RUDN Journal of Informatization in EducationRUDN Journal of Informatization in EducationВестник Российского университета дружбы народов. Серия: Информатизация образования2312-86312312-864XPeoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)3022910.22363/2312-8631-2021-18-4-347-359DIGITAL EDUCATIONAL ENVIRONMENTЦИФРОВАЯ ОБРАЗОВАТЕЛЬНАЯ СРЕДАResearch ArticleData farming for virtual school laboratoriesВыращивание данных для школьных виртуальных лабораторийhttps://orcid.org/0000-0002-1216-5043PatarakinYevgeny D.ПатаракинЕвгений Дмитриевич

Doctor of Pedagogical Sciences, Academic Supervisor of the educational program “Digital Transformation of Education”

доктор педагогических наук, академический руководитель образовательной программы «Цифровая трансформация образования»

epatarakin@hse.ruhttps://orcid.org/0000-0001-6217-0871YarmakhovBoris B.ЯрмаховБорис Борисович

Candidate of Philosophical Sciences, Research Supervisor of the Center for Data Analysis, Institute for Digital Education

кандидат философских наук, научный руководитель Центра анализа данных, Институт цифрового образования

yarmakhovbb@mgpu.ruNational Research University “Higher School of Economics,”Национальный исследовательский университет «Высшая школа экономики»Moscow City UniversityМосковский городской педагогический университет30122021184VOL 18, NO4 (2021)ТОМ 18, №4 (2021)34735914022022Copyright ©; 2021, Patarakin Y.D., Yarmakhov B.B.Copyright ©; 2021, Патаракин Е.Д., Ярмахов Б.Б.2021Patarakin Y.D., Yarmakhov B.B.Патаракин Е.Д., Ярмахов Б.Б.http://creativecommons.org/licenses/by/4.0https://journals.rudn.ru/informatization-education/article/view/30229

Problem and goal. Building statistical, mathematical, computational and research literacies in teaching school subjects is discussed in the article. The purpose is to develop a model for generating data for research experiments by students. Methodology. The Netlogo data generation and consecutive statistical data procession in CODAP and R programming language were used. Results. The generative approach helps students to work with data collected by agents, programmed by students themselves. In doing so, the student assumes the position of a researcher, who plans an experiment and analyses its results. Conclusion. The proposed approach of data generation and analysis allows to introduce the student to the contemporary culture of generating and sharing data.

Проблема и цель. Рассматривается преподавание школьных дисциплин, связанных с формированием статистической, математической, вычислительной и исследовательской грамотности. Цель состоит в порождении данных в ходе экспериментов, условия которых диктуются учениками. Методология. В исследовании использованы генерация данных в агентных моделях NetLogo и последующая статистическая обработка в средах CODAP и R. Результаты. Показано, что генеративный подход позволяет ученикам работать с данными, которые порождаются агентами-исполнителями, выполняющими указания учащегося. При этом ученик находится в позиции ученого, который планирует собственные эксперименты и анализирует полученные в их процессе данные. Заключение. Предложенный подход генерации данных для их последующего анализа приобщает школьников к современной культуре выращивания и обмена данными и генерирующими их моделями.

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