METHODOLOGICAL APPROACHES TO ORGANIZATION OF EDUCATIONAL MATERIALS OF THE DISCIPLINE «MODELS AND MEANS OF WORKING WITH LARGE DATA VOLUMES (BIG DATA) »
Journal Title: Наукові праці. Серія "Педагогіка" - Year 2018, Vol 313, Issue 301
Abstract
Development of informational technologies leads to the necessity of adjusting the content of education, and this first of all con-cerns preparation of IT specialists at universities. In particular, boisterous development of network technologies and the technolo-gies of data collection, processing, and storage contribute to considerable increase of data streams and volumes, and in its turn this results in development and implementation of new technologies united under an umbrella name «Big Data». These processes are also reflected within the higher IT education system: new disciplines appear, in particular the discipline «Models and means of working with big volumes of data (Big Data) ». The content component of specialized professional knowledge of Big Data technologies is sufficiently covered in corresponding literature. However, analysis of the process of preparation of IT specialists especially indicates that provision of knowledge about the above-mentioned technologies needs to be augmented. The goal of this article is to cover methodological approaches to choice and presenting of educational materials about the Big Data technologies. The methodological techniques are based on the peculiarities of the basic stages of learning and the specifics of the discipline. The students already possess a sufficient base of theoretical and practical knowledge, the experience of creative search and of independent learning of study materials. This way the study materials should be primarily aimed at understanding of the peculiarities of work with big volumes of data. Theoretical points are illustrated with an example of working with a system that belongs to the Big Data class, a Document Databases MongoDB. Suggested methodological approaches of educational materials choice and presenting allow to shape the students’ understanding of the models and means of working with big volumes of data, as well as the necessary theoretical and practical knowledge for further studying of these technologies
Authors and Affiliations
E. Kirey, L. Solobuto
Keywords
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