INDIVIDUALIZED LEARNING: CUSTOMIZED TUTORING WITH ARTIFICIAL INTELLIGENCE (AI) ADAPTABILITY

Abstract

This paper explores the integration of Adaptive Artificial Intelligence (AI) in educational settings to customize tutoring experiences according to individual student needs. Traditional one-size-fits-all approaches to education often overlook the diverse learning styles, paces, and preferences of students, leading to inefficiencies and disparities in academic outcomes. Adaptive AI presents a promising solution by dynamically tailoring instructional content, pace, and feedback to suit each student's unique profile. The implementation of Adaptive AI in tutoring involves several key components, including data collection through various sources such as assessments, interaction logs, and behavioural patterns. Machine learning algorithms then analyse this data to identify patterns, strengths, weaknesses, and learning preferences of individual students. Based on these insights, the AI system generates personalized learning pathways, selecting and delivering content and activities that are most relevant and effective for each student.