How engineering students argue in an introductory course in data science

Abstract

Model building and validation are at the core of machine learning and a subfield of data science. In this paper, the Toulmin model is used to structure students’ approaches and analyze students' argumentation when building a model. A qualitative analysis of passages from the underlying design experiments with undergraduate engineering students shows different approaches and visual, contextual and mathematical or statistical elements that students use within their argumentation.