2025/10/27 by Dmytrii Verbivskyi, Serhii Zhukovskyi, Olena Usata +2 · 1 voice
Computer Science · Social Sciences · #Innovative Educational Technologies #Mathematics Education and Teaching Techniques #Teaching and Learning Programming
paper · doi:10.70389/pjs.100153
openalex publication_date 2025/10/27 · openalex created_date 2025/10/31 · openalex updated_date 2026/07/23
BACKGROUND The integration of modern information technologies, such as machine learning, cloud computing, and computer algebra systems (CAS), has revolutionized problem-solving in mathematics and computer science. These technologies enhance computational speed, accuracy, and efficiency, offering new methods for approaching complex problems in both research and educational contexts. This systematic review evaluates the role of these technologies in improving problem-solving processes and their implications for educational practices in mathematics and computer science. MATERIALS AND METHODS A comprehensive search was conducted in academic databases such as Scopus, Web of Science, and Google Scholar, targeting peer-reviewed articles, books, and conference proceedings published from 2016 to 2025. The review focuses on studies involving machine learning, cloud computing, and CAS, particularly those addressing their educational applications in mathematics and programming instruction. A rigorous selection process was applied to include only studies with methodological rigor and empirical evidence. RESULTS The review finds that information technologies significantly improve problem-solving efficiency. CAS such as Maple and Mathematica reduce errors and speed up calculations. High-level programming languages like Python enhance algorithm development productivity, while cloud computing accelerates task execution. Additionally, machine learning models offer personalized learning experiences, which enhance student engagement and understanding in educational settings. CONCLUSION Modern information technologies improve both computational problem-solving and educational outcomes. Despite challenges such as resource limitations and teacher training, their integration into educational practices presents numerous benefits. Future research should focus on real-world validation to further assess the long-term effectiveness of these technologies in diverse educational environments.