DEVELOPING ALGORITHMIC THINKING AND SYSTEM MODELING COMPETENCIES IN COMPUTER SCIENCE STUDENTS THROUGH MATLAB/SIMULINK-BASED SIMULATION- ORIENTED ACTIVE LEARNING

Authors

  • Saidaxon Atajonova Andijan State Technical Institute Author

Keywords:

MATLAB, Simulink, computer science, algorithmic thinking, system modeling, simulation-based learning, active learning, project-based learning, computer modeling, digital learning environment.

Abstract

 The digital transformation of professional activities in the field of information 
technology is increasing the requirements not only for proficiency in programming 
languages and software tools but also for future specialists’ ability to decompose complex 
systems, formalize real-world processes, develop computational algorithms, construct 
and verify models, conduct computational experiments, and make decisions based on the 
data obtained. The aim of this study is to develop a methodological approach to fostering 
algorithmic thinking and system modeling competencies among Computer Science 
students through MATLAB/Simulink-based simulation-oriented active learning. The 
methodological framework draws on the principles of simulation-based learning, active 
learning, problem/project-based learning, experiential learning, formative assessment, and 
progressive scaffolding. The proposed methodology is implemented through five 
interconnected stages: problem conceptualization, algorithm development, computer 
modeling, computational experimentation and optimization, and interpretation of results 
followed by project-based decision-making. Unlike approaches focused primarily on the 
use of ready-made simulation models, the proposed model requires a systematic 
transition from problem analysis to algorithm development in MATLAB, model 
construction in Simulink, model verification, parameter investigation, and evidence-based 
decision-making. An assessment framework has been developed that encompasses 
algorithmic thinking, system modeling, computational and experimental activities, and 
problem-solving. The proposed approach makes it possible to view MATLAB/Simulink 
not merely as a software package for performing calculations but as an integrated digital 
environment for developing the professional competencies of students in IT-related fields. 

References

1. Rodríguez-Gómez A., Granados-Fernández R., Lacasa E., Fernández-Marchante C. M., Rodrigo M. A. How to

Teach Frequency Response Easily to Chemical Engineers Using Spreadsheets // Education for Chemical Engineers. – 2025.

– Vol. 53. – P. 91–101. – DOI: 10.1016/j.ece.2025.06.001.

2. Romero-Cano L. A. Modular Simulation as a Teaching Tool: Integrating MATLAB-Simulink into Heat Transfer

Courses to Promote Active Learning and Conceptual Understanding // Education for Chemical Engineers. – 2025. – Vol.

53. – P. 171–177. – DOI: 10.1016/j.ece.2025.07.004.

3. Rodgers T. L. Critique – Tools for Sharing: MATLAB-Simulink into Heat Transfer Courses // Education for

Chemical Engineers. – 2025. – Vol. 53. – P. 178–179. – DOI: 10.1016/j.ece.2025.06.004.

4. Leiva C., Arroyo-Torralvo F., Luna-Galiano Y., Ronda A., Muñoz de la Peña D. Implementation of a Continuous

Assessment System Through the Creation of a Problem Book Using DOCTUS in General Chemistry Subjects // Education

for Chemical Engineers. – 2025. – Vol. 53. – P. 1–7. – DOI: 10.1016/j.ece.2025.06.003.

5. de Pedro Z. M., Alvarez-Montero A., Casas J. A., Muñoz M. Active Learning in Environmental Engineering:

Combining Interactive Platforms and Project-Based Approaches to Boost Engagement and Academic Performance //

Education for Chemical Engineers. – 2025. – Vol. 53. – P. 161–170. – DOI: 10.1016/j.ece.2025.09.002.

6. Jamil M. G., Isiaq S. O. Teaching Technology with Technology: Approaches to Bridging Learning and Teaching

Gaps in Simulation-Based Programming Education // International Journal of Educational Technology in Higher Education.

– 2019. – Vol. 16. – Article 25. – DOI: 10.1186/s41239-019-0159-9.

7. Computer-Controlled Systems Virtual Laboratory with MATLAB and Simulink // IFAC-PapersOnLine. – 2025.

– Vol. 59, No. 7. – P. 72–77. – DOI: 10.1016/j.ifacol.2025.08.025.

8. Xue D., Pan F. MATLAB and Simulink in Action: Programming, Scientific Computing and Simulation. – Singapore:

Springer, 2024. – DOI: 10.1007/978-981-99-1176-9.

9. Tang P., Zhang C., Du Y., Xu Y., Wang M., Yu H., Zhang X., Gong J., Zhang H., Sun X. Enhancing Experimental

Teaching of β-Interferon Synthesis Through a Virtual Simulation Platform: Application and Effectiveness Analysis //

Education for Chemical Engineers. – 2025. – Vol. 53. – P. 71–79. – DOI: 10.1016/j.ece.2025.07.007.

10. Lopez-Fernandez D., Gordillo A., Alarcon P. P., Tovar E. Comparing Traditional Teaching and Game-Based

Learning Using Teacher-Authored Games on Computer Science Education // IEEE Transactions on Education. – 2021. –

Vol. 64. – P. 367–373. – DOI: 10.1109/TE.2021.3057849.

11. Prince M. Does Active Learning Work? A Review of the Research // Journal of Engineering Education. – 2004.

– Vol. 93, No. 3. – P. 223–231.

12. Jamison C. S. E., Fuher J., Wang A., Huang-Saad A. Experiential Learning Implementation in Undergraduate

Engineering Education: A Systematic Search and Review // European Journal of Engineering Education. – 2022. – Vol. 47.

– P. 1356–1379. – DOI: 10.1080/03043797.2022.2031895.

13. Nieto Bermejo M., García Zancajo A., Nieto-Marquez A. Fostering Chemical Engineering Competencies

Through Competition Teams: The UPM MotoStudent Electric Experience // Education for Chemical Engineers. – 2025. –

Vol. 53. – P. 149–160. – DOI: 10.1016/j.ece.2025.09.001.

14. Cole J. S., Spence S. W. T. Using Continuous Assessment to Promote Student Engagement in a Large Class //

European Journal of Engineering Education. – 2012. – Vol. 37. – P. 508–525. – DOI: 10.1080/03043797.2012.719002.

15. Felder R. M., Brent R. Teaching and Learning STEM: A Practical Guide. – San Francisco: Jossey-Bass, 2016.

16. Atajonova S., Zulfikharov I. Improving the Methodology of Effective Organization of Mathematics Courses in

Technical Universities // AIP Conference Proceedings. – 2024. – Vol. 3244, No. 1. – DOI: 10.1063/5.0241836.

17. Boratalievna A. S. Models and Mechanisms for Implementing an Inclusive Approach in Engineering Education

Based on Artificial Intelligence // International Journal of Pedagogics. – 2025. – Vol. 5, No. 5. – P. 110–114.

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Published

2026-08-05

Issue

Section

13.00.00 Pedagogical Sciences

How to Cite

DEVELOPING ALGORITHMIC THINKING AND SYSTEM MODELING COMPETENCIES IN COMPUTER SCIENCE STUDENTS THROUGH MATLAB/SIMULINK-BASED SIMULATION- ORIENTED ACTIVE LEARNING . (2026). Modern Scientific and Technical Research, 2(3), 51-60. https://ijcst.uz/index.php/journal/article/view/147