Ofejiro Akwenuke
University of Maryland Eastern Shore

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Student Advising and Retention Application in Cloud Computing Environment Gurdeep S Hura; Ofejiro Akwenuke
Journal of Education and Learning (EduLearn) Vol 10, No 4: November 2016
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (929.121 KB) | DOI: 10.11591/edulearn.v10i4.4729

Abstract

 This paper proposes a new user-friendly application enhancing and expanding the current advising services of Gradesfirst currently being used for advising and retention by the Athletic department of UMES with a view to implement new performance activities like mentoring, tutoring, scheduling, and study hall hours into existing tools. This application includes various measurements that can be used to monitor and improve the performance of the students in the Athletic Department of UMES by monitoring students’ weekly study hall hours, and tutoring schedules. It also supervises tutors’ login and logout activities in order to monitor their effectiveness, supervises tutor-tutee interaction, and stores and analyzes the overall academic progress of each student. A dedicated server for providing services will be developed at the local site. The paper has been implemented in three steps. The first step involves the creation of an independent cloud computing environment that provides resources such as database creation, query-based statistical data, performance measures activities, and automated support of performance measures such as advising, mentoring, monitoring and tutoring. The second step involves the creation of an application known as Student Advising and Retention (SAR) application in a cloud computing environment. This application has been designed to be a comprehensive database management system which contains relevant data regarding student academic development that supports various strategic advising and monitoring of students. The third step involves the creation of a systematic advising chart and frameworks which help advisors. The paper shows ways of creating the most appropriate advising technique based on the student’s academic needs. The proposed application runs in a Windows-based system. As stated above, the proposed application is expected to enhance and expand the current advising service of Gradesfirst tool. A brief demonstration of the proposed application will highlight the main features of the existing tool (Gradefirst).