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

P. 14–25.

Maksimenkova O. V., Neznanov A., Radchenko I.

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.

Keywords: образование, education, наука о данных, data science, Data expeditions, collaborative technologies, дата экспедиция, коллаборативные технологии

Publication based on the results of: Intelligent Data Analysis in Interactive Systems for Transdisciplinary Applications (2020)

In book

The Challenges of the Digital Transformation in Education

Vol. 1. , Switzerland: Springer, 2020.