Data Science and Machine Learning in mathematics education: High-school students working on the Netflix Prize


One goal of contemporary mathematical modeling classes in schools should be to include up-to-date problems or interesting, new technologies from the everyday life of students-especially if these allow the didactical reduction to elementary (school-)mathematical knowledge and thus have the potential to enrich mathematics education. Data Science and Machine Learning is applied in numerous areas of science and technology and used in many applications in our everyday life. Using movie recommender systems and the so-called Netflix Prize as an example, this paper discusses how mathematics education can be enriched by modeling real-world, student-centered problems from the field of Machine Learning in school. For this purpose, we describe tested digital learning material from guided modeling projects and share our experience with giving the problem of developing a recommender system as a completely open problem to upper secondary students.

In: Twelfth Congress of the European Society for Research in Mathematics Education (CERME12)
Sarah Schönbrodt
Sarah Schönbrodt
Assistenzprofessorin @ Universität Salzburg

Forschung im Bereich Mathematikdidaktik und KI-Bildung