Artificial Intelligence enabled Smart Learning
This paper addresses the problem of learning gaps and student dropouts in traditional education for students, proposing AI-enabled personalized learning as a solution. This is an incremental contribution.
This paper discusses the potential of Artificial Intelligence to personalize learning experiences, addressing the limitations of traditional education where a single teaching method may not suit all students. By analyzing vast amounts of student data, AI aims to tailor learning content and methods to individual needs, thereby reducing learning gaps and student dropout rates.
Artificial Intelligence (AI) is a discipline of computer science that deals with machine intelligence. It is essential to bring AI into the context of learning because it helps in analysing the enormous amounts of data that is collected from individual students, teachers and academic staff. The major priorities of implementing AI in education are making innovative use of existing digital technologies for learning, and teaching practices that significantly improve traditional educational methods. The main problem with traditional learning is that it cannot be suited to every student in class. Some students may grasp the concepts well, while some may have difficulties in understanding them and some may be more auditory or visual learners. The World Bank report on education has indicated that the learning gap created by this problem causes many students to drop out (World Development Report, 2018). Personalised learning has been able to solve this grave problem.