Machine Learning i gymnasiet
IND's studenterserie nr. 111, 2023. Bachelorprojekt - Matematik
Metine Rahbek Tarp & Nicolaj Pape Frantzen.
Vejleder: Britta Eyrich Jessen
Abstract
This project builds upon the ongoing discussion regarding the implementation of machine learning (ML) into mathematics education at the high school level. Specifically, this project aims to explore this implementation through the research methodology known as didactic engineering. Based on a preliminary analysis that provided an overview of prior research on ML education at high school level, inquiry-based education and hands-on work are highlighted as being positive. As a result, the following research question emerged, about whether TDS can serve as a tool for designing meaningful mathematical inquiry-based education in ML, such that the students’ relational understanding is promoted rather than the instrumental understanding. Drawing on materials from Dataekspeditioner (Machholm & Jørgensen, n.d.), three lessons are designed with the aim of contributing to answering the research question. The lessons were tested in a Danish high school class leading to the conclusion that TDS is well-suited for designing meaningful mathematical inquiry-based education in ML, particularly in enhancing students' relational understanding of concrete ML models. However, it is less effective in teaching students’ fundamental skills in handling ML programs. This potential can contribute to further advancements in research related to the implementation of ML in high school mathematics education.