From AI adoption to underperformance? Investigating the impact of interactive AI tools on student outcomes in higher education
Abstract
This study explores the paradoxical effects of interactive AI tools on university students’ academic performance. Although technologies such as chatbots and virtual assistants are designed to enhance learning through personalised experiences, inadequate integration into curricula may lead to adverse outcomes. Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2), this research examines determinants of students’ behavioural intention to use AI tools and their subsequent impact on academic achievement. Data collected from 407 students across Spanish and French universities reveal that performance expectancy, social influence, hedonic motivation, price value, and habit significantly predict intention to use, whereas effort expectancy and facilitating conditions do not. Importantly, actual usage of these tools shows a statistically significant negative association with academic performance, suggesting that unstructured adoption can be counterproductive. These findings underscore the need for institutional strategies to ensure pedagogically sound integration of AI technologies. While students perceive AI as a means to improve outcomes, improper use may result in lower grades. The study offers critical implications for higher education, highlighting the necessity of balancing technological innovation with effective instructional design to maximise learning benefits.
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Scholars are concerned about genAI's overall effects on academic performance as well as capacities for reading and thinking critically, exercising evaluative judgement, thinking creatively and independently, and collaborating.
“Scholars are concerned about genAI's overall effects on academic performance (Castro-Lopez et al., 2026) as well as capacities for reading and thinking critically (Dguidegue, 2025;Olsson, 2026;Rahman et al., 2025), exercising evaluative judgement (Bearman et al., 2024), thinking creatively and independently (Isiaku et al., 2024;Newell et al., 2024;Xia et al., 2024), and collaborating (Xia et al.,”
From Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education (2026) · cites this paper as Castro-Lopez et al., 2026
Cites
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 · see citing works
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941 · see citing works
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459 · see citing works
When to Use and How to Report the Results of PLS-SEM
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019) · European Business Review · doi:10.1108/ebr-11-2018-0203 · Cited by 27,541 · see citing works
Pls-Sem: indeed a silver bullet
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679190202 · Cited by 21,631 · see citing works
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756 · see citing works
Structural equation models with unobservable variables and measurement error: Algebra and statistics
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800313 · Cited by 13,287 · see citing works
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021) · Classroom Companion: Business · doi:10.1007/978-3-030-80519-7 · Cited by 10,343 · see citing works
Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead
University of Arkansas, Venkatesh, V., Thong, J., Hong Kong University of Science and Technology, Xu, X., & The Hong Kong Polytechnic University (2016) · Journal of the Association for Information Systems · doi:10.17705/1jais.00428 · Cited by 2,513 · see citing works
Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024) · Business & Information Systems Engineering · doi:10.1007/s12599-023-00834-7 · Cited by 1,409 · see citing works
Thompson, C. G., Kim, R. S., Aloe, A. M., & Becker, B. J. (2017) · Basic and Applied Social Psychology · doi:10.1080/01973533.2016.1277529 · Cited by 1,092 · see citing works
Ouyang, F., Zheng, L., & Jiao, P. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10925-9 · Cited by 831 · see citing works
Improving PLS-SEM Use for Business Marketing Research
Guenther, P., Guenther, M., Ringle, C. M., Zaefarian, G., & Cartwright, S. (2023) · Industrial Marketing Management · doi:10.1016/j.indmarman.2023.03.010 · Cited by 800 · see citing works
Artificial intelligence: a survey on evolution, models, applications and future trends
Lu, Y. (2019) · Journal of Management Analytics · doi:10.1080/23270012.2019.1570365 · Cited by 641 · see citing works
Sajja, R., Sermet, Y., Cikmaz, M., Cwiertny, D., & Demir, I. (2024) · Information · doi:10.3390/info15100596 · Cited by 620 · see citing works
Lee, Y.-F., Hwang, G.-J., & Chen, P.-Y. (2022) · Educational Technology Research and Development · doi:10.1007/s11423-022-10142-8 · Cited by 323 · see citing works
Thakkar, J. J. (2020) · Studies in systems, decision and control · doi:10.1007/978-981-15-3793-6 · Cited by 305 · see citing works
Use of ChatGPT at University as a Tool for Complex Thinking: Students’ Perceived Usefulness
Romero-Rodríguez, J.-M., Ramírez-Montoya, M.-S., Buenestado-Fernández, M., & Lara-Lara, F. (2023) · Journal of New Approaches in Educational Research · doi:10.7821/naer.2023.7.1458 · Cited by 277 · see citing works
Batista, J., Mesquita, A., & Carnaz, G. (2024) · Information · doi:10.3390/info15110676 · Cited by 256 · see citing works
A Systematic Review of Generative AI for Teaching and Learning Practice
Ogunleye, B., Zakariyyah, K. I., Ajao, O., Olayinka, O., & Sharma, H. (2024) · Education Sciences · doi:10.3390/educsci14060636 · Cited by 251 · see citing works
Tian, W., Ge, J., Zhao, Y., & Zheng, X. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1268549 · Cited by 232 · see citing works
Liu, C., Hou, J., Tu, Y.-F., Wang, Y., & Hwang, G.-J. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2021.2012812 · Cited by 231 · see citing works
Gil de Zúñiga, H., Goyanes, M., & Durotoye, T. (2024) · Political Communication · doi:10.1080/10584609.2023.2290497 · Cited by 198 · see citing works
Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Vighio, M. S., Alblehai, F., Soomro, R. B., & Shutaleva, A. V. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12599-x · Cited by 187 · see citing works
Artificial intelligence in educational leadership: a comprehensive taxonomy and future directions
Sposato, M. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00517-1 · Cited by 183 · see citing works
Sebastián, M. G. D. B., Guede, J. R. S., & Antonovica, A. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.993935 · Cited by 180 · see citing works
From explainable to interactive AI: A literature review on current trends in human-AI interaction
Raees, M., Meijerink, I., Lykourentzou, I., Khan, V.-J., & Papangelis, K. (2024) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2024.103301 · Cited by 180 · see citing works
Acosta-Enriquez, B. G., Farroñán, E. V. R., Zapata, L. I. V., García, F. S. M., Rabanal-León, H. C., Angaspilco, J. E. M., & Bocanegra, J. C. S. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e38315 · Cited by 180 · see citing works
Ni, A., & Cheung, A. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-11305-z · Cited by 169 · see citing works
Lee, S. J., & Kwon, K. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100211 · Cited by 169 · see citing works
Lavidas, K., Voulgari, I., Papadakis, S., Athanassopoulos, S., Anastasiou, A., Filippidi, A., Komis, V., & Karacapilidis, N. I. (2024) · Information · doi:10.3390/info15060314 · Cited by 165 · see citing works
Gado, S., Kempen, R., Lingelbach, K., & Bipp, T. (2022) · Psychology Learning & Teaching · doi:10.1177/14757257211037149 · Cited by 153 · see citing works
Understanding University Students’ Acceptance of ChatGPT: Insights from the UTAUT2 Model
Grassini, S., Aasen, M. L., & Møgelvang, A. (2024) · Applied Artificial Intelligence · doi:10.1080/08839514.2024.2371168 · Cited by 151 · see citing works
Interactive AI With Retrieval-Augmented Generation for Next Generation Networking
Zhang, R., Du, H., Liu, Y., Niyato, D., Kang, J., Sun, S., Shen, X., & Poor, H. V. (2024) · IEEE Network · doi:10.1109/mnet.2024.3401159 · Cited by 147 · see citing works
Zheng, Y., Wang, Y.-B., Liu, K. S.-X., & Jiang, M. (2024) · Education and Information Technologies : Official Journal of the IFIP technical committee on Education · doi:10.1007/s10639-024-12763-3 · Cited by 133 · see citing works
Li, Q., & Qin, Y. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04700-8 · Cited by 131 · see citing works
Examining Students’ Acceptance and Use of ChatGPT in Saudi Arabian Higher Education
Sobaih, A. E. E., Elshaer, I. A., & Hasanein, A. M. (2024) · European Journal of Investigation in Health Psychology and Education · doi:10.3390/ejihpe14030047 · Cited by 123 · see citing works
Al-kfairy, M. (2024) · Applied System Innovation · doi:10.3390/asi7060110 · Cited by 123 · see citing works
Almahri, F. A. A. J., Bell, D., & Merhi, M. (2020) · International Conference on Information Management · doi:10.1109/icim49319.2020.244712 · Cited by 116 · see citing works
Research Methodology and Scientific Writing
Thomas, C. G. (2021) · Springer eBooks · doi:10.1007/978-3-030-64865-7 · Cited by 111 · see citing works
Ali, I., Warraich, N. F., & Butt, K. (2024) · Information Development · doi:10.1177/02666669241257206 · Cited by 94 · see citing works
Tao, W., Yang, J., & Qu, X. (2024) · JMIR Medical Education · doi:10.2196/57132 · Cited by 85 · see citing works
Rethinking Plagiarism in the Era of Generative AI
Hutson, J. (2024) · Journal of Intelligent Communication · doi:10.54963/jic.v4i1.220 · Cited by 83 · see citing works
Şova, R., Tudor, C. D., Tartavulea, C. V., & Dieaconescu, R. I. (2024) · Electronics · doi:10.3390/electronics13183632 · Cited by 82 · see citing works
Wijaya, T. T., Su, M., Cao, Y., Weinhandl, R., & Houghton, T. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-12837-2 · Cited by 80 · see citing works
Msambwa, M. M., Wen, Z., & Daniel, K. (2025) · European Journal of Education · doi:10.1111/ejed.12909 · Cited by 76 · see citing works
Chen, G., Fan, J., & Azam, M. (2024) · Journal of Librarianship and Information Science · doi:10.1177/09610006241269189 · Cited by 73 · see citing works
Ma, W., Wen-jing, M., Hu, Y., & Xinyu, B. I. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13128-6 · Cited by 71 · see citing works
C., S. B. G., Bhandari, P., Gurung, S. K., Srivastava, E., Ojha, D., & Dhungana, B. R. (2024) · Cogent Education · doi:10.1080/2331186x.2024.2403287 · Cited by 71 · see citing works
Slyke, C. V., Johnson, R. D., & Sarabadani, J. (2023) · Communications of the Association for Information Systems · doi:10.17705/1cais.05301 · Cited by 67 · see citing works
An AI-enabled feedback-feedforward approach to promoting online collaborative learning
Zheng, L., Fan, Y., Chen, B., Huang, Z., LeiGao, & Long, M. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12292-5 · Cited by 59 · see citing works
Saihi, A., Ben‐Daya, M., & Hariga, M. A. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13023-0 · Cited by 54 · see citing works
Between tech and text: the use of generative AI in Palestinian universities - a ChatGPT case study
Hamamra, B. T., Mayaleh, A., & Khlaif, Z. N. (2024) · Cogent Education · doi:10.1080/2331186x.2024.2380622 · Cited by 53 · see citing works
Durak, H. Y., & Onan, A. (2024) · Current Psychology · doi:10.1007/s12144-024-06072-8 · Cited by 52 · see citing works
Awal, M. R., & Haque, M. E. (2024) · Journal of Applied Research in Higher Education · doi:10.1108/jarhe-11-2023-0514 · Cited by 48 · see citing works
Cui, P., & Alias, B. S. (2024) · Journal of Infrastructure Policy and Development · doi:10.24294/jipd.v8i11.8390 · Cited by 47 · see citing works
A STUDY ON "AI IN EDUCATION: OPPORTUNITIES AND CHALLENGES FOR PERSONALIZED LEARNING
Lydia, E. G., Vidhyavathi, P., & Malathi, P. (2023) · Industrial Engineering Journal · doi:10.36893/iej.2023.v52i05.750-759 · Cited by 37 · see citing works
Qehaja, A. B. (2025) · foresight · doi:10.1108/fs-04-2024-0079 · Cited by 28 · see citing works
Non-probabilistic surveys and sampling in the human dimensions of fisheries
Howarth, A. T., Cooke, S. J., Nguyen, V. M., et al. (2024) · Reviews in Fish Biology and Fisheries · doi:10.1007/s11160-023-09831-1 · Cited by 28 · see citing works
Meta-Analysis of Influencing Factors on the Use of Artificial Intelligence in Education
Lu, W., & Lin, C. (2024) · The Asia-Pacific Education Researcher · doi:10.1007/s40299-024-00883-w · Cited by 21 · see citing works
Xiaohong, L., Zhang, J., Xiaoming, C., & Beina, Z. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2024.2343752 · Cited by 21 · see citing works
Integrating Generative AI in Education to Achieve Sustainable Development Goals
Doshi, R., Dadhich, M., Poddar, S., et al. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-2440-0 · Cited by 20 · see citing works
Impact of Educational AI on Students' Studying Habits and Academic Performance
Khalkho, R., Singh, S., Gupta, N., & Srivastava, P. (2024) · International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA) · doi:10.1109/icaiqsa64000.2024.10882178 · Cited by 13 · see citing works
Predictive analysis of Metaverse usage intention in the Spanish University
Castro-López, A., Cervero, A., & Blanco, L. Á. (2024) · Journal of Computers in Education · doi:10.1007/s40692-024-00335-w · Cited by 11 · see citing works
Self-citationExploration of employability perceptions with blended multi-criteria decision-making methods
Castro-López, A., Monteiro, S., Bernardo, A. B., et al. (2021) · Education + Training · doi:10.1108/et-07-2021-0296 · Cited by 9 · see citing works
Investigating the Efficacy of ChatGPT-3.5 for Tutoring in Chinese Elementary Education Settings
Bai, Y., Li, J., Shen, J., & Zhao, L. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3464560 · Cited by 8 · see citing works
Flagged first, then by citations
Research works printed but not linked: 6
- Falk, R. F., and N. B. Miller. 1992. A Primer for Soft Modeling. University of Akron Press.
- Kang, H. 2022. “Effects of Artificial Intelligence (AI) and Native Speaker Interlocutors on ESL Learners’ Speaking Ability and Affective Aspects.” Multimedia-Assisted Language Learning 25 (2): 9–43.
- Kharina, O. 2023, September. “Successful Practices of Artificial Intelligence Technologies in Educational Activities.” In International Conference on Interactive Collaborative Learning, edited by M. E. Aure, U. R. Cukierman, E. V. Vendrell, and E. Tovar, 511–529. Cham: Springer Nature Switzerland.
- Rega, A., R. Di Fuccio, and E. Inderst. 2024, May. “Learning Enhancer Tools: A Theoretical Framework to Use AI Chatbot in Education and Learning Applications.” In International Conference on Human-Computer Interaction, edited by H. Degen and S. Ntoa, 409–419. Cham: Springer Nature Switzerland.
- Ringle, C. M., S. Wende, and J. M. Becker. 2024. SmartPLS 4. Bönningstedt: SmartPLS. https://www.smartpls.com.
- Rouhiainen, L. 2018. Artificial Intelligence: 101 Things You Must Know Today about our Future. Vol. 1. Lasse Rouhiainen.
Cited by
Sorted by citations
Castro-López, A., Abed, M. E., Cervero, A., & Iglesias, V. (2026) · Education + Training · doi:10.1108/et-10-2025-0812 · Cited by 2 · see citing works
Self-citationToward Partnership Ethics for Generative Artificial Intelligence in Higher Education
Gillette, M., Wackenhut, A., & Olsson, E. (2026) · Journal of University Teaching and Learning Practice · doi:10.53761/yf2gt848
“Scholars are concerned about genAI ’s overall effects on academic performance (Castro-Lopez et al., 2026) as well as capacities for reading and thinking critically (Dguidegue, 2025; Olsson, 2026; Rahman et al., 2025), exercising evaluative judgement (Bearman et al., 2024), thinking creatively and…”
Zarrinabadi, N., Jabbari, N., Amini, F., & Eshaghi, S. M. (2026) · European Journal of Psychology of Education · doi:10.1007/s10212-026-01157-3
“…such as artificial intelligence (AI), large language model–based chatbots, and interactive digital learning platforms are rapidly transforming how students learn and engage in higher-education contexts (Castro-Lopez et al., 2025, 2026; Evange-lista, 2025; Stan et al., 2025; Yigci et al., 2025).”
From promise to practice? Unpacking the impact of artificial intelligence on teacher education
McGrath, C., Pargman, T. C., & Stenliden, L. (2026) · Teaching Education · doi:10.1080/10476210.2026.2692890
“We acknowledge that these reservations point to a pressing need for targeted teacher training that equips educators to engage with AI critically and responsibly, rather than adopting it as a ready-made solution (Castro-Lopez et al., 2026).”
- Authors
- Castro-Lopez, A., El Abed, M., Cervero, A., & Álvarez-Blanco, L.
- Affiliations
- University of Oviedo
- ESCE Business School, OMNES Education
- Venue
- European Journal of Higher Education
- Publisher
- Informa UK Limited
- Published
- 2026-01-28
- Pages
- 1-22
- ISSN
- 2156-8235 (ISSN-L)
- 2156-8243
- OpenAlex
- W7125973135
- Cited by
- 3
- References
- 63
- Citations by year
- 2026: 3
- FWCI
- 25.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Journal of Higher Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- chatbots, virtual assistants, academic performance, UTAUT2, performance expectancy, social influence, hedonic motivation, price value, habit, AI integration in curriculum, higher education
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