Logo PTI Logo FedCSIS

Position Papers of the 20th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 44

Enhancing Socio-Emotional Skills in Children with Autism through AI-Powered Serious Games: A Narrative Review

, , , ,

DOI: http://dx.doi.org/10.15439/2025F7538

Citation: Position Papers of the 20th Conference on Computer Science and Intelligence Systems, M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 44, pages 1521 ()

Full text

Abstract. This narrative review explores the integration of Artificial Intelligence (AI) and Serious Games (SGs) as a novel, interdisciplinary approach to fostering socio-emotional skills in children with Autism Spectrum Disorder (ASD). As ASD is characterized by persistent challenges in emotional understanding, social communication, and behavioral regulation, there is a growing need for interventions that are both effective and personalized. SGs provide structured, interactive environments where children can practice skills such as emotion recognition, joint attention, and empathy in a safe and motivating way. When augmented with AI, these games offer real-time feedback, dynamic personalization, and adaptive learning experiences tailored to individual cognitive and emotional profiles. This review synthesizes recent empirical evidence on AI-powered SGs targeting socio-emotional development in children with ASD. It examines the design strategies, targeted competencies, and evaluation methods used across current literature. The integration of SGs and AI is positioned as a promising and scalable tool to promote autonomy, emotional well-being, and social inclusion in neurodiverse children.

References

  1. American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. American Psychiatric Association, 2013. https://dx.doi.org/10.1176/appi.books.9780890425596.
  2. A. Bandura, «Social Cognitive Theory: An Agentic Perspective», Annu. Rev. Psychol., vol. 52, fasc. 1, pp. 1–26, feb. 2001, https://dx.doi.org/10.1146/annurev.psych.52.1.1.
  3. F. Xu et al., «The Use of Digital Interventions for Children and Adolescents with Autism Spectrum Disorder—A Meta-Analysis», J Autism Dev Disord, set. 2024, https://dx.doi.org/10.1007/s10803-024-06563-4.
  4. C. Eichenberg e M. Schott, «Serious Games for Psychotherapy: A Systematic Review», Games for Health Journal, vol. 6, fasc. 3, pp. 127–135, giu. 2017, https://dx.doi.org/10.1089/g4h.2016.0068.
  5. F. Petcusin, C. S. Spahiu, e L. Stanescu, «A machine learning approach for automatic testing», in Annals of Computer Science and Information Systems, PTI, ott. 2023, pp. 215–220. https://dx.doi.org/10.15439/2023f4426.
  6. S. D’Alfonso, «AI in mental health», Current Opinion in Psychology, vol. 36, pp. 112–117, dic. 2020, https://dx.doi.org/10.1016/j.copsyc.2020.04.005.
  7. S. Kewalramani, K.-A. Allen, E. Leif, e A. Ng, «A Scoping Review of the Use of Robotics Technologies for Supporting Social-Emotional Learning in Children with Autism», J Autism Dev Disord, vol. 54, fasc. 12, pp. 4481–4495, dic. 2024, https://dx.doi.org/10.1007/s10803-023-06193-2.
  8. F. Stasolla, E. Curcio, A. Passaro, M. Di Gioia, A. Zullo, e E. Martini, «Exploring the Combination of Serious Games, Social Interactions, and Virtual Reality in Adolescents with ASD: A Scoping Review», Technologies, vol. 13, fasc. 2, p. 76, feb. 2025, https://dx.doi.org/10.3390/technologies13020076.
  9. F. Stasolla, E. Curcio, A. Zullo, A. Passaro, e M. D. Gioia, «Integrating Artificial Intelligence-based programs into Autism Therapy: Innovations for Personalized Rehabilitation», presentato al 19th Conference on Computer Science and Intelligence Systems (FedCSIS), nov. 2024, pp. 169–176. https://dx.doi.org/10.15439/2024F6229.
  10. A. Coronato e M. Naeem, «A Reinforcement Learning Based Intelligent System for the Healthcare Treatment Assistance of Patients with Disabilities», in Pervasive Systems, Algorithms and Networks, vol. 1080, C. Esposito, J. Hong, e K.-K. R. Choo, A c. di, in Communications in Computer and Information Science, vol. 1080. , Cham: Springer International Publishing, 2019, pp. 15–28. https://dx.doi.org/10.1007/978-3-030-30143-9_2.
  11. H. M. Zakari, M. Ma, e D. Simmons, «A Review of Serious Games for Children with Autism Spectrum Disorders (ASD)», in Serious Games Development and Applications, vol. 8778, M. Ma, M. F. Oliveira, e J. Baalsrud Hauge, A c. di, in Lecture Notes in Computer Science, vol. 8778. , Cham: Springer International Publishing, 2014, pp. 93–106. https://dx.doi.org/10.1007/978-3-319-11623-5_9.
  12. K. Martinez, M. I. Menéndez-Menéndez, e A. Bustillo, «Awareness, Prevention, Detection, and Therapy Applications for Depression and Anxiety in Serious Games for Children and Adolescents: Systematic Review», JMIR Serious Games, vol. 9, fasc. 4, p. e30482, dic. 2021, https://dx.doi.org/10.2196/30482.
  13. J. Wolstencroft, L. Robinson, R. Srinivasan, E. Kerry, W. Mandy, e D. Skuse, «A Systematic Review of Group Social Skills Interventions, and Meta-analysis of Outcomes, for Children with High Functioning ASD», J Autism Dev Disord, vol. 48, fasc. 7, pp. 2293–2307, lug. 2018, https://dx.doi.org/10.1007/s10803-018-3485-1.
  14. E. Ferrari, «Artificial Intelligence for Autism Spectrum Disorders», in Artificial Intelligence in Medicine, N. Lidströmer e H. Ashrafian, A c. di, Cham: Springer International Publishing, 2021, pp. 1–15. https://dx.doi.org/10.1007/978-3-030-58080-3_249-1.
  15. S. S. Sethi e K. Jain, «AI technologies for social emotional learning: recent research and future directions», JRIT, vol. 17, fasc. 2, pp. 213–225, ago. 2024, https://dx.doi.org/10.1108/JRIT-03-2024-0073.
  16. M. Wang, B. Muthu, e C. B. Sivaparthipan, «Smart assistance to dyslexia students using artificial intelligence based augmentative alternative communication», Int J Speech Technol, vol. 25, fasc. 2, pp. 343–353, giu. 2022, https://dx.doi.org/10.1007/s10772-021-09921-0.
  17. S. Poria, N. Majumder, R. Mihalcea, e E. Hovy, «Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances», IEEE Access, vol. 7, pp. 100943–100953, 2019, https://dx.doi.org/10.1109/ACCESS.2019.2929050.
  18. M. Mengi e D. Malhotra, «Artificial Intelligence Based Techniques for the Detection of Socio-Behavioral Disorders: A Systematic Review», Arch Computat Methods Eng, vol. 29, fasc. 5, pp. 2811–2855, ago. 2022, https://dx.doi.org/10.1007/s11831-021-09682-8.
  19. N. Wankhede et al., «Leveraging AI for the diagnosis and treatment of autism spectrum disorder: Current trends and future prospects», Asian Journal of Psychiatry, vol. 101, p. 104241, nov. 2024, https://dx.doi.org/10.1016/j.ajp.2024.104241.
  20. A. Hassan, N. Pinkwart, e M. Shafi, «Zirkus Empathico 2.0: a multiplayer serious mobile game for children with autism spectrum disorder (ASD), with a focus on enhancing social and emotional development», Multimed Tools Appl, apr. 2025, https://dx.doi.org/10.1007/s11042-025-20826-x.
  21. H. K. H. A. El-Sattar, «EMOCASH: An Intelligent Virtual-Agent Based Multiplayer Online Serious Game for Promoting Money and Emotion Recognition Skills in Egyptian Children with Autism», IJACSA, vol. 14, fasc. 4, 2023, https://dx.doi.org/10.14569/IJACSA.2023.0140414.
  22. M. Elhaddadi et al., «SERIOUS GAMES TO TEACH EMOTION RECOGNITION TO CHILDREN WITH AUTISM SPECTRUM DISORDERS (ASD)», Acta Neuropsychologica, vol. 19, fasc. 1, pp. 81–92, gen. 2021, https://dx.doi.org/10.5604/01.3001.0014.7569.
  23. Y.-L. Chien et al., «Game-Based Social Interaction Platform for Cognitive Assessment of Autism Using Eye Tracking», IEEE Trans. Neural Syst. Rehabil. Eng., vol. 31, pp. 749–758, 2023, https://dx.doi.org/10.1109/TNSRE.2022.3232369.
  24. S. Baldassarri, L. Passerino, S. Ramis, I. Riquelme, e F. J. Perales, «Toward emotional interactive videogames for children with autism spectrum disorder», Univ Access Inf Soc, vol. 20, fasc. 2, pp. 239–254, giu. 2021, https://dx.doi.org/10.1007/s10209-020-00725-8.
  25. J. Löytömäki, P. Ohtonen, e K. Huttunen, «Serious game the Emotion Detectives helps to improve social–emotional skills of children with neurodevelopmental disorders», Brit J Educational Tech, vol. 55, fasc. 3, pp. 1126–1144, mag. 2024, https://dx.doi.org/10.1111/bjet.13420.
  26. J. M. Garcia-Garcia, V. M. R. Penichet, M. D. Lozano, e A. Fernando, «Using emotion recognition technologies to teach children with autism spectrum disorder how to identify and express emotions», Univ Access Inf Soc, vol. 21, fasc. 4, pp. 809–825, nov. 2022, https://dx.doi.org/10.1007/s10209-021-00818-y.
  27. G. Quirantes-Gutierrez, Á. F. Estévez, G. Artés Ordoño, e G. López-Crespo, «Design of an Emotional Facial Recognition Task in a 3D Environment», Computers, vol. 14, fasc. 4, p. 153, apr. 2025, https://dx.doi.org/10.3390/computers14040153.
  28. J. S. Y. Tang, M. Falkmer, N. T. M. Chen, S. Bӧlte, e S. Girdler, «Designing a Serious Game for Youth with ASD: Perspectives from End-Users and Professionals», J Autism Dev Disord, vol. 49, fasc. 3, pp. 978–995, mar. 2019, https://dx.doi.org/10.1007/s10803-018-3801-9.
  29. S. S. Joudar et al., «Artificial intelligence-based approaches for improving the diagnosis, triage, and prioritization of autism spectrum disorder: a systematic review of current trends and open issues», Artif Intell Rev, vol. 56, fasc. S1, pp. 53–117, ott. 2023, https://dx.doi.org/10.1007/s10462-023-10536-x.
  30. K. K. Fitzpatrick, A. Darcy, e M. Vierhile, «Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial», JMIR Ment Health, vol. 4, fasc. 2, p. e19, giu. 2017, https://dx.doi.org/10.2196/mental.7785.
  31. M. Saha, S. Lindsay, D. Varghese, T. Bartindale, e P. Olivier, «Benefits of Community Voice: A Framework for Understanding Inclusion of Community Voice in HCI4D», Proc. ACM Hum.-Comput. Interact., vol. 7, fasc. CSCW2, pp. 1–26, set. 2023, https://dx.doi.org/10.1145/3610174.
  32. T. Liu, J. Huang, T. Liao, R. Pu, S. Liu, e Y. Peng, «A Hybrid Deep Learning Model for Predicting Molecular Subtypes of Human Breast Cancer Using Multimodal Data», IRBM, vol. 43, fasc. 1, pp. 62–74, feb. 2022, https://dx.doi.org/10.1016/j.irbm.2020.12.002.
  33. P. Zemliansky e D. Wilcox, A c. di, Design and Implementation of Educational Games: Theoretical and Practical Perspectives. IGI Global, 2010. https://dx.doi.org/10.4018/978-1-61520-781-7.
  34. S. T. H. Rizvi, N. Kanwal, M. Naeem, A. Cuzzocrea, e A. Coronato, «Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series Prediction», 2025, arXiv. https://dx.doi.org/10.48550/ARXIV.2501.01087.
  35. J. Pérez, M. Castro, e G. López, «Serious Games and AI: Challenges and Opportunities for Computational Social Science», IEEE Access, vol. 11, pp. 62051–62061, 2023, https://dx.doi.org/10.1109/ACCESS.2023.3286695.
  36. C. Kasari, S. Shire, W. Shih, e D. Almirall, «Getting SMART About Social Skills Interventions for Students With ASD in Inclusive Classrooms», Exceptional Children, vol. 88, fasc. 1, pp. 26–44, ott. 2021, https://dx.doi.org/10.1177/00144029211007148.
  37. M. Fiorino, M. Naeem, M. Ciampi, e A. Coronato, «Defining a Metric-Driven Approach for Learning Hazardous Situations», Technologies, vol. 12, fasc. 7, p. 103, lug. 2024, https://dx.doi.org/10.3390/technologies12070103.
  38. F. Abomelha e P. Newbury, «A VARK learning style-based Recommendation system for Adaptive E-learning», in Annals of Computer Science and Information Systems, PTI, nov. 2024, pp. 1–8. https://dx.doi.org/10.15439/2024f5253.
  39. W. Westera et al., «Artificial intelligence moving serious gaming: Presenting reusable game AI components», Educ Inf Technol, vol. 25, fasc. 1, pp. 351–380, gen. 2020, https://dx.doi.org/10.1007/s10639-019-09968-2.
  40. S.-J. Eun, E. J. Kim, e J. Kim, «Artificial intelligence-based personalized serious game for enhancing the physical and cognitive abilities of the elderly», Future Generation Computer Systems, vol. 141, pp. 713–722, apr. 2023, https://dx.doi.org/10.1016/j.future.2022.12.017.
  41. E. Smith, Y. Wang, e E. Matson, «Psychological Needs as Credible Song Signals: Testing Large Language Models to Annotate Lyrics», in Annals of Computer Science and Information Systems, PTI, nov. 2024, pp. 159–168. https://dx.doi.org/10.15439/2024f7168.
  42. S. Rossi, M. Rossi, R. R. Mukkamala, J. B. Thatcher, e Y. K. Dwivedi, «Augmenting research methods with foundation models and generative AI», International Journal of Information Management, vol. 77, p. 102749, ago. 2024, https://dx.doi.org/10.1016/j.ijinfomgt.2023.102749.