POTENTIAL OF ARTIFICIAL INTELLIGENCE IN SOCIAL WORK EDUCATION
Keywords:
artificial intelligence, social work education, higher education, undergraduate students, opportunitiesAbstract
In recent years, there has been a continuously increasing interest in artificial intelligence and its application in almost all spheres of individual and public life. The same trend is observed in the field of education, affecting almost all educational levels and disciplines. Research interest has also increased, with studies focusing on adaptive and personalized learning, intelligent assessment and management, profiling and prediction, and the development of new products. Higher education is among the most frequently studied contexts. Research addresses both the opportunities provided by artificial intelligence and the associated risks and ethical challenges. On the other hand, the quality of education is one of the main objectives of development strategies at all levels of organization and governance. The issue of the effective implementation of artificial intelligence in the educational system, with a focus on human beings and their well-being, is gradually emerging as one of the most significant questions from both theoretical and practical perspectives.
The outlined trend of the widespread integration of artificial intelligence into education, together with the issues of quality and effectiveness, also affects social work education, whose primary objective is to develop skills for working with people in ways that promote their well-being. The present study presents the results of a survey examining the opinions of social work students regarding the possibilities and future of artificial intelligence in the educational process. Frequency analysis was applied to the quantitative data, while content analysis was used to analyze the responses to the open-ended questions. The study included 78 undergraduate social work students from different years of study. The results indicate a positive perception of the opportunities offered by artificial intelligence, confidence in its usefulness and future expansion, and, at the same time, a tendency to critically evaluate the different aspects of its impact on education and social development. The findings also identify the need for additional training for both students and academic staff in order to optimize effectiveness and prevent potential risks. Investigating the opinions of the learners themselves is an important element in planning the effective implementation of artificial intelligence. Despite the limitations of the study, the analysis of the data provides directions for further research with an experimental and practice-oriented focus
References
Стойкова, М. (2024). Възможности и предизвикателства в дигитализацията на обучението по социална работа. В Сборник с доклади от Втора национална конференция Дигитална трансформация на образованието –проблеми и решения, 132-136.
Стойкова, М. (2025). Приложение на изкуствения интелект в социалната работа. В Сборник с доклади от шеста научно-практическа конференция с международно участие „Социална работа, мениджмънт и социално развитие: съвременни предизвикателства, перспективи и иновативни практики, 39-47
Стойкова, М. (2026). Изкуствен интелект и стандарти за обучение по социална работа. В Сборник с доклади от Четвърта национална конференция Дигитална трансформация на образованието –проблеми и решения, 787-791.
Ahn, E., Choi, M., Fowler, P., & Song, I. H. (2025). Artificial intelligence (AI) literacy for social work: Implications for core competencies. Journal of the Society for Social Work and Research, 16(1), 9–26. https://doi.org/10.1086/735187
Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gašević, D., Martinez-Maldonado, R. (2023). Human-Centred Learning Analytics and AI in Education: a Systematic Literature Review. License: CC BY 4.0arXiv:2312.12751v1 [cs.CY] 20 Dec 2023
An, R., Lindsey, M. (2026). Artificial Intelligence In Social Work. Brinding Technology and Humanity, Springer
Asakura, K., Occhiuto, K., Tarshis, S., & Dubrowski, A. (2021). Designing and Conducting Healthcare Simulations: Contributions From Social Work. Cureus, 13(7), e16193. https://doi.org/10.7759/cureus.16193
Báez, J. C., Bjugstad, A., Park, T. K., Jones, J. L., Bidwell, L. N., Sage, M., & Hitchcock, L. I. (2025). Social Work Educators Innovating With Generative AI: An Exploratory Study. Journal of Social Work Education, 61(1), 14–29. https://doi.org/10.1080/10437797.2024.2411170
European Commission (EC) (2026). Living guidelines on the responsible use of generative AI in research. ERA Forum Stakeholders’document. Brussels: European Commission
Fang, Y., An, R., Fang, C. (2026). AI in Social Work Education. In: An, R., Lindsey, M.A. (eds) Artificial Intelligence in Social Work. Springer, Cham. https://doi.org/10.1007/978-3-032-18443-6_20
Filder, R., Silverman, L. (1988). Learning and Teaching Style in Engineering Education. Engineering Education, 78 (7), 674-681
Garkisch, M., Goldkind, L. (2025). Considering a Unified Model of Artificial Intelligence Enhanced Social Work: A Systematic Review. J. Hum. Rights Soc. Work 10, 23–42 (2025). https://doi.org/10.1007/s41134-024-00326-y
Kaplan, A., Haenlein, M. (2020). Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons, 63, 37-50.
Mallik, S. & Gangopadhyay, A. (2023). Proactive and Reactive Engagement of Artificial Intelligence Methods for Education: A Review. arXive.2301.10231[cs.CY]
Rodriguez, M. Y., Goldkind, L., Victor, B. G., Hiltz, B., & Perron, B. E. (2024). Introducing Generative Artificial Intelligence Into the MSW Curriculum: A Proposal for the 2029 Educational Policy and Accreditation Standards. Journal of Social Work Education, 60(2), 174–182. https://doi.org/10.1080/10437797.2024.2340931
Zawacki-Richter,O., Marín, V. I., Bond, M., Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators?. Int J Educ Technol High Educ 16, 39 (2019). https://doi.org/10.1186/s41239-019-0171-0
UNESKO (2021). Recommendatio on the Ethics of Artificial Intelligence. Paris: United Nations Educational, Scientific and Cultural Organization. Paris: United Nations Educational, Scientific and Cultural Organization
UNESKO (2023). Guidance for generative AI in Education and research.
Wallengren-Lynch, M. (2026). Towards a framework for digital literacy in social work education in a time of artificial intelligence. Social Work Education, 1–18. https://doi.org/10.1080/02615479.2026.2660786
Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems With Applications, 252
Weber, J., & Goldkind, L. (2026). Promoting AI literacy in social work education: lessons from an interdisciplinary course for social work students. Social Work Education, 1–17. https://doi.org/10.1080/02615479.2026.2635471
Yang, F., Liechty, J.M. (2026). Building AI Literacy and Competency in Social Work. In: An, R., Lindsey, M.A. (eds) Artificial Intelligence in Social Work. Springer, Cham. https://doi.org/10.1007/978-3-032-18443-6_23
