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The Hub

Volume no. 7 | 2017/10
Issue no. 1


Title
UB – My Thought: utilizing the concept of Data Warehousing and Sentiment Analysis to Manage Student Attendance
Author
John Mark A. Mangurali, Jhoan B. Patulot Researchers Mrs. Elvie E. Pita Adviser
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Abstract
One of the emerging trends is the use of business analytics in different organizations particularly in universities and colleges. With the rise of big data, its impact has becoming apparent even in the Higher Education sector. The strategic use and applications of big data in higher education would lead to higher educational quality and better student and staff experience. The study aims to design an Early Alert System that will provide an early warning and follow-up for students identified by their faculty member as experiencing academic difficulties or other problems interfering with the student’s academic success in the University of Batangas. Specifically, this research analyzes the concept of data mining and predictive analytics in designing an early alert system that relies on data about student behavior to identify students at risk of dropping out and to target interventions that assist the students in completing their course and/or program of study. By studying historical data, colleges can build profiles of students who are most at risk of not persisting and develop steps to intervene in a timely manner. Finally, the research outputs the design of the Early Alert System which can be used as a tool for maintaining the competitive advantage of the University of Batangas and to ensure high percentage of student retention and student success. This study utilized descriptive research design. Descriptive research is used to describe characteristics of a population or phenomenon being studied. It does not answer questions about how/when/why the characteristics occurred. The researchers will employ descriptive research design. Secondary data will be used and will be collected from the students output, curriculum guide, and the industry partners.
Keywords
Student retention, Dropouts, Data Warehouse, Sentiment analysis, Dashboards, Metadata repository, Data Mart
References
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