Rinnovare l’educazione nelle scuole rurali e piccole: Il ruolo dell’AI nello sviluppo professionale degli insegnanti
Barra laterale dell'articolo
Pubblicato:
Aug 1, 2024
Parole chiave:
AIEd, Intelligenza Artificiale, Scuole Rurali, Scuole di Piccole Dimensioni, Sviluppo Professionale degli Insegnanti
Contenuto principale dell'articolo
Abstract
L’articolo esplora la connessione tra intelligenza artificiale (AI) e sviluppo professionale degli insegnanti, concentrandosi sul contesto delle scuole di piccole dimensioni e rurali. A seguito di una scoping review condotta dal gruppo di ricerca, l’attenzione è posta sull’analisi di tre studi, afferenti a tre sottotemi del topic “AI e sviluppo professionale dei docenti” emersi dalla mappatura realizzata: l’uso di ambienti intelligenti per la formazione degli insegnanti, la percezione degli insegnanti sull’uso dell’AI nella loro pratica, lo sviluppo di agenti intelligenti per supportare l’insegnamento. La ricerca enfatizza l’importanza della formazione degli insegnanti per affrontare le sfide poste dall’AI per colmare il divario tra scuole urbane e rurali e apre a futuri scenari che verranno esplorati attraverso interviste con esperti nazionali e internazionali e uno Delphi Study al fine di identificare opportunità per le scuole di piccole dimensioni e sviluppare linee guida per raggiungere una convergenza sui possibili interventi nel contesto educativo non standard.
Dettagli dell'articolo
Sezione
Articoli - Numero speciale
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Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616-630.
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Di Tore, P. A., Mangione, G. R. J., Di Tore, S., & Aiello, P. (2013). Human machine interaction, embodied cognition and phenomenology: the body in digital storytelling. Learning & Teaching with Media & Technology, 1, 448-459.
Duncan, H. E., & Stock M. J. (2010). Mentoring and Coaching Rural School Leaders: What Do They Need? Mentoring and Tutoring: Partnership in Learning, 18(3), 293-311.
Edwards, B. I., & Cheok, A. D. (2018). Why not robot teachers: Artificial intelligence for addressing teacher shortage. Applied Artificial Intelligence, 32(4), 345–360.
EU (2023). Teachers’ competences. Briefing report No. 1 European Digital Education Hub’s squad on artificial intelligence in education (in press).
Fargas-Malet, M., & Bagley, C. (2022). Is Small Beautiful? A scoping review of 21st-century research on small rural schools in Europe. European Educational Research Journal, 21(5), 822-844.
Ferraro, F. V., Ambra, F. I., Aruta L., & Iavarone, M. L. (2020). Distance Learning in the Covid-19 Era: Perceptions in Southern Italy. Education Sciences, 10(12), 355.
Francom, G. M. (2016). Barriers to technology use in large and small school districts. Journal of Information Technology Education. Research, 15, 577.
Füller, C., & Spiewak, M. (2020). Digitale Hausaufgabe. Die Zeit, 37, 38.
Fuster, M., & Burns, T. (2020). Back to the future of education: Four OECD scenarios for schooling. OECD iLibrary. https://www.oecd.org/education/back-to-the-future-s-of-education-178ef527-en.htm
Goodpaster, K. P., Adedokun, O. A., & Weaver, G. C. (2012). Teachers’ perceptions of rural STEM Teaching: Implications for Rural Teacher Retention. The Rural Educator, 33(3).
Green, R. A. (2014). The Delphi technique in educational research. Sage Open, 4(2).
Handal, B., Watson, K., Petocz, P., & Maher, M. (2018). Choosing to teach in rural and remote schools: The zone of free movement. Education Research and Perspectives, 45, 1-32.
Hannum, W. H., Irvin, M. J., Banks, J. B., & Farmer T. W. (2009). Distance education use in rural schools. Journal of Research in Rural Education, 24(3), 1.
Hargreaves, L. M. (2009). Respect and Responsibility: Review of Research on Small Rural Schools in England. International Journal of Educational Research, 48(2), 117-128.
Hawkes, M., Halverson, P., & Brockmueller, B. (2002). Technology facilitation in the rural school: An Analysis of Options. Journal of Research in Rural Education, 17(3), 162-170.
Heffernan, N.T., & Heffernan, C .L. (2014). The assistments ecosystem: building a platform that brings scientists and teachers together for minimally invasive research on human learning and teaching. International Journal of Artificial Intelligence in Education, 24(4), 470–497.
Hinojo-Lucena, F. J., Aznar-Díaz, I., Cáceres-Reche, M. P., & Romero-Rodríguez, J. M. (2019). Artificial intelligence in higher education: A bibliometric study on its impact in the scientific literature. Education Sciences, 9(1), 51.
Holstein, K., McLaren, B. M., & Aleven, V. (2017). Intelligent Tutors as Teachers’ Aides: Exploring Teacher Needs for Real-time Analytics in Blended Classrooms. Proceedings of the seventh international learning analytics & knowledge conference, 257-266.
Howley, A., Wood, L., & Hough, B. (2011). Rural Elementary School Teachers’ Technology Integration. Journal of Research in Rural Education, 29(9), 1-18.
Ingersoll, M., Hirschkorn, M., Landine, J., & Sears, A. (2018). Recruiting international educators in a global teacher shortage: Research for practice. The International Schools Journal, 37(2), 92–102.
Lucisano, P. (2020). Fare ricerca con gli insegnanti. I primi risultati dell’indagine nazionale SIRD. Per un confronto sulle modalità didattica a distanza adottate nelle scuole italiane nel periodo di emergenza COVID-19. Lifelong Lifewide Learning, 17(36), 3-25.
Jian, L. (2020). Improving teacher development in rural China: A Case of “Rural Teacher Support Plan”. Beijing International Review of Education, 2(2), 301-306.
Jiang, C. (2021). Technical framework and model of artificial intelligence for boosting the revitalization of rural education. 2021 2nd International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT), 107–110.
Kaden, U. (2020). COVID-19 School closure-related changes to the professional life of a K–12 teacher. Education Sciences, 10(6), 165.
Kale, U., Goh, D. (2014). Teaching style, ICT experience and teachers’ attitudes toward teaching with Web 2.0. Education and Information Technologies, 19(1), 41-60.
Kormos, E. M. (2018). The Unseen Digital Divide: Urban, Suburban, and Rural Teacher Use and Perceptions of Web-Based Classroom Technologies. Computers in the Schools, 35(1), 19-31.
Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M. D., Păun, D., & Mihoreanu, L. (2021). Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions. Sustainability, 13(18), 10424.
Kusmawan, U. (2023). Redefining teacher training: The promise of ai-supported teaching practices. Journal of Advances in Education and Philosophy, 332–335. https://doi.org/10.36348/jaep.2023.v07i09.001
Laferrière, T., Hamel, C., Allaire, S., Turcotte, S., Breuleux, A., Beaudoin, J., & Gaudreault Perron, J. (2011). L’ecole eloignee en reseau, un modele. Rapport-synthèse, CEFRIO.
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