Collaborative Working and Critical Thinking: Adoption of Generative Artificial Intelligence Tools in Higher Education
Open accessAbstract
This study explores the impact of generative artificial intelligence tools on critical thinking and collaboration among university students, highlighting the importance of investigating these technologies due to their increasing integration into higher education and their potential to transform traditional pedagogical practices. A predominantly female sample was surveyed to assess their familiarity with and experience and perceptions of these tools. A total of 87% of the respondents had prior knowledge of generative AI tools, with 38% using them occasionally. Among the most popular tools are Canva 2024 (33%), Chat PDF (26%), and YOU.COM (24%). Additionally, 64% of the respondents believe that these tools significantly improve their critical thinking ability. Despite their high familiarity with and occasional use of these tools, the need for continuous training and technical support was identified. While generative AI tools show promising potential for enhancing collaboration and critical thinking in higher education, previous research has limitations, such as the lack of longitudinal data and the inadequacy in addressing ethical considerations and potential biases. More comprehensive research is needed to understand their long-term impact better and maximize their potential benefits.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
GenAI has ignited fierce debates about the future of human creativity and originality.
“Since ChatGPT revolutionized the writing world in late 2022, generative artificial intelligence (GenAI) has ignited fierce debates about the future of human creativity and originality (Ruiz-Rojas et al., 2024).”
From MAPPING GENERATIVE AI'S ETHICAL ISSUES IN HIGHER EDUCATION: A FELT-GUIDED SYSTEMATIC REVIEW [PEMETAAN ISU ETIKA GENERATIVE AI DI PENDIDIKAN TINGGI: TINJAUAN SISTEMATIS BERPANDUAN FELT] (2025) · cites this paper as Ruiz-Rojas et al., 2024
ChatGPT revolutionized the writing world in late 2022.
“Since ChatGPT revolutionized the writing world in late 2022, generative artificial intelligence (GenAI) has ignited fierce debates about the future of human creativity and originality (Ruiz-Rojas et al., 2024).”
From MAPPING GENERATIVE AI'S ETHICAL ISSUES IN HIGHER EDUCATION: A FELT-GUIDED SYSTEMATIC REVIEW [PEMETAAN ISU ETIKA GENERATIVE AI DI PENDIDIKAN TINGGI: TINJAUAN SISTEMATIS BERPANDUAN FELT] (2025) · cites this paper as Ruiz-Rojas et al., 2024
Traditional instruction encourages students to practice writing skills over time, reinforcing long-term retention through exercises, discussions, and feedback loops.
“Traditional instruction encourages students to practice these skills over time, reinforcing long-term retention by incorporating exercises, discussions, and feedback loops [21].”
From The Role of AI in Academic Writing: Impacts on Writing Skills, Critical Thinking, and Integrity in Higher Education (2025) · cites this paper as [21]
Collaborative learning through peer reviews and discussions significantly contributes to skill development.
“Another key element for effective instruction is collaborative learning through peer reviews and discussions, which significantly contribute to skill development [21].”
From The Role of AI in Academic Writing: Impacts on Writing Skills, Critical Thinking, and Integrity in Higher Education (2025) · cites this paper as [21]
Traditional instruction methods foster deeper learning by requiring students to actively engage in the writing process.
“traditional instruction methods foster deeper learning by requiring students to actively engage in the writing process [9,21]”
From The Role of AI in Academic Writing: Impacts on Writing Skills, Critical Thinking, and Integrity in Higher Education (2025) · cites this paper as [21]
Cites
Generative AI and ChatGPT: applications, challenges, and AI-human collaboration
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2233814 · Cited by 1,363 · see citing works
Pavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972 · cited 6× · see citing works
“For example, ChatGPT can be a virtual discussion moderator, promoting critical thinking by offering diverse perspectives and responses [17].”
InfluentialStrategies for Teaching Students to Think Critically: A Meta-Analysis
Abrami, P. C., Bernard, R. M., Borokhovski, E., Waddington, D. I., Wade, C. A., & Persson, T. (2015) · Review of Educational Research · doi:10.3102/0034654314551063 · Cited by 932 · see citing works
Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT
Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023) · Education Sciences · doi:10.3390/educsci13090856 · Cited by 877 · see citing works
Thornhill-Miller, B., Camarda, A., Mercier, M., Burkhardt, J.-M., Morisseau, T., Bourgeois-Bougrine, S., Vinchon, F., El Hayek, S., Augereau-Landais, M., Mourey, F., et al. (2023) · Journal of Intelligence · doi:10.3390/jintelligence11030054 · Cited by 768 · cited 2× · see citing works
“Critical thinking involves analyzing, evaluating, and synthesizing information reflec-tively and deliberately, questioning assumptions, examining evidence, identifying biases, and forming informed conclusions [37].”
Challenges and Future Directions of Big Data and Artificial Intelligence in Education
Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J. H., Ogata, H., Baltes, J., Guerra, R., Li, P., & Tsai, C.-C. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.580820 · Cited by 667 · see citing works
ChatGPT in education: Strategies for responsible implementation
Halaweh, M. (2023) · Contemporary Educational Technology · doi:10.30935/cedtech/13036 · Cited by 607 · cited 2× · see citing works
“The article of [28] addresses educators’ concerns regarding integrating ChatGPT into education.”
van den Berg, G., & du Plessis, E. (2023) · Education Sciences · doi:10.3390/educsci13100998 · Cited by 401 · see citing works
Leading teachers' perspective on teacher-AI collaboration in education
Kim, J. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12109-5 · Cited by 376 · cited 1× · see citing works
“Studies [38] have noted that these tools can improve students’ ability to critically analyze, evaluate, and synthesize information by providing access to various resources and perspectives.”
Ruiz-Rojas, L. I., Acosta-Vargas, P., De-Moreta-Llovet, J., & Gonzalez-Rodriguez, M. (2023) · Sustainability · doi:10.3390/su151511524 · Cited by 340 · see citing works
Self-citationWhy and how to embrace AI such as ChatGPT in your academic life
Lin, Z. (2023) · Royal Society Open Science · doi:10.1098/rsos.230658 · Cited by 202 · see citing works
Why and how to embrace AI such as ChatGPT in your academic life
Lin, Z. (2023) · doi:10.31234/osf.io/sdx3j · Cited by 202 · see citing works
Salinas-Navarro, D. E., Vilalta-Perdomo, E., Michel-Villarreal, R., & Montesinos, L. (2024) · Education Sciences · doi:10.3390/educsci14010083 · Cited by 193 · cited 1× · see citing works
“Studies [30,33] indicate that these tools can create realistic learning scenarios, challenging students to apply critical thinking in practical contexts and encouraging a reflective approach to problems.”
Li, T., Ji, Y., & Zhan, Z. (2024) · Asia Pacific Journal of Education · doi:10.1080/02188791.2024.2305163 · Cited by 133 · cited 3× · see citing works
“A study [25] investigates the impact of collaborative learning approaches involving generative AI on the professional development of future teachers.”
InfluentialArtificial Intelligence: A Universal Virtual Tool to Augment Tutoring in Higher Education
Hemachandran, K., Verma, P., Pareek, P., Arora, N. R., Kumar, K. V. R., Ahanger, T. A., Pise, A. A., & Ratna, R. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/1410448 · Cited by 121 · see citing works
A systematic review of socio-technical gender bias in AI algorithms
Hall, P., & Ellis, D. (2023) · Online Information Review · doi:10.1108/oir-08-2021-0452 · Cited by 117 · see citing works
StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesis
Kang, M., Shin, J., & Park, J. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3306436 · Cited by 68 · see citing works
Ssemugenyi, F. (2023) · Cogent Education · doi:10.1080/2331186x.2023.2187943 · Cited by 56 · see citing works
Systematic review on mobile collaborative learning for engineering education
Peramunugamage, A., Ratnayake, U. W., & Karunanayaka, S. P. (2022) · Journal of Computers in Education · doi:10.1007/s40692-022-00223-1 · Cited by 54 · see citing works
Muca, E., Cavallini, D., Odore, R., Baratta, M., Bergero, D., & Valle, E. (2022) · Education Sciences · doi:10.3390/educsci12080573 · Cited by 42 · see citing works
Fairness in Design: A Framework for Facilitating Ethical Artificial Intelligence Designs
Zhang, J., Shu, Y., & Yu, H. (2023) · International Journal of Crowd Science · doi:10.26599/ijcs.2022.9100033 · Cited by 39 · see citing works
Sun, Y., Chen, J., Yao, B., Liu, J., Wang, D., Ma, X., Lu, Y., Xu, Y., & He, L. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3687035 · Cited by 32 · see citing works
Fotaris, P., Μάστορας, Θ., & Lameras, P. (2023) · European Conference on Games Based Learning · doi:10.34190/ecgbl.17.1.1870 · Cited by 30 · see citing works
Pedagogical access and ethical considerations in forensic anthropology and bioarchaeology
Spiros, M. C., Plemons, A. M., & Biggs, J. A. (2022) · Science & Justice · doi:10.1016/j.scijus.2022.03.008 · Cited by 29 · see citing works
Facilitating Global Collaboration and Knowledge Sharing in Higher Education With Generative AI
(2023) · Advances in higher education and professional development book series · doi:10.4018/979-8-3693-0487-7 · Cited by 22 · see citing works
Okuogume, A., & Toledano, N. (2024) · Sustainability · doi:10.3390/su16062272 · Cited by 21 · see citing works
Teachers’ Professional Skills as a Factor in the Development of Students’ Critical Thinking
Корешникова, Ю. Н., & Froumin, I. D. (2020) · Psychological Science and Education · doi:10.17759/pse.2020250608 · Cited by 18 · see citing works
Bansal, G., Mitchell, A., & Li, D. (2024) · Communications of the Association for Information Systems · doi:10.17705/1cais.05413 · Cited by 16 · see citing works
ChatGPT for generating stories and mind-maps in storytelling
Chen, X., Xie, H., Zou, D., & Wang, F. L. (2023) · International Conference on Behavioral, Economic, and Socio-Cultural Computing · doi:10.1109/besc59560.2023.10386441 · Cited by 12 · see citing works
Where Are we with Inclusive Digital Further Education? Accessibility Through Digitalization
Branig, M., Engel, C., Schmalfuß-Schwarz, J., et al. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-030-93904-5_3 · Cited by 8 · see citing works
Exploring the Challenges and Applications of Generative AI on Engineering Education in Mexico
Orduño-Osuna, J. H., Cota-Rivera, E. I., Raygoza-L., M. E., Jiménez-Sánchez, R., Limón-Molina, G. M., Bravo-Zanoguera, M. E., Mercado-Herrera, A., & Murrieta-Rico, F. N. (2023) · Advances in higher education and professional development book series · doi:10.4018/979-8-3693-0487-7.ch011 · Cited by 8 · see citing works
PAR: Towards a Reference Architecture for Accessible Platforms in Respiratory Therapies
Santórum, M., Carrión-Toro, M., Martinez, D. M., et al. (2024) · Applied Sciences · doi:10.3390/app14020840 · Cited by 8 · see citing works
The contribution of critical thinking to STEM disciplines at the time of generative intelligence
Guerra, E. (2024) · STEM Education · doi:10.3934/steme.2024005 · Cited by 8 · see citing works
AI, autonomous machines and human awareness: Towards shared machine-human contexts in medicine
Miller, D. D., & Wood, E. A. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-820543-3.00010-9 · Cited by 6 · see citing works
Digital Teaching Skills to Design Virtual Learning Classrooms with the 4PADAFE Methodology
Ruiz-Rojas, L. I., Martínez, C. P. C., & Cañizares, S. (2023) · Lecture notes in educational technology · doi:10.1007/978-981-99-0942-1_112 · Cited by 5 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Sardi, J., Darmansyah, Candra, O., Yuliana, D. F., Habibullah, Yanto, D. T. P., & Eliza, F. (2025) · International Journal of Engineering Pedagogy (iJEP) · doi:10.3991/ijep.v15i1.53379 · Cited by 105 · see citing works
Wijaya, T. T., Yu, Q., Cao, Y., He, Y., & Leung, F. K. S. (2024) · Behavioral Sciences · doi:10.3390/bs14111008 · Cited by 103 · see citing works
Deep, P. D., & Chen, Y. (2025) · Societies · doi:10.3390/soc15090247 · Cited by 65 · see citing works
Zhang, D., Wijaya, T. T., Wang, Y., Su, M., Li, X., & Damayanti, N. W. (2025) · Scientific Reports · doi:10.1038/s41598-025-99127-0 · Cited by 63 · see citing works
Ursavaş, Ö. F., Yalçın, Y., İslamoğlu, H., Bakır-Yalçın, E., & Cukurova, M. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00535-z · Cited by 69 · see citing works
AI-Powered E-Learning for Lifelong Learners: Impact on Performance and Knowledge Application
Ahn, H. Y. (2024) · Sustainability · doi:10.3390/su16209066 · Cited by 56 · see citing works
Naatonis, R. N., Rusijono, R., Jannah, M., & Malahina, E. A. U. (2024) · Qubahan Academic Journal · doi:10.48161/qaj.v4n3a919 · Cited by 24 · see citing works
Seker, O., Kwon, K., & Kocak, O. (2025) · Information Development · doi:10.1177/02666669251336368 · Cited by 21 · see citing works
Matobobo, C., Ncube, P. D. N., Ngesimani, N. L., Dzvapatsva, G. P., & Chinhamo, E. (2025) · 2025 IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon62633.2025.11016317 · Cited by 17 · see citing works
Alubthane, F. O. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1863931 · Cited by 12 · see citing works
Barus, O., Hidayanto, A. N., & Eitiveni, I. (2025) · Polyglot: Jurnal Ilmiah · doi:10.19166/pji.v21i2.10020 · Cited by 6 · see citing works
Transformative potential of generative AI in higher education teaching practices
Ututalum, C. S. (2025) · Environment and Social Psychology · doi:10.59429/esp.v10i9.3291 · Cited by 4 · see citing works
Krishnan, S. (2026) · Information Services and Use · doi:10.1177/18758789261452185 · Cited by 1 · see citing works
“37 Future research should pursue n = 2000 RCTs, 5-year behavioural tracking, and cross-national comparisons using shared materials, incorporating LIS-specific AI literacy measures.”
Krishnan, S. (2026) · Review of Artificial Intelligence in Education · doi:10.37497/rev.artif.intell.educ.v7ii.76
- Authors
- Ruiz-Rojas, L. I., Salvador-Ullauri, L., & Acosta-Vargas, P.
- Affiliations
- Universidad de las Fuerzas Armadas ESPE (EC)
- University of Alicante (ES)
- Universidad de Las Américas (EC)
- Corresponding author
- Acosta-Vargas, Patricia
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2024-06-24
- Volume
- 16
- Issue
- 13
- Pages
- 5367
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W4399973009
- Cited by
- 263
- References
- 35
- Citations by year
- 2026: 126 · 2025: 124 · 2024: 13
- FWCI
- 99.19
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sustainability (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Universidad de Las Américas (489.A.XIV.24)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Education › Technology-Enhanced Education Studies
- Keywords
- generative AI, higher education, critical thinking, cooperative learning, student perceptions, artificial intelligence adoption, university students, AI in teaching
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
