Utilizing Machine Learning to Increase Online Learning Instructors' Efficiency

Abstract

The online learning management system (OLMS) is one of the fundamental parts of the e-learning framework. As assessment of teachers is referred to as an essential part of education and a helpful contribution to improve the nature of teaching, the Feedback module of the OLMS provides with the facility to collect potential feedback of the teachers. The integration of the feedback module of the system with artificial intelligence (AI), especially machine learning (ML) allows with the ability to investigate vast amounts of data and discover patterns that can be useful in the progression of teaching techniques and ensures a deep analysis of the performance of the teachers. This absolutely underpins educational institutions to undertake noteworthy decisions for the improvement of the teachers and ultimately, the learners. This work proposes that the incorporation of technologies, like machine learning algorithms, with OLMS may facilitate in augmenting teaching efficiency.