TY - GEN
T1 - Automatic academic advisor
AU - Taha, Kamal
PY - 2012
Y1 - 2012
N2 - One of the problems that face a Distance Education academic advisor (and for lesser degree local academic advisors) is to identify courses that best suit a student's interests and academic skills from a wide collection of elective courses. This is because an advisor needs to select courses that suit both the interest and academic skills of the student. The student may not be able to know his interest in a course from merely its title or from the description of the course provided in the course catalogue. Also, the advisor needs to advise the student to take a course that suits the student's academic performance and skills. Towards this, the advisor needs to consider the performance of students in all his prior courses, which is time consuming. These problems can be overcome using a course recommender system. We introduce in this paper an XML user-based Collaborative Filtering (CF) system called AAA. The system advises a student to take courses that were taken successfully by students, who have the same interest and academic performance as the student. We experimentally evaluated AAA. Results showed marked improvement.
AB - One of the problems that face a Distance Education academic advisor (and for lesser degree local academic advisors) is to identify courses that best suit a student's interests and academic skills from a wide collection of elective courses. This is because an advisor needs to select courses that suit both the interest and academic skills of the student. The student may not be able to know his interest in a course from merely its title or from the description of the course provided in the course catalogue. Also, the advisor needs to advise the student to take a course that suits the student's academic performance and skills. Towards this, the advisor needs to consider the performance of students in all his prior courses, which is time consuming. These problems can be overcome using a course recommender system. We introduce in this paper an XML user-based Collaborative Filtering (CF) system called AAA. The system advises a student to take courses that were taken successfully by students, who have the same interest and academic performance as the student. We experimentally evaluated AAA. Results showed marked improvement.
KW - Automatic academic advisor
KW - collaborative filering
KW - Course recommender system
KW - Distance education
UR - https://www.scopus.com/pages/publications/84874407469
U2 - 10.4108/icst.collaboratecom.2012.250338
DO - 10.4108/icst.collaboratecom.2012.250338
M3 - Conference contribution
AN - SCOPUS:84874407469
SN - 9781936968367
T3 - CollaborateCom 2012 - Proceedings of the 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing
SP - 262
EP - 268
BT - CollaborateCom 2012 - Proceedings of the 8th International Conference on Collaborative Computing
T2 - 8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2012
Y2 - 14 October 2012 through 17 October 2012
ER -
