Unified Graphic Visualization of Activity (UGVA) Method

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: 2nd International Conference on Novel and Intelligent Digital Systems, NiDS 2022

Год издания: 2023

Идентификатор DOI: 10.1007/978-3-031-17601-2_25

Ключевые слова: cognitive graphics, curriculum, decision making, digital educational footprint, lifelong learning concept, personalized learning space, ugva method

Аннотация: The article focuses on the need to maintain data from the digital educational footprint throughout the student’s life in the frame of institutional, corporate and independent learning. The grounds for decision-making such as the scope of the learning situation and the depth of analysis are identified. The possibilities of multidimeПоказать полностьюnsional analysis and cognitive computer graphics to enhance decision-making in LMS are considered. The advantages of Chernoff faces and their modifications are emphasized. It is suggested to form an image of a specialist in the form of an anthropomorphic figure and overlay individual attributes from the digital educational footprint of a student. The method of Unified Graphic Visualization of Activity (UGVA) is described. It allows forming images of specialists, comparing them with each other, and estimating the balance of educational material contribution. An example of the formation of a specific profile for the academic program “Informatics and Computer Science” and its visualization in UGVA notation is given. Images are formed for several students, including current learning achievements from individual digital educational footprints (competence aspect). The example is accompanied by recommendations for teachers of the academic department implementing the corresponding program in Siberian Federal University. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Ссылки на полный текст

Издание

Журнал: Lecture Notes in Networks and Systems

Выпуск журнала: Vol. 556 LNNS

Номера страниц: 255-265

ISSN журнала: 23673370

Издатель: Springer Science and Business Media Deutschland GmbH

Персоны

  • Uglev V. (Siberian Federal University, Krasnoyarsk, Russian Federation)

Вхождение в базы данных