A new approach for evaluating the virtual education of students using association rule-mining in cloud computing environments

Nowadays, most universities and organizations use various computer systems, operating systems, mobile devices and databases with different infrastructure, hardware and software architectures. Many internet-based systems and advanced distributed environments have currently been developed in adapting to heterogonous systems. Cloud and grid computing are the new developed environments that present required services of users. In virtual education system, learners use different systems and facilities in various geographical locations. Therefore, evaluating the quality of education of learners is sophisticate. To this issue, we have developed a new approach for analyzing and extracting useful rules based on distributed heterogonous environments. For this research, we have implemented our proposed approach based on simulated grid computing environment. The obtained results confirm that the extracted rules based on distributed information can be useful to personalize education system for learners based on their characteristics and locations. This new architecture is powerful and rapid in comparison with centralized architectures. Keywords: cloud computing, association rule mining, virtual education;