Data Literacy as a meta-skill: options for Data Science curriculum implementation

Pavel Glukhov (Russia), Andrey Deryabin (Russia), Aleksandr Popov (Russia)

Data science is affecting an increasingly wide area of everyday life but general education in Russia has not yet reacted to the new challenges associated with this aspect of digitalization. The changes in technologies, the economy, and society over the last two decades have formed a new agenda for teaching mathematics and information technologies, as well as media education and social sciences. Education in all these fields requires a reconsideration of the content and methods of teaching due to the increasing importance of data science and artificial intelligence in the context of fundamental changes in the economy and the labor market. As many areas of human life are changing, there is a need to formulate new types and kinds of educational results, at which modern pedagogy should be aimed. A modern way of meeting such challenges is to distinguish new literacies (media literacy, environmental literacy, functional literacy, etc.). The article deals with the concept of data literacy, examines its content and composition, and substantiates its relevance as an educational result consistent with digitalization trends that one can observe in modern society. A distinction is made between approaches to in-depth and general studies of data science. A description is given of various types of tasks aimed at developing data literacy among students in the context of their setting on different educational material. The authors consider possible ways of deploying programs aimed at mastering data science by students without the need to formalize it into a separate discipline or school subject.