Data farming for virtual school laboratories

Abstract

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.