Generative AI and its application in general and special education in middle and high schools. What fruitful hybridizations?
Parole chiave:
IA; Education; Curriculum; School; TeacherAbstract
School is conceived as a place for learning knowledge and developing skills through curricula that address, on the one hand, administrative aspects and on the other, aspects that concern the individual who will be the protagonist of the educational process. These are not two separate, or worse, opposing, realities, but rather appear as complementary elements, as aspects that complement each other. This develops through a school that must increasingly become a laboratory of innovation. Therefore, teachers, as essential protagonists of instruction and education, must increasingly be: 1) capable of renewing curricula, planning teaching programs creatively and flexibly in light of each student’s talents, gaps, and educational needs, in order to bring out everyone’s potential.
Riferimenti bibliografici
Aversa R., Kolodziej J., Zhang Jun, Amato F., Fortino G. (2013). Algorithms And Architectures For Parallel Processing (13th International Conference, Ica3pp 2013, Vietri Sul Mare, Italy, December 18-20, 2013, Proceedings, Part II). Berlino: Springer;
Bolognesi F. (2024). Intelligenza artificiale. Come il Machine Learning e l’Ia Generativa possono trasformare le attività e generare vantaggi competitivi. EPC Editore
Chounta I.A., Bardone E., Raudsep A., Pedaste M., Exploring Teachers’ Perceptions of Artificial Intelligence as a Tool to Support Their Practice in Estonian K-12 Education, in «International Journal of Artificial Intelligence in Education», 32(3), 2022, pp. 725–755;
Cuomo S., Ranieri M., Biagini G., (2024). Scuola e Intelligenza Artificiale. Percorsi di alfabetizzazione critica. Roma: Carocci
Dewey J.(1958), Le fonti di una scienza dell’educazione. Firenze: La Nuova Italia Editrice;
Domènec Melé, in The Challenge of Humanistic Management (Journal of Business Ethics, Volume 44, Number 1, 2003
Gardner H. (2006). Multiple Intelligences: New Horizons in Theory and Practice, New York: Basic Books
Goleman D. (2011). Intelligenza emotiva. Milano: Rizzoli
Lévy P. (1999). L’ intelligenza collettiva. Per un’antropologia del cyberspazio. Milano: Feltrinelli
MIM. (2025). Linee guida per l’introduzione dell’Intelligenza Artificiale nelle Istituzioni scolastiche, Roma: Versione 1.0.
Minghetti M. (2013). L’intelligenza collaborativa. Verso la social organization. Milano: EGEA
Mulè P., (Eds.). (2017). La didattica per competenze. Presupposti epistemologici e ambientali di apprendimento. Roma: Pensa Multimedia;
Mulè P., Gulisano D. (2024) (Eds). L’insegnante tre innovazione didattica e processi inclusivi. Roma: Studium.
Ortega Y Gasset J. (2016). L’uomo e la gente. Sesto San Giovanni: Mimesis
Panciroli C., Rivoltella P.C. (2022). Pedagogia algoritmica. Per una riflessione educativa sull’Intelligenza Artificiale. Brescia: Morcelliana Scholè;
Pedró F., Subosa M., Rivas A., Valverde P. (2019). Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development. Paris: Unesco;
Porter M.E. (1980). Comptetitive strategy: techniques for analyzing industries and competitors. United Kingdom: Free Press.
Sternberg R. J. (1987). Teorie dell’intelligenza. Milano: Bompiani
##submission.downloads##
Pubblicato
Come citare
Fascicolo
Sezione
Licenza
Copyright (c) 2025 Paolina Mulè

Questo lavoro è fornito con la licenza Creative Commons Attribuzione - Non commerciale - Non opere derivate 4.0 Internazionale.