Collaborative Learning in Data Science Education: A Data Expedition as a Formative Assessment Tool

  • Olga MaksimenkovaEmail author
  • Alexey Neznanov
  • Irina Radchenko
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 916)


The paper addresses the questions of data science education of current importance. It aims to introduce and justify the framework that allows flexibly evaluate the processes of a data expedition and a digital media created during it. For these purposes, the authors explore features of digital media artefacts which are specific to data expeditions and are essential to accurate evaluation. The rubrics as a power but hardly formalizable evaluation method in application to digital media artefacts are also discussed. Moreover, the paper documents the experience of rubrics creation according to the suggested framework. The rubrics were successfully adopted to two data-driven journalism courses. The authors also formulate recommendations on data expedition evaluation which should take into consideration structural features of a data expedition, distinctive features of digital media, etc.


Data expedition Data science Collaborative technologies Education 



The article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project “5-100”.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Olga Maksimenkova
    • 1
    Email author
  • Alexey Neznanov
    • 1
  • Irina Radchenko
    • 2
  1. 1.National Research University Higher School of EconomicsMoscowRussia
  2. 2.ITMO UniversitySt. PetersburgRussia

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