Abstract
Education can shape a better tomorrow, and it positively affects learning outcomes when it is delivered with better methods and procedures. Academic institutions are always looking for solutions to improve their efficiency and boost student outcomes. For many scholars in the past several years, data mining has become an area of interest because of statistics mining’s ability to uncover hidden patterns and trends in the data. Learning with the aid of technology, also known as educational data mining, is a productive process that significantly contributes to the growth of the academic sector. It is incredibly simple to retrieve the necessary data from various sources using machine learning techniques, and users like students, teachers, and professors can immediately utilize this data. The use of various tools to deliver better education utilizing efficient material produced from a very large database and provided to the target audience is one of many trends that are currently becoming popular in the educational system. In the current scenario when thinking about the use of machine learning in education, many techniques are available like adaptive learning, predictive learning, personalized learning, assessment evaluation, and many more. A different researcher works on it, but still, there is a lack of technique that handles multiple criteria and give concrete way using which the education domain get beneath. Therefore, the purpose of this work is to identify and analyze the numerous machine learning techniques that support the extraction of crucial information.
Authors
