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. 2025 Feb 5;20(2):e0315011.
doi: 10.1371/journal.pone.0315011. eCollection 2025.

Higher education students' perceptions of ChatGPT: A global study of early reactions

Dejan Ravšelj  1 Damijana Keržič  1 Nina Tomaževič  1 Lan Umek  1 Nejc Brezovar  1 Noorminshah A Iahad  2 Ali Abdulla Abdulla  3 Anait Akopyan  4 Magdalena Waleska Aldana Segura  5   6 Jehan AlHumaid  7 Mohamed Farouk Allam  8 Maria Alló  9 Raphael Papa Kweku Andoh  10 Octavian Andronic  11 Yarhands Dissou Arthur  12 Fatih Aydın  13 Amira Badran  14 Roxana Balbontín-Alvarado  15 Helmi Ben Saad  16 Andrea Bencsik  17   18 Isaac Benning  19 Adrian Besimi  20 Denilson da Silva Bezerra  21 Chiara Buizza  22 Roberto Burro  23 Anthony Bwalya  24 Cristina Cachero  25 Patricia Castillo-Briceno  26 Harold Castro  27 Ching Sing Chai  28 Constadina Charalambous  29 Thomas K F Chiu  30 Otilia Clipa  31 Ruggero Colombari  32 Luis José H Corral Escobedo  33 Elísio Costa  34 Radu George Crețulescu  35 Marta Crispino  36 Nicola Cucari  37 Fergus Dalton  38 Meva Demir Kaya  39 Ivo Dumić-Čule  40 Diena Dwidienawati  41 Ryan Ebardo  42 Daniel Lawer Egbenya  43 MoezAlIslam Ezzat Faris  44 Miroslav Fečko  45 Paulo Ferrinho  46 Adrian Florea  35 Chun Yuen Fong  47 Zoë Francis  38 Alberto Ghilardi  22 Belinka González-Fernández  48 Daniela Hau  49 Md Shamim Hossain  50 Theo Hug  51 Fany Inasius  52 Maryam Jaffar Ismail  53 Hatidža Jahić  54 Morrison Omokiniovo Jessa  55 Marika Kapanadze  56 Sujita Kumar Kar  57 Elham Talib Kateeb  58 Feridun Kaya  39 Hanaa Ouda Khadri  59 Masao Kikuchi  60 Vitaliy Mykolayovych Kobets  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 López-Aguilar  68 Adrian Luca  69 Ruth Garcia Luciano  70 Juan D Machin-Mastromatteo  71 Marwa Madi  7 Alexandre Lourenço Manguele  72 Rubén Francisco Manrique  27 Thumah Mapulanga  73 Frederic Marimon  32 Galia Ilieva Marinova  62 Marta Mas-Machuca  32 Oliva Mejía-Rodríguez  74 Maria Meletiou-Mavrotheris  29 Silvia Mariela Méndez-Prado  75 José Manuel Meza-Cano  76 Evija Mirķe  77 Alpana Mishra  78 Ondrej Mital  45 Cristina Mollica  79 Daniel Ionel Morariu  35 Natalia Mospan  80 Angel Mukuka  81 Silvana Guadalupe Navarro Jiménez  33 Irena Nikaj  82 Maria Mihaylova Nisheva  83 Efi Nisiforou  84 Joseph Njiku  85 Singhanat Nomnian  86 Lulzime Nuredini-Mehmedi  87 Ernest Nyamekye  88 Alka Obadić  89 Abdelmohsen Hamed Okela  90 Dorit Olenik-Shemesh  91 Izabela Ostoj  92 Kevin Javier Peralta-Rizzo  75 Almir Peštek  54 Amila Pilav-Velić  54 Dilma Rosanda Miranda Pires  93 Eyal Rabin  91 Daniela Raccanello  23 Agustine Ramie  94 Md Mamun Ur Rashid  95 Robert A P Reuter  49 Valentina Reyes  96 Ana Sofia Rodrigues  97 Paul Rodway  98 Silvia Ručinská  45 Shorena Sadzaglishvili  99 Ashraf Atta M S Salem  100 Gordana Savić  101 Astrid Schepman  98 Samia Mokhtar Shahpo  102 Abdelmajid Snouber  103 Emma Soler  32 Bengi Sonyel  104 Eliza Stefanova  83 Anna Stone  105 Artur Strzelecki  106 Tetsuji Tanaka  107 Carolina Tapia Cortes  108 Andrea Teira-Fachado  9   109 Henri Tilga  110 Jelena Titko  111 Maryna Tolmach  112 Dedi Turmudi  113 Laura Varela-Candamio  9 Ioanna Vekiri  29 Giada Vicentini  23 Erisher Woyo  114 Özlem Yorulmaz  115 Said A S Yunus  53 Ana-Maria Zamfir  116   117 Munyaradzi Zhou  118 Aleksander Aristovnik  1
Affiliations

Higher education students' perceptions of ChatGPT: A global study of early reactions

Dejan Ravšelj et al. PLoS One. .

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 supporting 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. 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 communication, 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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Most and least exposed statements across ChatGPT aspects.
Fig 2
Fig 2. Word cloud of students’ perceptions of ChatGPT.
Fig 3
Fig 3. ChatGPT usage frequency (top two box scores and average values).
Fig 4
Fig 4. Differences in ChatGPT usage frequency (top two box scores by field of study).
Fig 5
Fig 5. Differences in ChatGPT usage frequency (top two box scores by income region).
Fig 6
Fig 6. Agreement on ChatGPT capabilities (top two box scores and average values).
Fig 7
Fig 7. Differences in agreement on ChatGPT capabilities (top two box scores by field of study).
Fig 8
Fig 8. Differences in agreement on ChatGPT capabilities (top two box scores by income region).
Fig 9
Fig 9. Agreement on ChatGPT regulation and ethical concerns (top two box scores and average values).
Fig 10
Fig 10. Differences in agreement on ChatGPT regulation and ethical concerns (top two box scores by field of study).
Fig 11
Fig 11. Differences in agreement on ChatGPT regulation and ethical concerns (top two box scores by income region).
Fig 12
Fig 12. Agreement on ChatGPT satisfaction and attitude (top two box scores and average values).
Fig 13
Fig 13. Differences in agreement on ChatGPT satisfaction and attitude (top two box scores by field of study).
Fig 14
Fig 14. Differences in agreement on satisfaction and attitude (top two box scores by income region).
Fig 15
Fig 15. Agreement on study issues and outcomes related to ChatGPT (top two box scores and average values).
Fig 16
Fig 16. Differences in agreement on study issues and outcomes related to ChatGPT (top two box scores by field of study).
Fig 17
Fig 17. Differences in agreement on study issues and outcomes related to ChatGPT (top two box scores by income region).
Fig 18
Fig 18. Agreement on the ChatGPT potential for skills development (top two box scores and average values).
Fig 19
Fig 19. Differences in agreement on the ChatGPT potential for skills development (top two box scores by field of study).
Fig 20
Fig 20. Differences in agreement on the ChatGPT potential for skills development (top two box scores by income region).
Fig 21
Fig 21. Agreement on the ChatGPT potential for labor market and skills mismatch (top two box scores and average values).
Fig 22
Fig 22. Differences in agreement on the ChatGPT potential for labor market and skills mismatch (top two box scores by field of study).
Fig 23
Fig 23. Differences in agreement on the ChatGPT potential for labor market and skills mismatch (top two box scores by income region).
Fig 24
Fig 24. Frequency of emotions felt when using ChatGPT (top two box scores and average values).
Fig 25
Fig 25. Differences in frequency of emotions felt when using ChatGPT (top two box scores by field of study).
Fig 26
Fig 26. Differences in frequency of emotions felt when using ChatGPT (top two box scores by income region).

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