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Smart Academic Adviser system for assisting academic adviser to manage students progress and profile. The system utilizes some machine learning methods to predict students progress

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GP1-G3-AcademicAdviser

Smart Academic Adviser system for assisting academic adviser to manage students progress and profile. The system utilizes some machine learning methods to predict students progress

Promo Video

https://youtu.be/8wi1KBgZsOk

Abstract

The proposed solution focuses on the academic advising process by creating an assistant system for academic advisors and students. Our aim is to provide a comprehensive dashboard that presents a fine-grained visual representation of the essential information and data needed by the advisor in one place. The solution is designed to significantly reduce the workload and time spent on manual data collection and analysis by bringing all relevant information into one central location.

Motiviation

The increasing number of college students had significantly contributed to the increasing workload on the academic advisor. The demand for one platform to gather all students' data in one place from the academic advising point of view. This can be achieved by providing some assisting information through student's profile to review, progress to check, and important decisions regarding the student progress. Eventually, academic advisors should struggle less when gathering all the necessary information to understand each student's profile.

User Interface

Original Theme

Group 701

Academic Theme

Group 703

Conclusion

In Conclusion, we developed a system to assist the academic advisor and the student in order to improve the academic advising process. The system has been developed with various features to facilitate the decisions made by the advisor. The quality of the user interface has been tested using a usability testing survey on a number of participants.

Demo

https://youtu.be/xbjcysKb_XE

Codemagic build status CircleCI

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Smart Academic Adviser system for assisting academic adviser to manage students progress and profile. The system utilizes some machine learning methods to predict students progress

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