Lucia Campitiello, Fabrizio Schiavo, Pio Alfredo Di Tore


In recent years, the significant progress of technologies based on AI has revolutionized the field of emotion recognition, opening new horizons in the interpretation and analysis of human expression. This progress promises the personalized educational applications that help children with autism recognize emotions by mimicking facial expressions associated with specific feelings. The project aims to develop a robot integrated with AI algorithms to foster socio-emotional skills in children with autism

Full Text:



Baron-Cohen, S. (2002). The extreme male brain theory of autism. Trends in Cognitive Sciences, 6(6), 248-254.

Barrett, L. F. (2017). How emotions are made: The secret life of the brain. Pan Macmillan.

Bower, G. H., & Cohen, P. R. (1982). Emotional influences in memory and thinking: Data and theory. Affect and Cognition, 1.

Damasio, A. R. (1994). Descartes’ error: Emotion, reason, and the human brain. Vintage Digital Edition (2008).

Ezquerra, A., Agen, F., Rodríguez-Arteche, I., & Ezquerra-Romano, I. (2022). Integrating artificial intelligence into research on emotions and behaviors in science education. Eurasia Journal of Mathematics, Science and Technology Education, 18(4).

Goodwin, M. S., Mazefsky, C. A., Ioannidis, S., Erdogmus, D., & Siegel, M. (2019). Predicting aggression to others in youth with autism using a wearable biosensor. Autism Research, 12(8), 1286-1296.

Juuti, K., & Lavonen, J. (2006). Design-based research in science education: One step towards methodology. Nordic Studies in Science Education, 2(2), 54-68.

Knight, W. (2013). Facial analysis software spots struggling students. MIT Technology Review.

Loderer, K., Pekrun, R., & Plass, J. L. (2019). Affective foundations of game-based learning. In J. L. Plass, E. Richard, R. E. Mayer, & B. D. Homer (Eds.), The handbook of game-based learning (pp. 111-151). MIT Press.

Lucangeli, D. (2019). Cinque lezioni leggere sull'emozione di apprendere. Edizioni Centro Studi Erickson.

Marcos-Merino, J. M. (2019). Análisis de las relaciones emociones-aprendizaje de maestros en formación inicial con una práctica activa de biología [Analysis of the emotions-learning relationships of teachers in initial training with an active practice of biology]. Revista Eureka sobre Enseñanza y Divulgación de las Ciencias [Eureka Magazine on Teaching and Dissemination of Sciences], 16(1), 1603.

Mejbri, N., Essalmi, F., Jemni, M., & Alyoubi, B. A. (2022). Trends in the use of affective computing in e-learning environments. Education and Information Technologies, 1-23.

Pekrun, R., Lichtenfeld, S., Marsh, H. W., Murayama, K., & Goetz, T. (2017). Achievement emotions and academic performance: Longitudinal models of reciprocal effects. Child Development, 88(5), 1653-1670.

Pennazio, V. (2019). Robotica e sviluppo delle abilità sociali nell’autismo. Una review critica. Mondo Digitale, 2.

Phelps, E. A. (2006). Emotion and cognition: Insights from studies of the human amygdala. Annual Review of Psychology, 57, 27–53.

Picard, R. W. (1995). Affective computing. MIT Media Laboratory Perceptual Computing Section Technical Report No. 321.

Putwain, D. W., Becker, S., Symes, W., & Pekrun, R. (2018). Reciprocal relations between students’ academic enjoyment, boredom, and achievement over time. Learning and Instruction, 54, 73-81.

Qualter, P., Gardner, K. J., & Whiteley, H. E. (2007). Emotional intelligence: Review of research and educational implications. Pastoral Care in Education, 25(1).

Richardson, S. (2020). Affective computing in the modern workplace. Business Information Review, 37(2), 78-85.

Robinson, P., & el Kaliouby, R. (2009). Computation of emotions in man and machines. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1535), 3441-3447.

Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition and Personality, 9(3), 185–211.

Sap, M., Card, D., Gabriel, S., et al. (2019). The risk of racial bias in hate speech detection. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florence, Italy, 28 July–2 August 2019, pp. 1668–1678.

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.

Sivasangari, A., Ajitha, P., Rajkumar, I., & Poonguzhali, S. (2019). Emotion recognition system for autism disordered people. Journal of Ambient Intelligence and Humanized Computing, 1-7.

Thubron, R. (2018). Chinese school using facial recognition to analyze students’ emotions: the system also monitors teachers. TechSpot.

Woolf, B., Burleson, W., Arroyo, I., Dragon, T., Cooper, D., & Picard, R. (2009). Affect-aware tutors: Recognising and responding to student affect. International Journal of Learning Technology, 4(3–4), 129–164.



  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Italian Journal of Health Education, Sports and Inclusive Didactics 
ISSN: 2532-3296