Using big data technology for prediction of quiz difficulty level in E-learning systems

Abstract EN

In recent years, big data have received a great deal of attention from many of researchers.

Big data concepts have its various applications; it can be used in the field of healthcare and medicine, education world, finance and fraud detection, education and industry sectors...etc.

From e-Learning environment, a large amount of data could be generated as a result of different e-learning aspects, which is called Big Data in e-learning.

Analyzing big data across the educational organization has the potential to enhance the future of e-learning contents and students’ performance.

The aim of the paper is to develop a method that can be used for analyzing the level of difficulty of the test questions for students who tested through e-learning software.

I addition, it is expected to help instructors in determining strengths and weaknesses of students in the exams, as well as recognizing hardest/easiest questions for students based on their answers.

An emerging open source Apache Spark tool had been used to facilitate the analysis process of large data through linking it to the database of e-learning systems.