International Journal of Recent Development in Computer Technology & Software Applications [ISSN: 2581-6276 (online)]

Essentials of Data Visualization and Infographic Design: Principles, Elements, and Tools

Rujittika Mungmunpuntipantip — 2025-03-15

Data visualization and infographic design are essential skills for effectively communicating complex information. This article explores the fundamental principles of data visualization, the key elements involved in creating compelling infographics, and the tools commonly used for their design. It provides insights into how to select appropriate graph types, use color effectively, and arrange data for clarity. Additionally, it highlights the importance of design elements such as fonts, icons, and layout in creating visually appealing and informative infographics. Lastly, we discuss popular software tools like Adobe Illustrator that are commonly used in the creation of data visualizations.

Understanding Computer Programming: Essential Concepts and Applications

Rujittika Mungmunpuntipantip — 2025-03-15

In today's technology-driven world, learning how computer programs work and how to write them is an essential skill. This article introduces the fundamental workings of computer programs, focusing on the key command structures and their practical applications. By understanding the basics of programming, individuals can not only use computers more efficiently but also gain the foundation to explore more advanced programming techniques. The article serves as an entry point for those interested in developing the ability to write and understand computer code.

Enhancing Student Performance and Retention Prediction across Different Languages Using Ensemble Learning Models

Sukhdev Singh — 2025-03-15

This research develops ensemble models for predicting student performance retention across multiple languages using artificial intelligence as part of educational analytics improvement. A dataset of approximately 11500 entries obtained from Kaggle needed preprocessing methodologies that standardized and normalized and balanced the data. A combination of Logistic Regression and Decision Trees with Gradient Boosting constitutes an ensemble model which performs better than Random Forests and Support Vector Machines as conventional models. The ensemble model reveals its superiority through performance measures that show 96% accuracy as well as precision, recall and F1 score. The predictive model demonstrates its capability to perform well in various linguistic contexts. AI-based insights prove valuable as both personalized learning tools and early identification systems which create opportunities for future educational forecasting development through deep learning methods alongside broader socio-cultural factors.