Radu George Crețulescu, Marta Crispino, Nicola Cucari, Fergus Dalton, Meva
Demir Kaya, Ivo Dumić-Čule, Diena Dwidienawati, Ryan Ebardo, Daniel Lawer Egbenya,
MoezAlIslam Ezzat Faris, Miroslav Fečko, Paulo Ferrinho, Adrian Florea, Chun Yuen
Fong, Zoe¨Francis, Alberto Ghilardi, Belinka Gonza
´lez-Ferna
´ndez, Daniela Hau, Md. Sha-
mim Hossain, Theo Hug, Fany Inasius, Maryam Jaffar Ismail, Hatidz
ˇa Jahić, Morrison
Omokiniovo Jessa, Marika Kapanadze, Sujita Kumar Kar, Elham Talib Kateeb, Feridun
Kaya, Hanaa Ouda Khadri, Masao Kikuchi, Vitaliy Mykolayovych Kobets, Katerina Meto-
dieva Kostova, Evita Krasmane, Jesus Lau, Wai Him Crystal Law, Florin Lazăr, Lejla
Lazović-Pita, Vivian Wing Yan Lee, Jingtai Li, Diego Vinicio Lo
´pez-Aguilar, Adrian Luca,
Ruth Garcia Luciano, Juan D. Machin-Mastromatteo, Marwa Madi, Alexandre Lourenc¸o
Manguele, Rube
´n Francisco Manrique, Thumah Mapulanga, Frederic Marimon, Galia
Ilieva Marinova, Marta Mas-Machuca, Oliva Mejı
´a-Rodrı
´guez, Maria Meletiou-Mav-
rotheris, Silvia Mariela Me
´ndez-Prado, Jose
´Manuel Meza-Cano, Evija Mirk¸e, Alpana Mis-
hra, Ondrej Mital, Cristina Mollica, Daniel Ionel Morariu, Natalia Mospan, Angel Mukuka,
Silvana Guadalupe Navarro Jime
´nez, Irena Nikaj, Maria Mihaylova Nisheva, Efi Nisiforou,
Joseph Njiku, Singhanat Nomnian, Lulzime Nuredini-Mehmedi, Ernest Nyamekye, Alka
Obadić, Abdelmohsen Hamed Okela, Dorit Olenik-Shemesh, Izabela Ostoj, Kevin Javier
Peralta-Rizzo, Almir Pes
ˇtek, Amila Pilav-Velić, Dilma Rosanda Miranda Pires, Eyal Rabin,
PLOS ONE
Higher education students’ perceptions of ChatGPT: A global study of early reactions
PLOS ONE | https://doi.org/10.1371/journal.pone.0315011 February 5, 2025 44 / 53
Daniela Raccanello, Agustine Ramie, Md. Mamun ur Rashid, Robert A. P. Reuter, Valen-
tina Reyes, Ana Sofia Rodrigues, Paul Rodway, Silvia Ručinska
´, Shorena Sadzaglishvili, Ash-
raf Atta M. S. Salem, Gordana Savić, Astrid Schepman, Samia Mokhtar Shahpo,
Abdelmajid Snouber, Emma Soler, Bengi Sonyel, Eliza Stefanova, Anna Stone, Artur Strze-
lecki, Tetsuji Tanaka, Carolina Tapia Cortes, Andrea Teira-Fachado, Henri Tilga, Jelena
Titko, Maryna Tolmach, Dedi Turmudi, Laura Varela-Candamio, Ioanna Vekiri, Giada
Vicentini, Erisher Woyo, O
¨zlem Yorulmaz, Said A. S. Yunus, Ana-Maria Zamfir, Munyar-
adzi Zhou, Aleksander Aristovnik.
Software: Lan Umek.
Supervision: Aleksander Aristovnik.
Validation: Lan Umek.
Visualization: Damijana Kerz
ˇič, Lan Umek.
Writing – original draft: Dejan Ravs
ˇelj, Damijana Kerz
ˇič, Nina Tomaz
ˇevič, Ali Abdulla
Abdulla, Anait Akopyan, Magdalena Waleska Aldana Segura, Jehan AlHumaid, Maria Allo
´,
Raphael Papa Kweku Andoh, Octavian Andronic, Fatih Aydın, Amira Badran, Roxana Bal-
bontı
´n-Alvarado, Helmi Ben Saad, Andrea Bencsik, Adrian Besimi, Denilson da Silva
Bezerra, Chiara Buizza, Roberto Burro, Cristina Cachero, Harold Castro, Constadina Char-
alambous, Thomas K. F. Chiu, Ruggero Colombari, Marta Crispino, Nicola Cucari, Meva
Demir Kaya, Ivo Dumić-Čule, Ryan Ebardo, MoezAlIslam Ezzat Faris, Paulo Ferrinho,
Adrian Florea, Chun Yuen Fong, Zoe¨Francis, Alberto Ghilardi, Belinka Gonza
´lez-Ferna
´n-
dez, Daniela Hau, Md. Shamim Hossain, Theo Hug, Fany Inasius, Maryam Jaffar Ismail,
Hatidz
ˇa Jahić, Morrison Omokiniovo Jessa, Sujita Kumar Kar, Elham Talib Kateeb, Feridun
Kaya, Hanaa Ouda Khadri, Masao Kikuchi, Vitaliy Mykolayovych Kobets, Katerina Meto-
dieva Kostova, Evita Krasmane, Wai Him Crystal Law, Florin Lazăr, Lejla Lazović-Pita, Viv-
ian Wing Yan Lee, Jingtai Li, Ruth Garcia Luciano, Juan D. Machin-Mastromatteo, Marwa
Madi, Rube
´n Francisco Manrique, Thumah Mapulanga, Frederic Marimon, Galia Ilieva
Marinova, Marta Mas-Machuca, Oliva Mejı
´a-Rodrı
´guez, Maria Meletiou-Mavrotheris, Sil-
via Mariela Me
´ndez-Prado, Jose
´Manuel Meza-Cano, Evija Mirk¸e, Cristina Mollica, Natalia
Mospan, Irena Nikaj, Maria Mihaylova Nisheva, Efi Nisiforou, Singhanat Nomnian, Lul-
zime Nuredini-Mehmedi, Alka Obadić, Abdelmohsen Hamed Okela, Dorit Olenik-She-
mesh, Izabela Ostoj, Kevin Javier Peralta-Rizzo, Almir Pes
ˇtek, Amila Pilav-Velić, Dilma
Rosanda Miranda Pires, Eyal Rabin, Daniela Raccanello, Agustine Ramie, Md. Mamun ur
Rashid, Robert A. P. Reuter, Valentina Reyes, Paul Rodway, Silvia Ručinska
´, Shorena Sadza-
glishvili, Gordana Savić, Astrid Schepman, Samia Mokhtar Shahpo, Abdelmajid Snouber,
Artur Strzelecki, Andrea Teira-Fachado, Henri Tilga, Jelena Titko, Maryna Tolmach, Dedi
Turmudi, Laura Varela-Candamio, Ioanna Vekiri, Giada Vicentini, Erisher Woyo, O
¨zlem
Yorulmaz, Said A. S. Yunus, Ana-Maria Zamfir.
Writing – review & editing: Dejan Ravs
ˇelj, Damijana Kerz
ˇič, Nina Tomaz
ˇevič, Nejc Brezovar,
Noorminshah A. Iahad, Mohamed Farouk Allam, Yarhands Dissou Arthur, Isaac Benning,
Anthony Bwalya, Patricia Castillo-Briceno, Ching Sing Chai, Otilia Clipa, Luis Jose
´H. Cor-
ral Escobedo, Elı
´sio Costa, Radu George Crețulescu, Fergus Dalton, Diena Dwidienawati,
Daniel Lawer Egbenya, Miroslav Fečko, Marika Kapanadze, Jesus Lau, Diego Vinicio
Lo
´pez-Aguilar, Adrian Luca, Alexandre Lourenc¸o Manguele, Alpana Mishra, Ondrej Mital,
Daniel Ionel Morariu, Angel Mukuka, Silvana Guadalupe Navarro Jime
´nez, Joseph Njiku,
Ernest Nyamekye, Ana Sofia Rodrigues, Ashraf Atta M. S. Salem, Emma Soler, Bengi
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Higher education students’ perceptions of ChatGPT: A global study of early reactions
PLOS ONE | https://doi.org/10.1371/journal.pone.0315011 February 5, 2025 45 / 53
Sonyel, Eliza Stefanova, Anna Stone, Tetsuji Tanaka, Carolina Tapia Cortes, Munyaradzi
Zhou, Aleksander Aristovnik.
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