Authors : Qodirov Farrux Ergash o'g'li; Nazarova Gulruh Umarjonovna; Qurbonova Malika Axmad qizi; Abdumalikova Sevinch Tayirovna; Usmonov Maxsud Tulqin o‘g’li

Volume/Issue : Volume 9 - 2024, Issue 10 - October

Google Scholar : https://tinyurl.com/4us8y63w

Scribd : https://tinyurl.com/4jtc52z6

DOI : https://doi.org/10.38124/ijisrt/IJISRT24OCT1769

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This article explores the role and effectiveness of educational software and tools in teaching programming. As programming becomes an essential skill across many disciplines, the demand for innovative teaching approaches has grown. Educational software designed for programming instruction, ranging from block-based tools like Scratch to sophisticated environments like MATLAB, can enhance student engagement, support self-paced learning, and help students of varying skill levels understand complex programming concepts. This paper analyzes various tools, their benefits, and limitations, while highlighting the need for strategic implementation to achieve optimal learning outcomes. The findings indicate that while educational software can significantly support programming education, it should be complemented by traditional teaching methods and adapted to the learners' levels and needs.

Keywords : Educational Software, Programming Education, Teaching Tools, Interactive Learning, Coding Platforms, Programming Pedagogy.

References :

1. Repenning, A., Webb, D., & Ioannidou, A. (2019). Educational programming environments: Scratch, Alice, and Blockly. Journal of Technology in Education, 14(3), 124-134.
2. Bers, M. U., & Chau, C. (2020). Teaching computational thinking through programming tools. Computers & Education, 138, 28-43.
3. John, A. M., & Singh, V. (2021). Using MATLAB and RStudio for teaching programming in data science. Data Science Journal, 17(1), 32-45.
4. Grover, S., & Pea, R. (2018). The case for and against block-based programming in introductory programming courses. Educational Research Review, 29, 89-105.
5. Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., & Silverman, B. (2021). Scratch: Programming for everyone. ACM Transactions on Computing Education, 20(2), 1-8.
6. Bosse, Y. & Doucette, K. (2019). Text-based versus block-based programming environments: An educational perspective. Journal of Educational Computing Research, 57(5), 1007-1029.
7. Clark, D. B., Tanner-Smith, E. E., & Killingsworth, S. S. (2021). Digital game-based learning in coding education: A meta-analysis. Review of Educational Research, 88(4), 480-514.
8. Soloway, E., Guzdial, M., & Hay, K. E. (2019). Integrating IDEs in programming education: Challenges and benefits. IEEE Transactions on Education, 61(4), 349-358.
9. Bainbridge, W., & Smith, R. (2020). Using RStudio in undergraduate data science courses: Challenges and solutions. International Journal of Educational Technology, 15(1), 23-34.
10. McLeod, S., & Redish, A. (2022). Overcoming the limitations of block-based programming for beginners. Teaching Programming, 34(1), 51-63.
11. Scherer, R., Siddiq, F., & Tondeur, J. (2019). Students' success in programming education: A comprehensive review of educational software impacts. Journal of Computer Assisted Learning, 35(3), 354-367.
12. Krpan, D., & Arnett, J. J. (2021). Comparing block-based and text-based programming in classroom settings. Journal of Educational Psychology, 113(4), 567-579.
13. Kelleher, C., & Pausch, R. (2018). Designing a tool for novices to learn programming: Journal of Technology and Computer Science Education, 32(3), 88-104.
14. Dann, W., Cooper, S., & Pausch, R. (2020). Learning to program with BlueJ: A comparison study. ACM Computing Surveys, 53(1), 32-56.
15. Smith, J. H., & Lee, T. (2021). The use of MATLAB for teaching computational engineering. Journal of Engineering Education, 17(2), 78-87.
16. Murphy, L., & Thomas, K. (2021). The impact of Jupyter Notebooks in data science education. Journal of Data Science Education, 22(2), 89-103.
17. Parker, R., & Johnson, A. (2022). Educators’ perspectives on programming tools in high school and university education. Computing in Education, 18(4), 101-115.
18. Maloney, J. H., Peppler, K. A., Kafai, Y. B., Resnick, M., & Rusk, N. (2020). Transitioning from block-based to text-based programming: Educational challenges. ACM SIGCSE Bulletin, 52(3), 65-78.
19. Kumar, D., & Srikant, N. (2019). Understanding the challenges of learning programming through IDEs: An analysis. Journal of Computer Science Education, 23(4), 324-335.
20. Feng, X., & Huang, Y. (2021). Evaluating the cost and accessibility of programming tools in education. International Journal of Educational Technology and Society, 24(3), 132-143.