Generation of academic groups and project teams based on learners data acquisition
Main Article Content
Abstract
The questions of usage of the learners’ data in the solutions for generating student academic groups, electives and project teams are considered. The applications of Machine Learning clustering algorithms for these tasks are illustrated. The opportunity of usage of social network data is shown.
Article Details
References
2. Селевко Г.К. Энциклопедия образовательных технологий. Том 1. М.: Народное образование, 2005. С. 224–225.
3. Семенов А.В., Веретенник Е.В., Пронин А.С. Формирование учебных групп в университете с помощью анализа социальных сетей // Вопросы образования. 2014. № 3. С. 18–21.
4. Официальный сайт проекта VK API. URL: https://vk.com/dev
5. Королев М.А. Статистический словарь. М.: Финансы и статистика, 1989. 623 с.
6. Котов А., Красильников Н. Кластеризация данных, 2006. URL: https://logic.pdmi.ras.ru/~yura/internet/02ia-seminar-note.pdf
7. Нейский И.М. Классификация и сравнение методов кластеризации // Интеллектуальные технологии и системы. Сб. учебно-методических работ и статей аспирантов и студентов. М.: НОК «CLAIM», 2006. Вып. 8. С. 130–142.
8. Тараскина А.С. Нечеткая кластеризация по модифицированному методу С-средних и ее применение для обработки микрочиповых данных // Проблемы интеллектуализации и качества систем автоматизации. 2013. № 13. С. 217–228.
Presenting an article for publication in the Russian Digital Libraries Journal (RDLJ), the authors automatically give consent to grant a limited license to use the materials of the Kazan (Volga) Federal University (KFU) (of course, only if the article is accepted for publication). This means that KFU has the right to publish an article in the next issue of the journal (on the website or in printed form), as well as to reprint this article in the archives of RDLJ CDs or to include in a particular information system or database, produced by KFU.
All copyrighted materials are placed in RDLJ with the consent of the authors. In the event that any of the authors have objected to its publication of materials on this site, the material can be removed, subject to notification to the Editor in writing.
Documents published in RDLJ are protected by copyright and all rights are reserved by the authors. Authors independently monitor compliance with their rights to reproduce or translate their papers published in the journal. If the material is published in RDLJ, reprinted with permission by another publisher or translated into another language, a reference to the original publication.
By submitting an article for publication in RDLJ, authors should take into account that the publication on the Internet, on the one hand, provide unique opportunities for access to their content, but on the other hand, are a new form of information exchange in the global information society where authors and publishers is not always provided with protection against unauthorized copying or other use of materials protected by copyright.
RDLJ is copyrighted. When using materials from the log must indicate the URL: index.phtml page = elbib / rus / journal?. Any change, addition or editing of the author's text are not allowed. Copying individual fragments of articles from the journal is allowed for distribute, remix, adapt, and build upon article, even commercially, as long as they credit that article for the original creation.
Request for the right to reproduce or use any of the materials published in RDLJ should be addressed to the Editor-in-Chief A.M. Elizarov at the following address: amelizarov@gmail.com.
The publishers of RDLJ is not responsible for the view, set out in the published opinion articles.
We suggest the authors of articles downloaded from this page, sign it and send it to the journal publisher's address by e-mail scan copyright agreements on the transfer of non-exclusive rights to use the work.