AI-mediated socio-emotional support for children with autism: a human-supervised framework
Parole chiave:
Artificial Intelligence; Inclusive Education; Autism Spectrum Disorder; Socio-Emotional Learning; Human-in-the-Loop SystemsAbstract
Artificial Intelligence (AI) is progressively reshaping the field of inclusive education by offering new tools to support structured and personalized learning processes for students with autism spectrum disorder (ASD). This contribution introduces EMORI, a conceptual and architectural framework for the use of artificial intelligence as a mediated educational support in socio-emotional interventions for children with autism. The project is implemented through EmoRobot, an embodied robotic agent, and supported by Socrate, an AI orchestration platform designed to manage conversational logic through pedagogically guided retrieval-augmented generation techniques. The system is grounded in the socio-emotional intervention program proposed by Patricia Howlin and adopts a state-based conversational model that structures interaction into progressive and predictable stages. Within each state, the language model operates under constrained generative conditions, providing adaptive prompts and feedback while preserving instructional control. A central feature of the framework is the adoption of a human-in-the-loop approach, ensuring continuous pedagogical supervision. The contribution of this work lies in the definition of a theoretical and methodological model for the pedagogically sustainable integration of artificial intelligence into socio-emotional interventions for children with autism.
Riferimenti bibliografici
Amershi, S., Cakmak, M., Knox, W. B., & Kulesza, T. (2014). Power to the people: The role of humans in interactive machine learning. AI magazine, 35(4), 105-120.
Bandura, A., & Walters, R. H. (1977). Social learning theory (Vol. 1, pp. 141-154). Englewood Cliffs, NJ: Prentice hall. Baron-Cohen, S. (1995). Mindblindness: An essay on autism and theory of mind. Cambridge, MA: MIT Press.
Baron-Cohen, S., Leslie, A. M., & Frith, U. (1985). Does the autistic child have a “theory of mind”?. Cognition, 21(1), 37-46. https://doi.org/10.1016/0010-0277(85)90022-8
Cabibihan, J. J., Javed, H., Ang Jr, M., & Aljunied, S. M. (2013). Why robots? A survey on the roles and benefits of social robots in the therapy of children with autism. International journal of social robotics, 5(4), 593-618.. https://doi.org/10.1007/s12369-013-0202-2
Floridi, L. (2022). Etica dell’intelligenza artificiale: Sviluppi, opportunità, sfide. Raffaello Cortina Editore.
Goleman, D. (2011). Intelligenza emotiva. Che cos' è e perché può renderci felici. Bur.
Holzinger, A. (2016). Machine learning for health informatics. In Machine Learning for Health Informatics: State-of-the-Art and Future Challenges (pp. 1-24). Cham: Springer International Publishing.
Howlin, P., Baron-Cohen, S., & Hadwin, J. (1999). Teoria della mente e autismo-Insegnare a comprendere gli stati psichici dell’altro. Edizioni Erickson.
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., ... & Kiela, D. (2020). Retrieval-augmented generation for knowledge-intensive NLP tasks. Advances in neural information processing systems, 33, 9459-9474.
Picard, R. W. (1997). Affective computing. Cambridge, MA: MIT Press.
Picard, R. W. (2003). Affective computing: challenges. International journal of human-computer studies, 59(1-2), 55-64.https://doi.org/10.1016/S1071-5819(03)00052-1
Premack, D., & Woodruff, G. (1978). Does the chimpanzee have a theory of mind? Behavioral and Brain Sciences, 1(4), 515– 526. https://doi.org/10.1017/S0140525X00076512
Rudovic, O., Lee, J., Mascarell-Maricic, L., Schuller, B., & Picard, R. W. (2018). Measuring engagement in ro-bot-assisted autism therapy: A cross-cultural study. Frontiers in Robotics and AI, 5, 36. https://doi.org/10.3389/frobt.2018.00036
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161–1178. https://doi.org/10.1037/h0077714
Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition and Personality, 9(3), 185–211. https://doi.org/10.2190/DUGG-P24E-52WK-6CDG
Scasellati, B., Admoni, H., & Mataric, M. (2018). Robots for use in autism research. Annual Review of Biomedical Engineering, 19, 275–299. https://doi.org/10.1146/annurev-bioeng-071811-150036
Scherer, K. R. (2001). Appraisal Considered as a Process of Multilevel Sequential Checking. Ιn K. R. Scherer, A. Schorr, & T. Johnstone (Eds.), Appraisal Processes in Emotion: Theory, Methods, Research (pp. 92-120). Oxford: Oxford University Press.
Schiavo, F., Campitiello, L., Todino, M. D., & Di Tore, P. A. (2024). Educational Robots, Emotion Recognition and ASD: New Horizon in Special Education. Education Sciences, 14(3), 258. https://doi.org/10.3390/educsci14030258
Vygotsky, L. S. (1978). Mind in society Harvard university press. Cambridge, MA.
Wang, K., Sang, G.-Y., Huang, L.-Z., Li, S.-H., & Guo, J.-W. (2023). The Effectiveness of Educational Robots in Improving Learning Outcomes: A Meta-Analysis. Sustainability, 15(5), 4637. https://doi.org/10.3390/su15054637
Wong, C., Odom, S. L., Hume, K. A., Cox, A. W., Fettig, A., Kucharczyk, S., ... & Schultz, T. R. (2015). Evi-dence-based practices for children, youth, and young adults with autism spectrum disorder: A compre-hensive review. Journal of autism and developmental disorders, 45(7), 1951-1966.
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of child psychology and psychiatry, 17(2), 89-100.
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Copyright (c) 2026 Lucia Campitiello, Anna Rescigno, Emanuela Zappalà, Amelia Lecce, Stefano Di Tore
Questo lavoro è fornito con la licenza Creative Commons Attribuzione - Non commerciale - Non opere derivate 4.0 Internazionale.
