K-12 Students’ Academic Status: A Data Warehouse Architecture Framework
Evangeline T. Sarte1, Thelma D. Palaoag2
1Evangeline T. Sarte, Our Lady of Pillar College-Cauayan, Cauayan City, Philippines.
2Thelma D. Palaoag, University of the Cordilleras, Baguio City, Philippines.
Manuscript received on 16 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 2749-2752 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B13370982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1337.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The K-12 Basic Education Program in the Philippine is now on its full swing status. However, as it moves to the peak of its full implementation, the number of drop-outs, retention, and migration students is increasing. With this in mind, the researcher came across with designing data warehouse and data mining architecture in the analysis of drop-out, retention, and migration patterns of students. Academic performance is the main factor in the students’ drop-out, retention, and migration. The proposed architecture would be sufficient for the analysis of the K-12 students’ academic status. It served as a foundation in the conduct of a thorough study on students’ drop-out, retention, and migration patterns.
Keywords: K-12, Data Warehouse Architecture, Academic Status.
Scope of the Article: Patterns and Frameworks