Preservice teachers’ exploration of multivariate data based on personal interestsOpen Access

Podworny, Susanne; Birk, Lisa; Kazak, Sibel; Leavy, Aisling

Forschungsartikel in Sammelband (Konferenz) | Peer reviewed

Zusammenfassung

The DataSETUP project addresses the critical need for data science competencies in teacher education by developing short, modular courses for preservice teachers. Based on the DataSETUP framework, these modules guide future teachers through key data science processes, including data exploration, problem formulation, modeling, and results communication. In a pilot study, preservice primary teachers used a real-world dataset to explore digital gaming habits of young people. Findings show that students effectively formulated statistical questions and created visualizations to answer them. However, they tended to select their own topics and struggled to connect their analyses to the module’s thematic context, highlighting both the motivational potential and the challenges of working with large, multivariate datasets.

Details zur Publikation

Herausgeber*innenBirk, Lisa; Loth, Gerrit; Jotzo, Luca; Binder, Karin; Frischemeier, Daniel
BuchtitelStatistics and Data Science Education in STEAM. Proceedings of the Satellite Conference of the International Association for Statistical Education (IASE)
Seitenbereich1-8
VerlagSelbstverlag / Eigenverlag
Verlegt durchISI/IASE
ErscheinungsortMünster
StatusVeröffentlicht
Veröffentlichungsjahr2026
Sprache, in der die Publikation verfasst istEnglisch
KonferenzIASE 2025 Satellite Conference, 30.09.-02.10.2025, Münster, Deutschland
DOI10.52041/iase25.131
Link zum Volltexthttps://iase-pub.org/conference_proceedings/IASECP/article/view/485/478
StichwörterData Science Bildung; Lehramtsstudium

Autor*innen der Universität Münster

Birk, Lisa
Professur für Didaktik der Mathematik mit dem Schwerpunkt Primarstufe (Prof. Frischemeier)