Preview

The Education and science journal

Advanced search

A PRACTICE OF OPEN DATA ADOPTION TO «PROGRAMMING» COURSE OF «SOFTWARE ENGINEERING» BACHELOR PROGRAM

https://doi.org/10.17853/1994-5639-2016-10-107-121

Abstract

Abstract. The aim of the publication is to show the possibilities of use of open data in teaching courses of programming.

Methods. The results of adoption of the technique presented in the publication to the process of training in programming at the first year of the course «Program Engineering» are received by a comparative research and analysed by methods of descriptive statistics.

Results and scientific novelty. The technique of the use of open data sets when developing training and control tasks on programming for students of a bachelor degree of information and technological educational program specialization is offered; standard tasks templates are presented.

The application of open data in the educational purposes is a rather new direction in education that considerably enables to improve the quality of training of an expert in the field of computer sciences: to bring closer educational tasks to real; to increase variability of control tasks; to increase motivation of students. However, along with positive characteristics of the presented method, there are some difficulties of the method introduction in educational process. The authors have formulated the problems arising when using open data; possible ways of their decision are shown.

Practical significance. The results received during the research show the possibilities of further expansion of application of open data in education. The described practical experience of training in programming can be partially or completely used by teachers of other training courses.

About the Authors

Olga V. Maksimenkova
National Research University Higher School of Economics, Moscow
Russian Federation
Junior Research Fellow, International Laboratory for Intelligent Systems and Structural Analysis: Senior Lecturer, School of Software Engineering, Faculty of Computer Science


Vadim V. Podbelskiy
National Research University Higher School of Economics, Moscow
Russian Federation
Doctor of Technical Sciences, Professor, School of Software Engineering, Faculty of Computer Science


References

1. Open Knowledge project. The open definition. Available at: http://opendefinition.org. (Translated from English)

2. Encheva S. Lecture notes in electrical engineering. Educational Data Mi￾ning for Problem Identification. 2014. Vol. 269. Р. 3491–3494. (Translated from English)

3. Muna A. R., Atheer S. A. K., Hend S. A. K. Educational data mining: a systematic review of the published literature 2006–2013. Lecture Notes in Electrical Engineering. 2015. Vol. 285. Р. 711–720. (Translated from English)

4. EdStats: Education Statistics (2015). Available at: http://datatopics.worldbank.org/education/. (Translated from English)

5. Drupal Groups. Using open data in education. 2011. Available at: https://groups.drupal.org/using-open-data-education. (Translated from English)

6. Ernst M. Teaching intro CS and programming by way of scientific data analysis. 2012. Available at: http://programanalysis.blogspot.ru/2012/08/teaching-intro-cs-and-programming-by.html. (Translated from English)

7. Jormanainen I., Sutinen E. An open approach for learning educational data mining. Koli Calling’13. Koli. 2013. Р. 203–204. (Translated from English)

8. Jo S., Ku J. O. Problem based learning using real-time data in science education for the gifted. Gifted Education International. 2011. Vol. 27. Р. 263–273. (Translated from English)

9. White S. Conceptual Structures for STEM data: Linked, Open, Rich and Personal. ICCS. 2013. Р. 1–21. (Translated from English)

10. Radchenko I., Sakoyan A. On Some Russian Educational Projects in Open Data and Data Journalism. Open Data for Education. Linked, Shared, and Reusable Data for Teaching and Learning. Springer International Publishing, 2016. Р. 153–165. (Translated from English)

11. Maksimenkova O., Podbelskiy V. On practice of using open data in construction of training and assessment tasks for programming courses. 10th International Conference on Computer Science & Education. 2015. Р. 233–236. (Translated from English)

12. Jackson D., Miller R. A new approach to teaching programming, 2009. (Translated from English)

13. Vahrenhold J., Paul W. Developing and validating test items for first-year computer science courses. Computer Science Education. 2014, October. Vol. 24. № 4. Р. 304–333. (Translated from English)

14. Pendergast M. O. Teaching Introductury Programming to IS Students: Java Problems and Pitfalls. Journal of Information Techonology Education. 2006. Vol. 5. Р. 491–515. (Translated from English)

15. Leutenegger S., Edgington J. A. A games first approach to teaching introductory programming. 38th SIGCSE Technical Symposium on Computer Science Education. SIGCSE 2007. New York, 2007. Р. 115–118. (Translated from English)

16. de Jonge E., van der Loo M. An introduction to data cleaning with R. Heerlen: Statistics Netherlands, 2013. 53 p.

17. Wichham H. Tidy Data. Journal of Statistical Software. 2014. Vol. 59. № 10. (Translated from English)

18. What is R? The R Project for Statistical Computing. 2014. Available at: https://www.r-project.org/about.html. (Translated from English)

19. Stevens S. S. On the Theory of Scales of Measurement. Science. 1946. Vol. 103. № 2684. Р. 677–680. (Translated from English)


Review

For citations:


Maksimenkova O.V., Podbelskiy V.V. A PRACTICE OF OPEN DATA ADOPTION TO «PROGRAMMING» COURSE OF «SOFTWARE ENGINEERING» BACHELOR PROGRAM. The Education and science journal. 2016;(10):107-121. (In Russ.) https://doi.org/10.17853/1994-5639-2016-10-107-121

Views: 1142


ISSN 1994-5639 (Print)
ISSN 2310-5828 (Online)