Fostering Natural and Data Science Skills of School Kids

Alexander Nussbaumer*, Christina Steiner-Stanitznig, Silke Luttenberger, Sylvia Ebner, Christian Gütl

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


While on the labour market there is a high demand for employees educated and skilled in the field of natural sciences, engineering and information technologies, a lack of interest in these fields of expertise can be identified in young people. The aim of our research is to leverage a scientifically founded and empirically validated approach and contribution towards promoting interest and motivation in dealing with data science and scientific and technical subjects. To this end a novel pedagogical approach and a related learning environment has been developed and used in a first pilot phase. This approach was implemented using research and exploration questions on weather forecasts and data from temperature measurements as an example pedagogical scenario. The pilot study was executed in real-world settings of three primary and two secondary schools. The results demonstrate high interest and motivation in the science project and related data science tool.

Original languageEnglish
Title of host publicationEducating Engineers for Future Industrial Revolutions - Proceedings of the 23rd International Conference on Interactive Collaborative Learning ICL2020
EditorsMichael E. Auer, Tiia Rüütmann
Place of PublicationCham
Number of pages12
ISBN (Electronic)978-3-030-68198-2
ISBN (Print)978-3-030-68197-5
Publication statusPublished - 2021
Event2020 International Conference on Interactive Collaborative Learning: ICL 2020 - Virtuell, Tallinn, Estonia
Duration: 23 Sept 202025 Sept 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1328 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


Conference2020 International Conference on Interactive Collaborative Learning
Abbreviated titleICL 2020
CityVirtuell, Tallinn


  • Data Science Process
  • Digital literacy
  • Inquiry-based learning
  • Science learning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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