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Perceptions and usage of AI chatbots among students in higher education across genders, academic levels and fields of study
Open accessAbstract
AI chatbots have ignited discussions and controversies about their impact on teaching and learning practices in higher education. This study explores students' adoption and perceptions of ChatGPT and other AI chatbots in higher education. Based on survey data from a large sample (n = 5894) across Swedish universities, the study employs descriptive statistical methods to analyze usage, attitudes, and concerns, and inferential statistics to identify relations between attitudes and usage and background variables (gender, academic level, and field of study). The results reveal broad awareness and use of ChatGPT among students, but not of other AI chatbots. More than half of the students expressed positive attitudes towards the use of chatbots in education, but almost as many expressed concerns about future use. Statistically significant differences were found across all examined grouping variables, particularly between genders and fields of study. Female students and students from the humanities and medicine consistently expressed more negative attitudes and concerns about AI's role in learning and assessment, while males and technology and engineering students showed higher usage and optimism. These findings not only validate the continued relevance of student backgrounds as a determinant of technology adoption but also expose several challenges and considerations surrounding AI and chatbot usage in education. The study supports the development of local solutions to AI in education tailored to student attributes and needs, and it provides insights for developers, educators, and policymakers.
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“Despite this, over one-third of students surveyed utilize ChatGPT for educational purposes, and the use of other chatbot technologies was minimal (Stohr et al., 2024).”
From Effects of Generative AI on Engagement and Performance Within Asynchronous Online Courses (2026) · cites this paper as Stohr et al., 2024
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“Stohr et al. (2024) found that male students in technology and engineering degree programs had more positive views of AI chatbots than their female counterparts in medical or humanities degree programs.”
From Effects of Generative AI on Engagement and Performance Within Asynchronous Online Courses (2026) · cites this paper as Stohr et al., 2024
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“Male students tend to report greater familiarity with AI tools and more optimism about their benefits for learning, whereas female students are generally more cautious and sceptical about their impact on assessment and academic integrity (Jospeh et al. 2024;Stöhr, Ou, and Malmström 2024).”
From Widely used but barely trusted: understanding student perceptions on the use of generative AI in higher education (2025) · cites this paper as Stöhr, Ou, and Malmström 2024
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“Large-scale surveys such as Jospeh et al. (2024) in Nigeria (n = 5, 554) and Stöhr, Ou, and Malmström (2024) in Sweden (n = 5, 894) point to positive attitudes towards GAI as usage increases.”
From Widely used but barely trusted: understanding student perceptions on the use of generative AI in higher education (2025) · cites this paper as Stöhr, Ou, and Malmström (2024)
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“While many students value GAI as a complement to their learning, a substantial proportion consider its use in exams to constitute cheating (Stöhr, Ou, and Malmström 2024).”
From Widely used but barely trusted: understanding student perceptions on the use of generative AI in higher education (2025) · cites this paper as Stöhr, Ou, and Malmström 2024
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“Disciplinary background appears to moderate these differences, as students in engineering and technology tend to embrace GAI tools more enthusiastically, while students in humanities and medicine have displayed more scepticism (Freeman 2025;Mercader and Gairín 2020;Stöhr, Ou, and Malmström 2024).”
From Widely used but barely trusted: understanding student perceptions on the use of generative AI in higher education (2025) · cites this paper as Stöhr, Ou, and Malmström 2024
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“Despite this, over one-third of students surveyed utilize ChatGPT for educational purposes, and the use of other chatbot technologies was minimal (Stohr et al., 2024).”
From Effects of Generative AI on Engagement and Performance Within Asynchronous Online Courses (2026) · cites this paper as Stohr et al., 2024
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Citations
Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Research design: qualitative, quantitative, and mixed methods approaches
Caldas, M. (2003) · Revista de Administração Contemporânea · doi:10.1590/s1415-65552003000100015 · Cited by 18,688
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · cited 4×
“…answering questions (Chen et al., 2023), facilitating group discussions, and resolving problems instantaneously (Rahman & Watanobe, 2023), thereby enriching students ’ learning experiences, offering personalized support, and potentially boosting academic performance (Kasneci et al., 2023).”
BackgroundInfluentialZawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-019-0171-0 · Cited by 7,242
Artificial Intelligence in Education: A Review
Chen, L., Chen, P., & Lin, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2988510 · Cited by 4,133 · cited 2×
“Concomitantly, AI in education (AIED) has emerged as a vibrant academic field, extending the capability of AI not just to learners but also to educators and institutions alike (Chen et al., 2020; Hwang et al., 2020; Nemorin et al., 2023).”
BackgroundWhat is AI Literacy? Competencies and Design Considerations
Long, D., & Magerko, B. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376727 · Cited by 3,241 · cited 1×
“Students ’ AI literacy development enabling them to critically evaluate, communicate with, and use AI technologies (Long & Magerko, 2020) are likely to be significantly shaped by the ways in which teachers insert and discuss AI technologies in their teaching practices.”
BackgroundThe Predictive Validity of Multiple-Item versus Single-Item Measures of the Same Constructs
Bergkvist, L., & Rossiter, J. R. (2007) · Journal of Marketing Research · doi:10.1509/jmkr.44.2.175 · Cited by 3,107
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079
Venkatesh, V., & Morris, M. G. (2000) · MIS Quarterly · doi:10.2307/3250981 · Cited by 2,780
The C-OAR-SE procedure for scale development in marketing
Rossiter, J. R. (2002) · International Journal of Research in Marketing · doi:10.1016/s0167-8116(02)00097-6 · Cited by 2,478
What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature
Lo, C. K. (2023) · Education Sciences · doi:10.3390/educsci13040410 · Cited by 2,024
ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.9 · Cited by 1,806 · cited 2×
“Data from stakeholder perspectives are sorely needed to provide a basis for more informed discussions and decision-making (e.g., Bates et al., 2020; García-Pe ˜ nalvo, 2023; Rudolph et al., 2023).”
BackgroundVision, challenges, roles and research issues of Artificial Intelligence in Education
Hwang, G.-J., Xie, H., Wah, B. W., & Gašević, D. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100001 · Cited by 1,435
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100118 · Cited by 1,181 · cited 1×
“Similarly, research on the academic discipline of students as a moderating factor is scarce (Chiu et al., 2023), though existing evidence suggests that there are greater barriers to technology adoption within the fields of arts and humanities compared to technological fields (e.g., Mercader &…”
BackgroundState of the art and practice in AI in education
Holmes, W., & Tuomi, I. (2022) · European Journal of Education · doi:10.1111/ejed.12533 · Cited by 1,093 · cited 1×
“…platforms that provide personalized learning experiences to students, automated assessment, or AI-powered writing tools that enhance students ’ writing quality by providing real-time feedback on issues with grammar, punctuation, and style (Holmes & Tuomi, 2022; Zawacki-Richter et al., 2019).”
BackgroundChatGPT for Education and Research: Opportunities, Threats, and Strategies
Rahman, M. M., & Watanobe, Y. (2023) · Applied Sciences · doi:10.3390/app13095783 · Cited by 1,080 · cited 2×
“…students in acquiring information, answering questions (Chen et al., 2023), facilitating group discussions, and resolving problems instantaneously (Rahman & Watanobe, 2023), thereby enriching students ’ learning experiences, offering personalized support, and potentially boosting academic…”
BackgroundRevolutionizing education with AI: Exploring the transformative potential of ChatGPT
Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023) · Contemporary Educational Technology · doi:10.30935/cedtech/13152 · Cited by 975
Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023) · Information Systems Frontiers · doi:10.1007/s10796-022-10291-4 · Cited by 685
The benefits and challenges of chatgpt: An overview
Deng, J., & Lin, Y. (2023) · Frontiers in Computing and Intelligent Systems · doi:10.54097/fcis.v2i2.4465 · Cited by 611
Morris, M. G., Venkatesh, V., & Ackerman, P. L. (2005) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2004.839967 · Cited by 604
The rise of ChatGPT : Exploring its potential in medical education
Lee, H. (2024) · Anatomical Sciences Education · doi:10.1002/ase.2270 · Cited by 596 · cited 1×
“However, this should be considered in the sometimes euphoric discussion about the potential of ChatGPT in medical education (e.g., Lee, 2023).”
BackgroundChatGPT and the rise of generative AI: Threat to academic integrity?
Eke, D. O. (2023) · Journal of Responsible Technology · doi:10.1016/j.jrt.2023.100060 · Cited by 532
A review of opportunities and challenges of chatbots in education
Hwang, G.-J., & Chang, C.-Y. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2021.1952615 · Cited by 530
Liu, G., & Ma, C. (2024) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2023.2240316 · Cited by 511
Can artificial intelligence transform higher education?
Bates, T., Cobo, C., Mariño, O., & Wheeler, S. (2020) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-020-00218-x · Cited by 490
The future of AI and education: Some cautionary notes
Selwyn, N. (2022) · European Journal of Education · doi:10.1111/ejed.12532 · Cited by 428
Juan, C. M., & Sallán, J. G. (2020) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-020-0182-x · Cited by 393
Tahiru, F. (2020) · Journal of Cases on Information Technology · doi:10.4018/jcit.2021010101 · Cited by 369
García-Peñalvo, F. J. (2023) · Education in the Knowledge Society (EKS) · doi:10.14201/eks.31279 · Cited by 331
AI hyped? A horizon scan of discourse on artificial intelligence in education (AIED) and development
Nemorin, S., Vlachidis, A., Ayerakwa, H. M., & Andriotis, P. (2023) · Learning, Media and Technology · doi:10.1080/17439884.2022.2095568 · Cited by 229
Adoption of AI-Chatbots to Enhance Student Learning Experience in Higher Education in India
Sandu, N., & Gide, E. (2019) · International Conference on Information Technology Based Higher Education and Training (ITHET) · doi:10.1109/ithet46829.2019.8937382 · Cited by 223
Farazouli, A., Cerratto-Pargman, T., Bolander-Laksov, K., & McGrath, C. (2024) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2023.2241676 · Cited by 219
ChatGPT in education: a discourse analysis of worries and concerns on social media
Li, L., Ma, Z., Fan, L., Lee, S., Yu, H., & Hemphill, L. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12256-9 · Cited by 218
Understanding User Trust in Artificial Intelligence-Based Educational Systems: Evidence from China
Qin, F., Li, K., & Yan, J. (2020) · British Journal of Educational Technology · doi:10.1111/bjet.12994 · Cited by 204
Hajkowicz, S. A., Sanderson, C., Karimi, S., Bratanova, A., & Naughtin, C. K. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102260 · Cited by 186
AI in Medical Education: Global situation, effects and challenges
Zhang, W., Cai, M., Lee, H. J., Evans, R., Zhu, C., & Ming, C. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12009-8 · Cited by 148
Alzahrani, L. (2023) · International journal of recent technology and engineering · doi:10.35940/ijrte.f7475.0311623 · Cited by 86
Santomartino, S. M., & Yi, P. H. (2022) · Academic Radiology · doi:10.1016/j.acra.2021.12.032 · Cited by 64
Education level as a technology adoption moderator
Abu-Shanab, E. A. (2011) · International Conference on Computer Research and Development · doi:10.1109/iccrd.2011.5764029 · Cited by 61
Nouraldeen, R. M. (2022) · Development in Learning Organizations An International Journal · doi:10.1108/dlo-07-2022-0133 · Cited by 56
Reading Comprehension Quiz Generation using Generative Pre-trained Transformers
Dijkstra, R., Genç, Z., Kayal, S., Kamps, J., Sosnovsky, S., Brusilovsky, P., & Lan, A. (2022) · UvA-DARE (University of Amsterdam) · Cited by 39
Chatbots and other AI for learning: A survey of use and views among university students in Sweden
Malmström, H., Stöhr, C., & Ou, W. (2023) · Chalmers University of Technology · doi:10.17196/cls.csclhe/2023/01 · Cited by 37
Self-citationP dos Santos, R. (2023) · doi:10.2139/ssrn.4447416 · Cited by 31
A Survey of the General Public’s Views on the Ethics of Using AI in Education
Latham, A., & Goltz, N. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-23204-7_17 · Cited by 27
ChatGPT in education: A discourse analysis of worries and concerns on social mediaPreprint
Li, L., Ma, Z., Fan, L., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2305.02201 · Cited by 25
We still need to teach engineers to write in the era of ChatGPT
Berdanier, C., & Alley, M. (2023) · Journal of Engineering Education · doi:10.1002/jee.20541 · Cited by 23
Effect of academic discipline on technology acceptance
Orji, R. (2010) · International Conference on Education and Management Technology · doi:10.1109/icemt.2010.5657581 · Cited by 18
Artificial Intelligence in Education
(2019) · Lecture notes in computer science · doi:10.1007/978-3-030-23204-7 · Cited by 14
Santos, R. P. D. (2023) · arXiv · doi:10.48550/arxiv.2305.11890 · Cited by 6
Barbero (2014) · doi:10.1016/j · Cited by 1
Research works printed but not linked: 3
- Lobet, 2023, Use of ChatGPT by students: Artificial intelligence is all the rage!
- Nisar, 2023, Is ChatGPT a good tool for T&CM students in studying pharmacology?, SSRN Scholarly Paper (4324310)
- Welding, 2023, Half of college students say using AI on schoolwork is cheating or plagiarism, BestColleges
Cited by
Sorted by citations
Almassaad, A. Z., Alajlan, H., & Alebaikan, R. (2024) · Systems · doi:10.3390/systems12100385 · Cited by 257
Bewersdorff, A., Hornberger, M., Nerdel, C., & Schiff, D. S. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100340 · Cited by 148
Schmidt, D. A., Alboloushi, B., Thomas, A., & Magalhães, R. (2025) · Computers and Education Open · doi:10.1016/j.caeo.2025.100274 · Cited by 171
Møgelvang, A., Bjelland, C., Grassini, S., & Ludvigsen, K. (2024) · Education Sciences · doi:10.3390/educsci14121363 · Cited by 157
Qu, Y., Tan, M. X. Y., & Wang, J. (2024) · Smart Learning Environments · doi:10.1186/s40561-024-00341-6 · Cited by 107
Metadata
- Authors
- Stöhr, C., Ou, A. W., & Malmström, H.
- Affiliations
- Chalmers University of Technology (SE)
- Corresponding author
- Stöhr, Christian
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2024-12
- Volume
- 7
- Pages
- 100259
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4399948582
- Cited by
- 319
- References
- 49
- Citations by year
- 2026: 145 · 2025: 155 · 2024: 19
- FWCI
- 119.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by)
- Chalmers Research (Chalmers University of Technology) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Karlstads universitet
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- AI chatbots, ChatGPT, student perceptions, technology adoption, gender differences, academic level, field of study, student attitudes, assessment, higher education, humanities students, medical students
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