Exploring Information Technology Industry Programming Language Trends with Non-Negative Matrix Factorization Topic Modelling


  • Niel Francis Casillano Department of Information Technology, College of Computer Studies, Eastern Samar State University, Philippines
  • Karen Cantilang Department of Information Technology, College of Computer Studies, Eastern Samar State University, Philippines




Topic Modelling, NMF, T, Industry, Programming


The study aimed to determine the preferred programming language among information technology professionals using non-negative matrix factorization topic modelling technique. The results showed that the majority of participants were software developers and programmers who commonly used C#, Java, and Python, and agreed that Java, C, or C++ would be the best language to start with when learning programming. The application of topic modelling revealed key themes such as online video tutorials as effective learning resources, hands-on activities as key to learning programming, importance of feedback, effective teaching strategies, and problem-solving skills as crucial for success in programming. Results of the study may serve as baseline data for the improvement of curricular offerings.


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How to Cite

Casillano, N. F., & Cantilang, K. (2023). Exploring Information Technology Industry Programming Language Trends with Non-Negative Matrix Factorization Topic Modelling. EDUCATUM Journal of Science, Mathematics and Technology, 10(1), 35–44. https://doi.org/10.37134/ejsmt.vol10.1.5.2023