Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/20086
Title: Towards a virtual academic adviser
Authors: Ajanovski, Vangel 
Issue Date: 2011
Conference: 8th International Conference for Informatics and Information Technology (CIIT 2011)
Abstract: One of the major administrative processes at the Institute of Informatics – the term enrollment, starts few weeks before the start of each following term and ends a week after the start of the courses. The students have to submit an enrollment application for the academic term with a selection of courses which then has to be approved by the academic adviser. The latest changes of the legislation allow that only 50- 60% of the courses for each program can be mandatory, whereas the rest of the courses can be chosen from other programs in the same institution or even from any program active at the university. The role of the academic adviser is to help the students with their choices and prevent them of making costly mistakes that could prolong their studying. The approval process is already done on-line [1], and the proposal is to introduce a virtual academic adviser component that will further ease this process by helping the majority of students, leaving only the truly problematic to be dealt off-line. The virtual adviser is a component that presents a visual map of all of the previously enrolled terms and the courses selections in each term to a student. It gives the student measures of his success in comparison to other students. The student can see his speed in acquiring and passing credits and compare it with the average of his generation. Further, the future academic terms of the student are mapped according to his average speed and his graduation date is forecasted. The component will enable the student to perform what-if scenarios and change his load, change plan/program, rearrange courses in order to come up with the best plan until graduation. This component will also enable future addition of intelligent recommendation system modules that may evaluate the capability of each student and his academic performance parameters, compare them to a historical database and suggest an optimally achievable adapted study plan to the student that may lead him to faster completion and/or higher GPA.
URI: http://hdl.handle.net/20.500.12188/20086
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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