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2015 | OriginalPaper | Chapter

Data Analysis for Courses Registration

Authors : Nada Alzahrani, Rasha Alsulim, Nourah Alaseem, Ghada Badr

Published in: Machine Learning and Data Mining in Pattern Recognition

Publisher: Springer International Publishing

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Abstract

Data mining is a knowledge discovery process to extract the interesting previously unknown, potentially useful and non-trivial patterns from large repositories of data. There is currently increasing interest in data mining in educational systems, making it into a growing new research community. This paper applies a frequent patterns extraction approach to analyzing the distribution of courses in universities, where there are core and elective courses. The system analyzes the data that is stored in the department’s database. The objective is to consider if allocation of courses is appropriate when they are more likely to be taken in the same semester by most students. A workflow is proposed; where the data is assumed to be collected over many semesters for already graduated students. A case study is presented and results are summarized. The results show the importance of the proposed system to analyze the courses registration in a given department.

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Title: Data Analysis for Courses Registration
Authors: Nada Alzahrani
Rasha Alsulim
Nourah Alaseem
Ghada Badr
Publisher: Springer International Publishing
Book: Machine Learning and Data Mining in Pattern Recognition
Print ISBN: 978-3-319-21023-0

Electronic ISBN: 978-3-319-21024-7

Copyright Year: 2015
DOI: https://doi.org/10.1007/978-3-319-21024-7_24

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