A Case Study on Students’ Academic Performance Employing Educational Data Mining
Data Mining Technology helps an organization to easily recognize the trends, patterns and visualization of the data available in a database. In an educational institution, the process is called Educational Data Mining which was applied on this study. The academic performance, gender, subjects and type of originating schools are the attributes which were derived from the database source. In order to process the extracted data, the Knowledge Discovery Process model was used. The Classification technique was utilized in order to categorize the attributes of the data collected and the rule based classifier using a set IF-THEN rules was also used to represent the information that was derived. The primary goal of the case study is to determine the level of academic achievement of the Grade 10 Junior High School from a select secondary private high school when grouped according to their originating schools, identify who perform better between male and female and determine the courses in which the students excel most and on the other hand find difficulties. The results of the study implied that originating school has a factor on academic performance of students, it was also proved that female performs better than male. Furthermore, it was identified that the academic performance rating of students in most subjects fall under the Proficiency level and revealed that Mathematics is the most difficult subject.
Keywords - Rule-based Classification, Academic Performance, Data Mining, Knowledge Data Discovery