Minor in Data Science. Virtual Learning Environment with Learning Analytics Support

Authors

  • Илья Леонидович Мусабиров Higher School of Economics, Moscow, Russia
  • Александр Владимирович Сироткин Higher School of Economics, Moscow, Russia

Keywords:

virtual learning environment, data analysis, learning analytics, machine learning, social network analysis

Abstract

This paper describes the design of a bootstrapped Virtual Learning Environment, developed for the undergraduate minor in Data Processing and Analysis. The environment is designed and deployed simultaneously with Learning Analytics subsystem to support students of diverse academic background studying in mixed groups. It includes integrated data analysis and statistical graphics environment, data applications server, interactive exercises system, tools for online communication and peer support, and progress tracking for students. Learning analytics subsystem includes analytical routines for behavioral logs, context-based surveys with a network component, and tools for analysis of online communication among the participants. The focus of Learning Analytics subsystem is on the social side of learning. Thus it includes advanced instruments for Social Network Analysis.

Author Biographies

  • Илья Леонидович Мусабиров, Higher School of Economics, Moscow, Russia

    Ilya L. Musabirov: MSc, Lecturer Department of Sociology Higher School of Economics

  • Александр Владимирович Сироткин, Higher School of Economics, Moscow, Russia

    Alexander V. Sirotkin: PhD, Associate Professor Department of Applied Mathematics Higher School of Economics, Senior Research Fellow SPIIRAS.

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Published

2017-06-04

Issue

Section

Training of specialits: studying programms

How to Cite

[1]
И. Л. Мусабиров and А. В. Сироткин, “Minor in Data Science. Virtual Learning Environment with Learning Analytics Support”, Компьютерные инструменты в образовании, no. 4, pp. 32–42, Jun. 2017, Accessed: Jul. 24, 2026. Available: http://cte.eltech.ru/ojs/index.php/kio/article/view/1405

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