Published
2025-04-19
Section
Research Articles
License
Copyright (c) 2025 JuanJuan Zhang, Aiza Maslan @ Baharudin

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The journal adopts the Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), which means that anyone can reuse and redistribute the materials for non-commercial purposes as long as you follow the license terms and the original source is properly cited.
Author(s) shall retain the copyright of their work and grant the Journal/Publisher rights for the first publication with the work concurrently licensed since 2023 Vol.8 No.2.
Under this license, author(s) will allow third parties to download, reuse, reprint, modify, distribute and/or copy the content under the condition that the authors are given credit. No permission is required from the authors or the publisher.
This broad license intends to facilitate free access, as well as the unrestricted use of original works of all types. This ensures that the published work is freely and openly available in perpetuity.
By providing open access, the following benefits are brought about:
- Higher Visibility, Availability and Citations-free and unlimited accessibility of the publication over the internet without any restrictions increases citation of the article.
- Ease of search-publications are easily searchable in search engines and indexing databases.
- Rapid Publication – accepted papers are immediately published online.
- Available for free download immediately after publication at https://esp.as-pub.com/index.php/ESP

Copyright Statement
1.The authors certify that the submitted manuscripts are original works, do not infringe the rights of others, are free from academic misconduct and confidentiality issues, and that there are no disputes over the authorship scheme of the collaborative articles. In case of infringement, academic misconduct and confidentiality issues, as well as disputes over the authorship scheme, all responsibilities will be borne by the authors.
2. The author agrees to grant the Editorial Office of Environment and Social Psychology a licence to use the reproduction right, distribution right, information network dissemination right, performance right, translation right, and compilation right of the submitted manuscript, including the work as a whole, as well as the diagrams, tables, abstracts, and any other parts that can be extracted from the work and used in accordance with the characteristics of the journal. The Editorial Board of Environment and Social Psychology has the right to use and sub-licence the above mentioned works for wide dissemination in print, electronic and online versions, and, in accordance with the characteristics of the periodical, for the period of legal protection of the property right of the copyright in the work, and for the territorial scope of the work throughout the world.
3. The authors are entitled to the copyright of their works under the relevant laws of Singapore, provided that they do not exercise their rights in a manner prejudicial to the interests of the Journal.
About Licence
Environment and Social Psychology is an open access journal and all published work is available under the Creative Commons Licence, Authors shall retain copyright of their work and grant the journal/publisher the right of first publication, and their work shall be licensed under the Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
Under this licence, the author grants permission to third parties to download, reuse, reprint, modify, distribute and/or copy the content with attribution to the author. No permission from the author or publisher is required.
This broad licence is intended to facilitate free access to and unrestricted use of original works of all kinds. This ensures that published works remain free and accessible in perpetuity. Submitted manuscripts, once accepted, are immediately available to the public and permanently accessible free of charge on the journal’s official website (https://esp.as-pub.com/index.php/ESP). Allowing users to read, download, copy, print, search for or link to the full text of the article, or use it for other legal purposes. However, the use of the work must retain the author's signature, be limited to non-commercial purposes, and not be interpretative.
Click to download <Agreement on the Licence for the Use of Copyright on Environmental and Social Psychology>.
How to Cite
The impact of artificial intelligence and virtual teachers on students' learning stress and anxiety: A social psychological analysis
JuanJuan Zhang
School of Humanities,Universiti Sains Malaysia, Pulau Pinang,11800,Malaysia
Aiza Maslan @ Baharudin
School of Humanities,Universiti Sains Malaysia, Pulau Pinang,11800,Malaysia
DOI: https://doi.org/10.59429/esp.v10i4.3515
Keywords: artificial intelligence;virtual teachers;learning stress;UTAUT model;educational psychology
Abstract
This study explores the impact of Artificial Intelligence (AI) and virtual teachers on students' learning stress and anxiety, applying the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The research investigates key factors influencing students' perceptions and usage of AI-driven learning tools, including Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Behavioral Intention (BI), and Use Behavior (UB). Data were collected from 100 students, revealing generally positive attitudes towards AI tools. The results show that AI's potential to reduce learning stress and improve academic performance (PE) significantly influences students' intention to use these tools in the future (BI). Ease of use (EE) and social support (SI) were also found to positively affect behavioral intention, while facilitating conditions (FC), such as access to necessary resources and technical support, played a crucial role in determining the actual use of AI tools. The study highlights that students are more likely to adopt AI-based educational systems when they perceive them as useful, easy to use, and adequately supported. These findings suggest that fostering positive perceptions, ensuring sufficient resources, and leveraging social influence can significantly enhance the adoption of AI tools, ultimately reducing learning stress and anxiety.
References
[1]. 1.Airaj, M. (2024). Ethical artificial intelligence for teaching-learning in higher education. Education and Information Technologies, 29(13), 17145-17167.
[2]. 2.Akhtar, M. (2024). Exploring the Role of AI-Driven Feedback in Influencing Students' Anxiety and Stress During Academic Assessments. Journal of Interdisciplinary Educational Studies, 4(2), 39-53.
[3]. 3.Beketov, V., Lebedeva, M., & Taranova, M. (2024). The use of artificial intelligence in teaching medical students to increase motivation and reduce anxiety during academic practice. Current Psychology, 43(16), 14367-14377.
[4]. 4.Bu, Q. (2022). Ethical risks in integrating artificial intelligence into education and potential countermeasures. Science Insights, 41(1), 561-566.
[5]. 5.Chen, C., Hu, W., & Wei, X. (2024). From anxiety to action: exploring the impact of artificial intelligence anxiety and artificial intelligence self-efficacy on motivated learning of undergraduate students. Interactive Learning Environments, 1-16.
[6]. 6.Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
[7]. 7.Elgohary, H. K. A., & Al-Dossary, H. K. (2022). The effectiveness of an educational environment based on artificial intelligence techniques using virtual classrooms on training development. International Journal of Instruction, 15(4), 1133-1150.
[8]. 8.Hopcan, S., Türkmen, G., & Polat, E. (2024). Exploring the artificial intelligence anxiety and machine learning attitudes of teacher candidates. Education and Information Technologies, 29(6), 7281-7301.
[9]. 9.Horton, R. P., Buck, T., Waterson, P. E., & Clegg, C. W. (2001). Explaining intranet use with the technology acceptance model. Journal of information technology, 16, 237-249.
[10]. 10.Jiang, R. (2022). How does artificial intelligence empower EFL teaching and learning nowadays? A review on artificial intelligence in the EFL context. Frontiers in Psychology, 13, 1049401.
[11]. 11.Lee, Y., Kozar, K. A., & Larsen, K. R. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for information systems, 12(1), 50.
[12]. 12.Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & management, 40(3), 191-204.
[13]. 13.Ma, J., Wang, P., Li, B., Wang, T., Pang, X. S., & Wang, D. (2025). Exploring user adoption of ChatGPT: A technology acceptance model perspective. International Journal of Human–Computer Interaction, 41(2), 1431-1445.
[14]. 14.Mogaji, E., Viglia, G., Srivastava, P., & Dwivedi, Y. K. (2024). Is it the end of the technology acceptance model in the era of generative artificial intelligence? International Journal of Contemporary Hospitality Management, 36(10), 3324-3339.
[15]. 15.Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y. (2022). Acceptance model of artificial intelligence (AI)-based technologies in construction firms: Applying the Technology Acceptance Model (TAM) in combination with the Technology–Organisation–Environment (TOE) framework. Buildings, 12(2), 90.
[16]. 16.Naseeb, J., & Bhatti, N. (2024). Ethical Considerations of AI in Educational Curriculum. Multidisciplinary Journal of Emerging Needs of Curriculum, 1(1), 30-38.
[17]. 17.Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and information technologies, 28(4), 4221-4241.
[18]. 18.Venkatesh, V., and Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies, Management Science, 46(2), 186-204.
[19]. 19.Venkatesh, V., Morris, M.G., Davis, G.B., and Davis, F.D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478.






