Paper—Using Data Expedition as a Formative Assessment Tool in Data Science Education: Reasoning … Using Data Expedition as a Formative Assessment Tool in Data Science Education: Reasoning, Justification, and Evaluation https://doi.org/10.3991/ijet.v14i11.10202 Olga Maksimenkova ( * ) , Alexey Neznanov National Research University Higher School of Economics, Moscow, Russia omaksimenkova@hse.ru Irina Radchenko ITMO University, St. Petersburg, Russia Abstract—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 arte- facts which are specific to data expeditions and are essential to accurate evalua- tion. The rubrics as a power but hardly formalizable evaluation method in ap- plication to digital media artefacts are also discussed. Moreover, the paper doc- uments the experience of rubrics creation according to the suggested frame- work. The rubrics were successfully adopted to two data-driven journalism courses. The authors also formulate recommendations on data expedition evalu- ation which should take into consideration structural features of a data expedi- tion, distinctive features of digital media, etc. Keywords—Data expedition, data science, collaborative technologies, forma- tive assessment, higher education 1 Introduction It is well known that Data Science (DS) is relatively young and rapidly growing area. The discussions about DS and its understanding as a field are still heat topic of current interest [1]. To be clear in this paper we will follow the definition of DS from IBM Analytics [2]: “Data Science is an interdisciplinary field that combines machine learning, statis- tics, advanced analysis, and programming. It is a new form of art that draws out hidden insights and puts data to work in the cognitive era”. Naturally, the youthfulness of DS is one the main reasons why data science educa- tion (DSE) is shaping today. However, several teaching and learning techniques and methods have been already introduced to the courses in this area [3, 4]. It is interest- ing that the actuality of DSE increases not only to data scientists but to the specialists of the other fields as well (e.g., education, medicine, journalism). This explains by iJET ‒ Vol. 14, No. 11, 2019 107