Intelligent computing for skill-set analytics in a big data framework—a practical approach

Abstract

Over the last few decades there is considerable increase in number of students both in Traditional as well as Online education. Especially students are showing utmost interest to learn from advanced online systems (Moretti in EDM, 2014, [1]) such as Intelligent Tutoring systems, Massive Open Online Courses (MOOC) and Virtual learning environments. These all systems are generating huge amount of Data. Now it is crucial to handle Big Data in Education. If Big Data in Education is handled properly by applying Big Data Analytics Techniques and Tools then some Intelligent Patterns can be retrieved which helps to improve Education process. In this paper Hadoop Framework (White in The definitive guide, O’Reily Media, 2009, [2]) is used to handle and process data. Analytics is applied by taking Resumes Data which are the most useful and commonly available Educational Data for Analysis and various valid Skill Inferences are drawn. Further Performance Analysis for Experiments is done by comparing Nondistributed Environment and Distributed Hadoop cluster by increasing the number of nodes. Stepwise experimentation is provided in Appendix with screenshots.