Affiliation:
1. School of Space and Information Technology, Siberian Federal University, 660041 Krasnoyarsk, Russia
2. Institute for Advanced Technologies and Industrial Programming, MIREA—Russian Technological University, 119454 Moscow, Russia
Abstract
During the past two decades, higher education institutions have been experiencing challenges in transforming the traditional way of in-class teaching into blended learning formats with the support of e-learning technologies that make possible the collection and storing of considerable amounts of data on students. These data have considerable potential to bring digital technologies in education to a new level of personalized learning and data-driven management of the educational process. However, the way data are collected and stored in a typical university makes it difficult to achieve the mentioned goals, with limited examples of data being used for the purposes of learning analytics. In this work, based on the analysis of existing information systems and databases at Siberian Federal University, we propose principles of design for a university database architecture that allow for the development and implementation of a data-driven management approach. We consider various levels of detail of education data, describe the database organization and structure, and provide examples of learning analytics tools that can benefit from the proposed approach. Furthermore, we discuss various aspects of its implementation and associated questions.
Funder
Russian Science Foundation
Subject
Public Administration,Developmental and Educational Psychology,Education,Computer Science Applications,Computer Science (miscellaneous),Physical Therapy, Sports Therapy and Rehabilitation
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