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Data Science and Big Data in Upper Secondary Schools: A Module to Build up First Components of Statistical Thinking in a Data Science Curriculum

Biehler, Rolf; Frischemeier, Daniel; Podworny, Susanne; Wassong, Thomas; Budde, Lea; Heinemann, Birte; Schulte, Carsten

Abstract:
Within the framework of a design-based research project, computer science educators and statistics educators at Paderborn University designed a pilot course on the subject of data science and big data. It addresses upper secondary students and was realized by weekly sessions (three hours) over seven months. The whole course that is intended to introduce upper secondary school students to the field of data science consists of four modules. In module 1, the learners are introduced into the basics of statistics and big data and it aims at developing their data competence and data awareness. In the sec- ond module, learners are introduced to machine learning and programming based, among others, on examples from module 1. In the third and fourth module, learners can apply their knowledge gained in modules 1 and 2 and will work in small groups on real and meaningful data science projects. In this paper, we want to concentrate on the statistics components, especially of module 1, and we will present how we develop the data competence and data awareness of upper secondary school students to prepare them to work on data science projects in modules 3 and 4.


Verlagsausgabe §
DOI: 10.5445/KSP/1000087327/28
Veröffentlicht am 22.12.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2018
Sprache Englisch
Identifikator ISSN: 2363-9881
KITopen-ID: 1000127944
Erschienen in Archives of Data Science, Series A (Online First)
Band 5
Heft 1
Seiten P28, 19 S. online
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