Teaching data literacy: curriculum content and competitive advantages

Authors

  • Andrey Aleksandrovich Deryabin Russian Presidential Academy of National Economy and Public Administration
  • Aleksandr Anatolyevich Popov Russian Presidential Academy of National Economy and Public Administration

Keywords:

big data, data literacy, data science education, machine learning, artificial intelligence, school education, computer science education, curriculum development

Abstract

A review of publications and an analysis of major discussions about the Data Science curriculum development for middle and secondary school is presented with special emphasis on use of authentic data and data relevancy to students’ context.

About authors

Andrey Aleksandrovich Deryabin

Russian Presidential Academy of National Economy and Public Administration

Federal Education Development Institute
Researcher

MSc Social Psychology

Aleksandr Anatolyevich Popov

Russian Presidential Academy of National Economy and Public Administration

Federal Education Development Institute
Head of open education section

Moscow City University
Institute of system projects
Head of competency practices lab

Novosibirsk State Technical University
Sociology & mass communications dept.
Professor

Dr. Sci. (Philos.), associate professor

Информационное общество, 2021, выпуск 1

Published

28.02.2021

How to Cite

Deryabin, A. A., & Popov, A. A. (2021). Teaching data literacy: curriculum content and competitive advantages. Information Society, (1), 21-29. Retrieved from http://infosoc.iis.ru/article/view/553

Issue

No. 1 (2021): Numeral quaque janua panditur

Section

Education in the information society

Copyright (c) 2021 Андрей Александрович Дерябин, Александр Анатольевич Попов

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.