Recommending degree studies according to students’ attitudes in high school by means of subgroup discovery

DOI

10.1080/18756891.2016.1256573How to use a DOI?

Keywords

Subgroup discovery; recommending degree; students’ skills

Abstract

The transition from high school to university is a critical step and many students head toward failure just because their final degree option was not the right choice. Both students’ preferences and skills play an important role in choosing the degree that best fits them, so an analysis of these attitudes during the high school can minimize the drop out in a posteriori learning period like university. We propose a subgroup discovery algorithm based on grammars to extract itemsets and relationships that represent any type of homogeneity and regularity in data from a supervised context. This supervised context is cornerstone, considering a single item or a set of them as interesting and distinctive. The proposed algorithm supports the students’ final degree decision by extracting relations among different students’ skills and preferences during the high school period. The idea is to be able to provide advices with regard to what is the best degree option for each specific skill and student. In this regard, the use of grammars is essential since it enables subjective and external knowledge to be included during the mining process. The proposed algorithm has been compared against different subgroup discovery algorithms, achieving excellent results. A real-world experimental analysis has been developed at King Abdulaziz University, one of the most important universities in Saudi Arabia, where there is a special interest in introducing models to understand the students’ skills to guide them accordingly.

Copyright

© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis

Open Access

This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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TY  - JOUR
AU  - Amin Y. Noaman
AU  - José María Luna
AU  - Abdul H. M. Ragab
AU  - Sebastián Ventura
PY  - 2016
DA  - 2016/12/01
TI  - Recommending degree studies according to students’ attitudes in high school by means of subgroup discovery
JO  - International Journal of Computational Intelligence Systems
SP  - 1101
EP  - 1117
VL  - 9
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1256573
DO  - 10.1080/18756891.2016.1256573
ID  - Noaman2016
ER  -