Synthesis of External Quality Assessment Reports in Industrial and community using Text Mining and OLAP

Abstract

The purposes of this research were to study the general information and synthesize the external quality assessment of Industrial and Community Education Colleges. We collected in second round that was qualified by Office of Standards and Quality Assessment. Text Mining was employed to classify unstructured data, particularly strength points and weakness points and then OLAP was utilized to synthesize external quality assessment reports. Significant are as follow: Most Industrial and Community Education Colleges are small-size and offer Industrial Trades and Commerce/Business Administration. The results of external quality assessment, there are 84.61 % that qualified, 5.59 % on probation and 9.79 % unqualified. Strength points of Industrial and Community Education Colleges were academic services to respond to the needs of community and society whereas weakness points were in Management Information System. Keywords: External Quality Assessment, Industrial and Community Education Colleges, Text Mining, OLAP