Artificial Intelligence (AI) is emerging as a transformative technology for education, promising novel perspectives for personalized, inclusive, and effective pedagogy. Leveraging AI’s capacity for data management and personalized learning pathways, this study focuses on teaching mathematics in primary school. Despite being crucial for the development of logical thinking, this discipline is often hampered by the abstract nature of foundational concepts (point, line, number) and the limitations of static traditional methods. AI presents itself as an innovative solution to overcome these challenges, utilizing advanced models like Deep Neural Networks and Generative Adversarial Networks (GANs) to create dynamic and interactive visualizations. Such tools make mathematical concepts more accessible, acting as a bridge between abstraction and students’ cognitive processes. AI can monitor progress in real-time, providing personalized support that enhances teaching effectiveness and self-esteem. Crucially, it also holds immense potential for supporting students with disabilities, ensuring equitable and integrated access to content. To evaluate this efficacy, a quasi-experimental pilot study will be conducted in a third-grade primary class in Puglia, Italy, with a sample of approximately 20 students, including pupils with Special Educational Needs. The experiment is structured in three phases: teacher training, didactic intervention using AI tools (progressive visualizations and interactive environments), and evaluation via pre- and post-intervention tests.

Beyond the traditional classroom: innovation and inclusion in math teaching with AI

Domenico Santoro;
2025-01-01

Abstract

Artificial Intelligence (AI) is emerging as a transformative technology for education, promising novel perspectives for personalized, inclusive, and effective pedagogy. Leveraging AI’s capacity for data management and personalized learning pathways, this study focuses on teaching mathematics in primary school. Despite being crucial for the development of logical thinking, this discipline is often hampered by the abstract nature of foundational concepts (point, line, number) and the limitations of static traditional methods. AI presents itself as an innovative solution to overcome these challenges, utilizing advanced models like Deep Neural Networks and Generative Adversarial Networks (GANs) to create dynamic and interactive visualizations. Such tools make mathematical concepts more accessible, acting as a bridge between abstraction and students’ cognitive processes. AI can monitor progress in real-time, providing personalized support that enhances teaching effectiveness and self-esteem. Crucially, it also holds immense potential for supporting students with disabilities, ensuring equitable and integrated access to content. To evaluate this efficacy, a quasi-experimental pilot study will be conducted in a third-grade primary class in Puglia, Italy, with a sample of approximately 20 students, including pupils with Special Educational Needs. The experiment is structured in three phases: teacher training, didactic intervention using AI tools (progressive visualizations and interactive environments), and evaluation via pre- and post-intervention tests.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12606/37345
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
social impact