Impact of Programming Languages on Learning Performance

• Published in: International journal of information and communication technology education Vol. 21; no. 1; pp. 1 - 17
• Main Authors: Zaldivar, Daniel, Cuevas, Erik Hombre, Perez, Marco
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.01.2025
• Subjects: Algorithms; Artificial intelligence; Communication; Communication (Thought Transfer); Computer vision; Computers; Curricula; Curriculum Design; Data analysis; Design of experiments; Educational Methods; Educational Strategies; Effectiveness; Engineering; Engineering Education; Image processing; Influence of Technology; Information technology; Learning; Learning Processes; Machine learning; Mathematical Models; Mathematics Education; Mathematics Skills; Matlab; Periodicals; Programming languages; Python; Students; Teaching; Teaching Methods; Technology education; Visualization; World Problems
• ISSN: 1550-1876; 1550-1337
• DOI: 10.4018/IJICTE.371419

The integration of various programming languages into the undergraduate engineering curriculum often occurs without adequate evaluation of their effectiveness within specific disciplines. Recently, Python and MATLAB have garnered significant attention as preferred languages for teaching subjects such as image processing and computer vision. Despite their popularity, few studies have evaluated their effectiveness in teaching these topics. This study aimed to determine which programming language, Python or MATLAB, facilitates a better understanding of image processing concepts. The analysis compared the learning performance of two groups, each comprising 40 students. One group utilized MATLAB as the programming tool, while the other implemented image processing algorithms using Python. To analyze the differences between these languages, a testing method of experimental design was employed. The results indicate that students who learned with MATLAB demonstrated superior learning performance compared to those who used Python.