Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System

Abstract

It is believed that the evaluation of the outcomes of the course, based on grades, is necessary to improve the teaching and learning process. Our research processes and workflows supported by AI utilize machine learning technology in order to interpret big data, analyze broad data sets and recognize associations with more reliably. The course learning outcomes will be assessed on the basis of QF-Emirates guidelines and use it to suggest teaching and learning measures. It will be used to determine courses learning results based on the empirical knowledge presented. We research and test the design of the right neural networks that achieves our goal. A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. As a machine-learning system, the proposed approach is tested and results are competitive.