Implementation of Learning Analytics with Deduplication

• Author(s): I. Bhuvaneshwarri
• Paper ID: 1700707
• Page: 55-57
• Published Date: 31-07-2018
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 2 Issue 1 July-2018

Abstract

Learning Analytics (LA) provides useful insights to tutors on the behavior of students in an online learning environment. The information collected for LA is treated as big data used to customize the educational environment, optimize the learning resources and activities, and personalize the student experience. The major three steps of LA are information gathering, information processing and information presentation. The benefit related with big data is scalability, it can be collected automatically in a computer-enabled learning environment and analyzed in bulk without requiring additional time and resources even though the data size grows significantly. However, the analysis of big data is not easy and requires suspicious investigations before it can be useful to researchers, teachers and students, and curriculum and technology developers. The duplication of big data impact results of analysis. In this paper, I have proposed deduplication technique on big data in information gathering step of LA. In this paper, I have taken real world data set and apply the deduplication technique and then compare the results. From the result, it shows that after applying the proposed method the duplicated data is removed from large data set and the size of big data taken for LA is optimized to reasonable size and provides better result.

Keywords

Learning Analytics, Big Data, Deduplication, optimization

Citations

IRE Journals:
I. Bhuvaneshwarri "Implementation of Learning Analytics with Deduplication" Iconic Research And Engineering Journals Volume 2 Issue 1 2018 Page 55-57

IEEE:
I. Bhuvaneshwarri "Implementation of Learning Analytics with Deduplication" Iconic Research And Engineering Journals, 2(1)