ARTIFICIAL INTELLIGENCE IN SCHOOL PSYCHOLOGY- PERSPECTIVES AND CHALLENGES
Keywords:
artificial intelligence, education, school transformation, technologyAbstract
The primary aim of this paper is to outline the main challenges and benefits of using artificial intelligence in the work of the school psychologist. A review has been made of the essence of artificial intelligence technology, as well as its specific application in school psychology. Artificial Intelligence (AI) is rapidly reshaping the field of school psychology, offering innovative tools that enhance the efficiency and effectiveness of psychological services in educational settings. By streamlining processes such as report writing and assessment, AI empowers school psychologists to focus more on direct interactions with students and timely interventions. Notable applications include AI-powered Early Warning Systems (EWS) that predict student risks and recommend tailored support, along with chatbots that provide immediate mental health resources. These advancements highlight AI's potential to transform traditional practices in school psychology and improve student mental health outcomes. Despite the promising benefits, the integration of AI in school psychology raises significant ethical concerns, particularly regarding algorithmic bias and data privacy. School psychologists play a vital role in advocating for equitable practices and ensuring cultural responsiveness in AI-assisted evaluations. This includes the need for thorough oversight to mitigate unintended consequences and maintain the integrity of psychological assessments. As AI continues to evolve, the profession must grapple with these ethical dilemmas while harnessing technology's potential to address the growing demand for mental health support among students. In addition to enhancing administrative efficiency and intervention strategies, AI tools are poised to expand the reach of mental health services, particularly in under-resourced areas where access to trained professionals is limited. The ability of AI to analyze large datasets enables school psychologists to identify trends and prioritize interventions effectively, thereby addressing the unique needs of diverse student populations. However, the reliance on AI also presents challenges, such as the risk of diminishing critical thinking skills among students and the potential for over-reliance on technology in therapeutic settings.
References
Abukmeil, A., Ferrari, S., Genovese, A., Piuri, V., & Scotti, F. (20210. A survey of unsupervised generative models for exploratory data analysis and representation learning. ACM Comput.Surv. 54 (5), 1–40.
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: adressing ethical challenges in K-12 settings. AI Ethics 2 (3), 431–440. https://doi.org/10.1007/ s43681-021-00096-7.
Ali, O., Murray, P., Momin, M., Dwivedi, Y., & Malik, T. (2024). The effects of artificial intelligence applications in educational settings: Challenges and strategies. Technological Forecasting & Social Change, Vol. 199. https://doi.org/10.1016/j.techfore.2023.123076.
Becchetti, L., Bruni, L., & Zamagni, S. (2020). New theories of the firm. In: The Microeconomics of Wellbeing and Sustainability, first ed., vol. 1. Academic Press, pp. 199–226. https://doi.org/10.1016/C2017-0-04428-2.
Bogdanova, S., Stepanova, M., Matytcina, M., Plastinina, N., Plekhanova, Y., & Kudritskaya, M. (2024). AI technologies in training PhD students. Proceedings - 2024 4th International Conference on Technology Enhanced Learning in Higher Education, TELE 2024, pp. 153–156. https://doi.org/10.1109/ TELE62556.2024.10605642.
Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education. Educational Technology & Society, 25(1), 28-47.
Farmer, R. L., Lockwood, A., Floyd, R. G., & Sisco, A. (2025, March 18). How Are School Psychologists Using Artificial Intelligence in 2024? A Descriptive Study. https://doi.org/10.31234/osf.io/cf2m3_v1.
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 1–23. https://doi.org/10.1007/s40593-021-00239-1.
Hu, K. (2023). ChatGPT Sets Record for Fastest-Growing User Base. Reuters. Available at: https://www.reuters.com/technology/chatgpt-sets-record-fastest-growinguser-base- analyst-note-2023-02-01/.
Gui, J., Sun, Z., Wen, Y., Tao, D., & Ye, J. (2023). A review on generative adversarial networks: algorithms, theory, and applications. IEEE Trans. Knowl. Data Eng. 35 (4), 3313–3332.
Johnston, H., Wells, R.F., Shanks, E.M., Boey, T., & Parsons, B.N. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. Int. J. Edu. Integr. 20 (1). https://doi.org/10.1007/s40979-024-00149-4.
Jovanovic, M., & Campbell, M. (2022). Generative artificial intelligence: trends and prospects. Computer 55 (10), 107–112.
Kwon, S., & Park, A. (2023) Examining Thematic and Emotional Differences across Twitter, Reddit, and YouTube: The Case of COVID-19 Vaccine Side Effects. Computers in Human Behavior, 144, Article ID: 107734.
https://doi.org/10.1016/j.chb.2023.107734
Mallin, B., Beimcik, J., & Hopfner, L. (2012). Teacher ratings of three school psychology report recommendation styles. Canadian Journal of School Psychology, 27(3), 258-273.
Martin, F., Zhuang, M., & Schaefer, D. (2024). Systematic review of research on artificial intelligence in K-12 education (2017–2022). Computers and Education: Artificial Intelligence, 6, 100195. https://doi.org/10.1016/j.caeai.2023.100195.
Martin, F., Ritzhaupt, A., Kumar, S., & Budhrani, K. (2019). Award-winning faculty online teaching practices: Course design, assessment and evaluation, and facilitation. The Internet and Higher Education, 42, 34–43. https://doi.org/10.1016/j.iheduc.2019.04.001.
Memarian, B., & Doleck, T. (2023). Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education: a systematic review. Comput. Educ. Artif. Intell. 5, 100152. https://doi.org/10.1016/j. caeai.2023.100152.
Moser, C., den Hond, F., & Lindebaum, D. (2022). Morality in the age of artificially intelligent algorithms. Acad. Manag. Learn. Educ. 21 (1), 139–155. https://doi.org/ 10.5465/amle.2020.0287.
Mouta, A., Pinto-Llorente, A. M., & Torrecilla-S´anchez, E. M. (2023). Uncovering blind spots in education ethics: Insights from a systematic literature review on artificial intelligence in education. International Journal of Artificial Intelligence in Education, 1–40. https://doi.org/10.1007/s40593-023-00384-9.
Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137- 161. https://doi.org/10.1007/s11423-023-10203-6.
San-Jose, L., Gonzalo, J.F., & Ruiz-Roque˜ ni, M. (2022). The management of moral hazard through the implementation of a Moral Compliance Model (MCM). Eur Res. Manag. Business Econ. 28 (1). https://doi.org/10.1016/j.iedeen.2021.100182.
Vallis, C., Wilson, S., Gozman, D., & Buchanan, J. (2024). Student perceptions of AI- Generated avatars in teaching business ethics: we might not be impressed. Postdigital Sci. Edu. 6 (2), 537–555. https://doi.org/10.1007/s42438-023-00407-7.
Wright, J. (2021). Applications of Artificial Intelligence (AI) in School Psychology.
Zhuang, M., Long S., Martin, F., & Castellanos-Reyes, D. (2025). The affordances of Artificial Intelligence (AI) and ethical considerations across the instruction cycle: A systematic review of AI in online higher education. The Internet and Higher Education. https://doi.org/10.1016/j.iheduc.2025.101039.https://teachflow.ai/ai-in-education-impact/.
Мар, Б. (2024). https://nio.government.bg/.
