Virtual Programming Laboratory with Machine Learning-Based Evaluation System for Computer Science Students
Discover the innovative tools that make our platform unique
Integrated development environment supporting PHP, HTML, and CSS with secure isolated coding environments.
Advanced analytics tracking student progress, learning patterns, and interaction with course materials.
K-Means clustering algorithm analyzes student behavior to provide personalized feedback and support.
Isolated coding environments ensuring security and consistent learning experiences for all students.
Immediate code analysis and feedback to help students improve their programming skills.
Comprehensive collection of learning materials, code examples, and documentation for reference.
Our e-learning platform provides an interactive learning environment for students to practice programming through a virtual laboratory IDE feature. The platform is equipped with a student activity monitoring system based on log files that uses machine learning algorithms (k-means) for analysis.
The main features include a virtual laboratory IDE that currently supports programming languages such as PHP, HTML, CSS, with full integration for coding, debugging, and testing. Each student is given an isolated code environment ensuring security and consistency in the learning experience.
Our student activity monitoring system automatically records and analyzes user activities, including interaction with materials, learning time, and IDE usage. These activity logs are analyzed using the K-Means machine learning algorithm to map student behavior, enabling recognition of different levels of understanding and delivery of customized feedback.