Cognitive Web Service-Based Learning Analytics in Education Systems Using Big Data Analytics

Abstract

In the field of education, digital learning plays an important part. For each passing day, digital learning is displacing the traditional method of education. An accurate analysis of a student's qualities improves their academic performance. With the advancement of technology and big data, there are many applications for big data analytics, including education. Huge volumes of academic information are being generated, and discovering a technique to harness and analyze this information effectively is a challenging issue among many educational organizations. In this paper, educational clustering big data mining system (ECBDMS) has been proposed. The cognitive web service based learning analytic(CWS-LA) system is integrated to securely categorize and provide ease of access to the data. ECBDMS has been found to improve performance gains of 92.8%, prediction ratios of 88.6%, clustering error ratios of 2.3 percent, learning percentages of 94%, and forecasting accuracy of 97.1 percent when compared to other existing methods.