Applicability of skyline query algorithm for career identification of k-12 graduates
1 Bulacan State University, City of Malolos, Bulacan, Philippines.
2 Angeles University Foundation, Graduate School, Angeles City, Philippines.
Research Article
Global Journal of Engineering and Technology Advances, 2020, 02(03), 010-015.
Article DOI: 10.30574/gjeta.2020.2.3.0012
Publication history:
Received on 18 February 2020; revised on 24 February 2020; accepted on 25 February 2020
Abstract:
In making the student highly proficient in a particular field, choosing the right program track in the Senior High School (SHS) program is critical. The additional 2 years in high school allow them to choose a specialization that is related to the field or profession that they wish to pursue in College. Computing user preference using skyline query algorithm can be a tool in determining the right career intended for a student since it can be used for various applications that include decision making, personalized services, and search pruning.
This paper focused on reviewing significant literature concerning the applicability of this algorithm in identifying the right course based on the student’s academic qualifications and K to 12 program tracks, strand and specialization as entry requirements in higher education. Different skyline query algorithm and processing were presented. Other significant variables like academic performance, examination taken and other significant variables will be considered in evaluating the capability of the student before entering to a college degree program. Identification of the data sets of the senior high school program tracks will be categorized into Academic tracks, Technical-Vocational-Livelihood, and Arts, Design and Sports which can be used to classify all the courses available related to the students’ chosen career.
Keywords:
Skyline Query Algorithm; Senior High School Program Tracks; User Preference; Entry Requirement in Higher Education
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Copyright © 2020 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0