The study of Coursera’s data science specialization
Keywords
Data science specialization
Coursera
R
How to Cite
Abstract
Objective: To identify the characteristics of the specialization form of the massive open online courses. Research object: a learning process of the massive open online courses. Research subject: Data science specialization of Coursera. Research objectives: to participate as a student in the several online courses in “data science specialization”, to find the structure of this specialization, to determine its characteristics. Methods: participant observation, content analysis. Results: Data science specialization of Cousera project is a series of 9 courses covering concepts and tools of data analysis, from the research questions formulation to results publication. The implementation of a special Capstone Project has completed this sequence of courses. Сourses are repeated once a month during a year. The courses in the specialization are related with a hard and a soft dependences. Course structure consists of syllabus, short video lectures, tests, peer assessment, course projects, forum. The software R, RStudio, Git, GitHub are used for programming assignment. Conclusions and recommendations: there are next ways to aggregate this form in the traditional educational process of Ukrainian universities: developing training and methodological support of disciplines, the students work organization with course materials, including the topics in qualification works, using new data analysis tools and techniques in the post graduate and post doctoral studies.
References
2. Capstone [Electronic resource]. – Access mode : http://en.wikipedia.org/wiki/Capstone.
3. Chauhan A. Massive Open Online Courses (MOOCS) : Emerging Trends in Assessment and Accreditation / A. Chauhan // Digital Education Review. – 2014. – No 25. – Access mode : http://greav.ub.edu/der/index.php/ der/article/view/277/491.
4. Coursera [Electronic resource]. – Access mode : https://www.coursera.org.
5. Johns Hopkins University Data Science [Electronic resource]. – Access mode : https://www.coursera.org/specialization/jhudatascience/ 1?utm_medium=listingPage.
6. Reyes-Ortiz J. Human Activity Recognition Using Smartphones Dataset Version 1.0. [Electronic resource] / Jorge L. Reyes-Ortiz, Davide Anguita, Alessandro Ghio, Luca Oneto. – Access mode: www.smartlab.ws.
7. Heaton J. My thoughts on courses 1-9 of the Johns Hopkins courser data science specialization [Electronic resource] / Jeff Heaton. – Access mode : http://www.jeffheaton.com/2014/08/my-thoughts-on-courses-1-9-of-the-johns-hopkins-coursera-data-science-specialization/.
8. What-is-a-capstone-project [Electronic resource]. – Access mode : https://fanatiq.wordpress.com/2009/07/23/what-is-a-capstone-project/.
9. Адаменко О. В. Хмарні технології аналізу даних / О. В. Адаменко, Л. Ф. Панченко // Хмарні технології в освіті : матеріали Всеукр. наук.-метод. семінару. – Кривий Ріг : Видавничий відділ КМІ, 2012. – С. 143-144.
10. Calter M. MOOCs and the library: engaging with evolving pedagogy / Calter Mariellen [Electronic resource]. – Access mode : http://library.ifla.org/160/.
11. Панченко Л. Ф. Масовий відкритий онлайн курс як альтернативна форма підвищення кваліфікації викладача вищої школи / Л. Ф. Панченко // Education and pedagogical sciences. – 2013. – № 1(156). – С. 19-28.
12. Панченко Л. Ф. Практикум по анализу данных / Л. Ф. Панченко. – Луганск : Изд-во ГУ «ЛНУ имени Тараса Шевченко», 2013. – 269 с.