| dc.description.abstract | In recent years, due to the rapid development of university education, many schools have begun to develop institutional research for the purpose of better evaluating and improving the school’s own operation and teaching performance, so that school decision makers can help schools to improve their planning through scientific research, and improve the quality of school operations and school development through data collection, analysis, and interpretation.
The institutional research data covers a wide range of school-related resources, including students, staff, teaching and academic affairs. Although the institutional research office has collected, organized, and integrated data from various offices, there is still unexplored information that has yet to be analyzed and utilized. Our research use students as the theme to conduct exploratory data analysis and analyze the development trend of students from their background, learning history, and post-graduation status, etc. Our research explore the combination of data that have causality from different aspects to provide institutional research office with diversified analysis issues and decision support.
In addition, since school data are constantly added, the addition of new data will affect the accuracy and applicability of the analysis results. In order to be more practical, our research design a incremental mining system framework, hoping to quickly provide decision makers with causal rule analysis results even when data are continuously added, and to reduce the possible loss caused by analysis delay. | en_US |