Algorithm for Anticipating Students’ Academic Per-formance Using Cloud

Abstract

Nowadays, Educational Data Mining (EDM) has become apparent system. EDM gives prominence on expansion of methods to examine particular data types that appear in educational frameworks such as classic face-to-face classroom habitat, educational software, online courses, and online examinations. These point of supply releases sheer volume of data, which can be analyzed to address questions that were not heretofore accomplished, viz. predicting students’ academic performance. EDM’s assistance have motivated a thought on pedagogy and learning and advanced the upgrade of students’ academic performance. Once there is a sizable volume of students’ academic records, manual prediction of students’ success is not feasible, instead go for automatic prediction. Task on this scope has been implemented, with the research being focused mainly on students’ classifier models for predicting students’ success. With the existing data, corporate with a suitable data mining tool, an appropriate appealing model can be built for predicting students’ academic performance. Classification is an eminent option, because it can bring off such class models, based on historical data. Once these models are set up, they can be used as predictive tools for new students’ favourable outcome. In this article, a classification method established on C5.0 algorithm is outlined and have been applied for predicting students’ academic performance. Since, the data is large, it has been decided to use a cloud-based system for maintaining students’ records. This evaluation model is invaluable to both learners and teachers for improving the student’s academic performance.