Educational Recommender Systems and Machine Learning

Abstract

A recommender system is one of the utilization of a vast amount of data normally known as Big Data, stored in digital format. One of the important of big data applications was to analyze them to identify relations concealed inside the data, such as pattern relations which were later developed for problem solving guidelines or for decision making. The ability of the recommender system was developed and created from the machine learning in which the machine or computer was enabled to imitate human intelligence and ability through the computer command set or algorithm. The computer finally could retrieve data and analyze them, and perform problem solving and decision making through the algorithm successfully prepared by human. The most important element of the recommender system was its ability in recommending information timely needed by users. In addition users’ trust in the recommender system concerning recommended information, its safety and usability was also important. Therefore, machine learning technique was integrated for problem solving and improving the system effectiveness in recommending more accurate and timely needed information. The purpose of this paper was to present machine learning technique for educational usage and guideline for improving educational recommender system effectiveness. This would eventually lead to the provision of accurate information needed by users.