Balancing Rights and Responsibilities in SMART Education: A Legal-Operational Matrix for the Professor, Institution, and State
Abstract
This article presents a legal-operational matrix for SMART Education, showing how the roles of professors, institutions, and the state are changing as AI becomes part of teaching. Using examples from different countries, it explains that both laws and daily practices need to fit local needs. The matrix looks at three groups: professors, who have rights and teaching duties; institutions, which set and enforce rules; and the state, which protects the public interest by setting standards. For example, if a professor wants to use a new AI tool for grading, the institution checks for legal and ethical issues, and the state provides the main data protection rules. Faculty can use the matrix in daily teaching by checking its guidelines to make sure their methods follow legal and institutional standards. This means being open with students about AI use, adjusting tools for different learning needs, and staying in regular contact with institutional leaders. The goal is to balance autonomy, accountability, and transparency.
References
Al-Adwan, A. S., Albelbisi, N. A., Al-Makadmeh, N. M., Hujran, O., & Al-Adwan, A. S. (2021). Investigating the drivers and barriers of hybrid e-learning adoption in higher education during the COVID-19 pandemic: The case of private universities in Jordan. Sustainability, 13(16), 9453. https://doi.org/10.3390/su13169453
Alaswad, Sara; Kalganova, Tatiana; Awad, Wasan (2025). Trustworthiness of Legal Considerations for the Use of LLMs in Education. Unknown Journal.
Arranz-García, O., Romero García, M. del C., & Alonso-Secades, V. (2025). Perceptions, strategies, and challenges of teachers in the integration of artificial intelligence in primary education: A systematic review. Journal of Information Technology Education: Research, 24, Article 6. https://doi.org/10.28945/5458
Bucea-Manea-Țoniș, R., Martins, O. M. D., & Bucea-Manea-Țoniș, R. (2021). Blockchain technology enhances sustainable higher education. Sustainability, 13(22), 12347. https://doi.org/10.3390/su132212347
Daskalaki, E., Psaroudaki, K., Fragopoulou, P. (2024). Navigating the Future of Education: Educators' Insights on AI Integration and Challenges in Greece, Hungary, Latvia, Ireland and Armenia. Unknown Journal.
European Union. (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council laying down harmonised rules on Artificial Intelligence (AI Act). EUR-Lex. https://eur-lex.europa.eu/eli/reg/2024/1689/oj
Fan, L., Deng, K., & Liu, F. (2025). Educational impacts of generative AI on learning and performance of engineering students in China. Scientific Reports, 15, Article 6930. https://www.nature.com/articles/s41598-025-06930-w
Governing intelligence: Singapore’s evolving AI governance framework. (2024). Cambridge Forum on AI: Law and Governance, 1.
Halkiopoulos, C., Sakkopoulos, E., Bortolas, A., & Ntalaperas, D. (2024). A framework for achieving smart education using the Education 5.0 paradigm. Electronics, 13(6), 1156. https://doi.org/10.3390/electronics13061156
Hanandeh, A., Qudah, M., Mansour, A., Al-Qudah, S., Abualfalayeh, G., Kilani, Q., & Khasawneh, M. A. S. (2024). The achievement of digital leadership sustainability and business performance through the implementation of business intelligence, artificial intelligence, and quality learning in private universities in Jordan. Uncertain Supply Chain Management, 12(4), 2581–2586. https://doi.org/10.5267/j.uscm.2024.5.012
Herrera, Pablo; Huepe, Mariana; Trucco, Daniela (2025). Education and the development of digital competences in Latin America and the Caribbean. Economic Commission for Latin America and the Caribbean (ECLAC).
Hernández-León, N., & Rodríguez-Conde, M. J. (2024). Inteligencia Artificial aplicada a la educación y la evaluación educativa en la universidad: Introducción de sistemas de tutoría inteligentes, sistemas de reconocimiento y otras tendencias futuras. Revista de Educación a Distancia. https://doi.org/10.6018/red.594651
Kuklin, O., Ivanova, I., & Borovyk, T. E. (2024). Modeling the integration of AI into the educational environment. Information Technologies and Learning Tools, 99(3). https://doi.org/10.33407/itlt.v99i3.6512
Kuzmin, N. N., Glazunova, I. N., & Chistyakova, N. A. (2024). Introduction of AI into education: Pros and cons. Management of Education (Upravlenie obrazovaniem). https://emreview.ru/jour/article/view/1308?locale=en_US
Lee, C.-C., & Low, M. Y. H. (2024). Using GenAI in education: The case for critical thinking. Frontiers in Artificial Intelligence, 7, 1452131. https://doi.org/10.3389/frai.2024.1452131
Mazutti, J., Brandli, L. L., Salvia, A. L., Gomes, B. M. F., Damke, L. I., da Rocha, V. T., & Rabello, R. S. (2020). Smart and learning campus as living lab to foster education for sustainable development: An experience with air quality monitoring. International Journal of Sustainability in Higher Education, 21(7), 1311–1330. https://eric.ed.gov/?id=EJ1277430
Merant, N., Paniagua Urbáez, Y. L., Fragoso García, P. P., & Troncoso, D. (2025). La inteligencia artificial en la enseñanza/aprendizaje del idioma inglés: Una revisión sistemática. AULA Revista de Humanidades y Ciencias Sociales, 10(36), 102–119. https://revistas.unphu.edu.do/index.php/aula/article/view/649
Montiel-Ruiz, F. J., & López Ruiz, M. (2023). Inteligencia artificial como recurso docente en un colegio rural agrupado. Revista Interuniversitaria de Investigación en Tecnología Educativa, 15, 28–40. https://doi.org/10.6018/riite.592031
Nezhyva, L., Palamar, S. P., Semenii, N. O., & Semerikov, S. O. (2025). AI tools for sustainable primary teacher education: Literary-artistic content generation. In International Workshop on Augmented Reality in Education (CEUR-WS, Vol. 3719). http://ceur-ws.org/Vol-3719/paper17.pdf
Peñafiel Arteaga, E. E., Pacho Sinchi, G. F., Yungán Ruiz, B. H., Estrada Valarezo, S. N., Reyes Suárez, I. V., & Mora, C. (2025). La inteligencia artificial en la educación: Desafíos y oportunidades. South Florida Journal of Development. https://southfloridapublishing.com/ojs/index.php/jdev/article/view/2793
San Martín Torres, D. M., Flores Mayorga, C. A., Granda Morocho, O. A., & Suconota Pintado, A. L. (2023). Aplicación de la inteligencia artificial en la educación para el desarrollo sostenible: Un análisis sistemático. Magazine de las Ciencias: Revista de Investigación e Innovación. https://revistas.utb.edu.ec/index.php/magazine/article/view/2194
Topkaya, Y., Doğan, Y., Batdı, V., & Aydın, S. (2025). Artificial Intelligence Applications in Primary Education: A Quantitatively Complemented Mixed-Meta-Method Study. Sustainability, 17(7), 3015. https://doi.org/10.3390/su17073015
UNESCO. (2023). Guidance for generative AI in education and research. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Xie, Qin; Li, Ming; Enkhtur, Ariunaa (2024). Exploring Generative AI Policies in Higher Education: A Comparative Perspective from China, Japan, Mongolia, and the USA. Unknown Journal.
Xiao, S., Wu, X., Chen, X., & Shen, Z. (2025). Exploring the potential of GenAI to enhance teaching effectiveness: A systematic review and meta-analysis. Sustainability, 17(12), 5046.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Didactica Danubiensis
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
