Journal of Digital Social Research (Oct 2021)

Crowd science infused learning: Connecting online teaching and crowd science in the social sciences

  • Isabell Stamm,
  • Michael Weinhardt,
  • Marie Gutzeit,
  • Matthias Bottel,
  • Johannes Lindenau

DOI
https://doi.org/10.33621/jdsr.v3i3.71
Journal volume & issue
Vol. 3, no. 3

Abstract

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In this article, we reflect upon the combination of crowd science and online teaching, which we refer to as Crowd Science infused Learning. We discuss Crowd Science infused Learning's conceptual design and its viability in sociology and related disciplines. For this purpose, our research project ‘Data Traces’ serves as an empirical case. In the project, we developed an online platform that provided a 45-minute teaching unit, training students in using different forms of digital data: websites, newspaper articles, and administrative register data. Afterwards, students were assigned to predefined, small-scale research tasks contributing to a real-world research project on the social relations in entrepreneurial groups. By completing the tasks, the students could apply their knowledge, gain insights, and contribute actively to an ongoing research project. This combination links students' learning experience with the collection of data for research purposes. We also implemented game elements in the platform's design to support students' motivation. After a brief outline of the Data Traces Project's chronology and key conceptual decisions, the article focuses on a critical discussion of the combination of crowd science and online teaching. Despite significant challenges, we believe that Crowd Science infused Learning is a promising approach and identify opportunities and conditions for a successful combination of crowd science and online teaching.

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