A Recommendation System for Books as Part of Smart Education

Abstract

Innovative solutions that attempt to enhance conventional learning system include smart academic system and machine learning-based recommendation systems. Machine Learning technologies are used in smart learning system to provide a more dynamic and customized learning environment. With the help of this technology, students can analyze, get appropriate guidance to ameliorate the quality of educational and evaluation strategies for raising the quality of instruction. The recommendation systems also analyze student performance data using machine learning algorithms and offer tailored suggestions to help students achieve better learning outcomes. These recommendations may include ideas for extra reading material, course selection, book selection result analysis, and placement options.  Contingent on the student's engrossment and objectives, the recommendation systems may also be utilized to offer suitable courses and learning routes. The research presented in this paper focuses on how different machine learning algorithms may provide better results for smart education, making the knowledge gaining process simple and precise. This research work helps in planning & execution of Intelligent Recommendation System (IRS) & its effective evaluation. It is further analysed that individualized and successful learning experience may transform the education industry into a smart education and recommendation system employing machine learning.