Analysing Artificial Neural Networks in High School Mathematics Education

Zusammenfassung

The rapid development of artificial intelligence (AI) and its integration into everyday life presents new challenges within the educational system. It is essential, that students possess a comprehensive understanding of the functionality of this technology to use the potential responsibly (Touretzky et al., 2022). The development of what is known as AI literacy (Long & Magerko, 2021) is therefore becoming the responsibility of the entire school system, rather than just computer science (Micheuz, 2020) or higher education. Mathematics, in particular, provides the tools to look deeper into the inner workings of AI models. Indeed, several AI methods, including support vector machines, decision trees and the k-nearest neighbour algorithm, offer a variety of connections to the content of school mathematics, including vector calculus, statistics and differential calculus (Schönbrodt et al., 2022; Biehler & Fleischer, 2021; Hazzan & Mike, 2022). In this regard, AI education represents an authentic and modern application of school mathematics.

Sarah Schönbrodt

Assistenzprofessorin @ Universität Salzburg

Forschung im Bereich Mathematikdidaktik und KI-Bildung