ADAPTIVE LEARNING USING ARTIFICIAL INTELLIGENCE: AN INNOVATIVE APPROACH FOR E-LEARNING PLATFORMS

Abstract

E-learning has become an important area of scientific research, especially since the COVID-19 pandemic, which has led to increased focus on this topic. However, many e-learning systems still use a one-size-fits-all approach, similar to trying to fit a single shirt size on all men's sizes. To address this issue and accommodate individual differences among students, an adaptive learning system is needed. This system can provide tailored learning paths that match each student's academic level and personal needs. This research introduces an adaptive learning system called Najah-AI. In this system, the curriculum is divided into specific learning objectives, and various recommendation systems are used, including collaborative and content-based approaches. The nearest neighbor machine learning algorithm was chosen for its suitability to the data type in this study. The findings revealed that 71% of students benefited from the adaptive e-learning system, and their performance improved significantly after watching videos that supported the learning objective where they were struggling.