| Summary: | 碩士 === 國立暨南國際大學 === 資訊管理學系 === 103 === Big Data continues popular. The issue pertaining to ways of utilizing data analysis for value-added data becomes important, which is not just because industries intend to make use of its creating competitive advantages, and current social environment changes gradually that declining birthrate is worthy of worry in the future, but also that the autonomy of universities and colleges enlarges which make them bear enrolling pressure on their own. In light of this, how to make the most proper use of limited school resources to achieve the most appropriate use of institutional resources becomes an issue needing universities and colleges to overcome. These of data analysis for "institutional research" has been implemented for years, which aimed at analyzing campus data, external data, and maximize resource utilization or provide decision-making information. This trend spreads gradually throughout Taiwan, and universities and colleges of Taiwan began to develop institutional research data analysis platform.
Many of the current platform of institutional research target on the analysis of curriculum and student learning effectiveness. However, as of now, the definition of student learning effectiveness is quite vague without uniform benchmarks for further evaluation. For this reason, this study intended to define target group in evaluating student learning effectiveness, aimed at finding out students who need counseling, and identifying key indicator variables among for subsequent differentiated prediction and tracking. Department of Information Management, C University was served as the subject in the case study.
Finally student’s learning effectiveness was clustered and distinguished and further for prediction. From these, we may predict student groups who might need counseling accurately. According to the findings, in the last semester, effectiveness variables had high degree of correlation, among of which, in the 2nd semester as a sophomore, the average score of the course titled Information Management was affected to the most, where prediction via such variables generated the most accurate effectiveness.
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