Document Type : Research Paper

Authors

• Delara Jafari
• Zahra Shaterzadeh-Yazdi

School of Engineering Science, College of Engineering, University of Tehran, 16 Azar Street, Enghelab Square, Tehran, Iran

Abstract

The evolving educational landscape requires innovative teaching methods to enhance learning and accommodate diverse styles. Technologies like artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are transforming education by improving student performance and engagement. This research introduces an Artificial Intelligent Personal Recommender System Algorithm (AIPRS) that focuses on individual learning styles and interests to recommend customized learning programs. Unlike traditional methods, AIPRS personalizes education by analyzing learners' backgrounds and preferences, utilizing AI, ML, and IoT. This tailored approach marks a significant shift from conventional systems, emphasizing the importance of individual learning styles to improve the overall educational experience. The study highlights the potential of personalized education, offering a solution to efficiently deliver knowledge and enhance student satisfaction.

Keywords

• Personalized Recommender Learning Algorithm
• Artificial Intelligence (AI)
• Machine Learning (ML)
• Internet of Things (IoT)
• Educational Technology
• Learning Styles