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Objective: Academic institutions worldwide are continually trying to improve their curricula to address the needs of industry and government. Many technology curricula emerged to satisfy well recognized IT standards and critical components. Colleges and universities are now inclined to include IT certification in their curricula. Moreover, this study aims to develop a model that will predict outcomes based performance of the IT students in their Cisco Certification Program. Method: The data sets used in this field are the forms of the 3rd year BSIT students enrolled in the Cisco Routing and Switching Certification Program from S.Y 2016-2017. Findings: There were 165 datasets with five variables Pre-Test, Quizzes, Hands-on Skills Exam, Final Exam, and Remarks. The Data Mining process predicts the performance of the students in the certification program, individually, the J48 Algorithm derived from a C4.5 decision tree model. The results revealed that Quizzes had the highest instances of achieving a passing mark and became the first split between the (Finals<=79.67) and (Finals> 79.67) in predicting student Performance in the CISCO Certificate Program. Moreover, it showed the decision tree model Quizzes has the highest factor that students will get Passed, Failed, or Conditional marks. Application/Improvements: In order to obtain more precise results, we can employ other reputable data mining techniques and prediction algorithms or a combination of both to assess and guide student performance in future studies.

Predicting Student Performance in a Computer Network Certification Program: using the J48 Algorithm