Prediction of Punjab Examination Commission (PEC) Student’s Performance Using Educational Data Mining

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Fareeha Anwar
Hira Afzak


Predicting the student performance is integral in the field of education. Conducted studies mainly interests the higher education area due its importance and validity but recognizing problems of students in early stages can be beneficial in the long run. Detecting problems at secondary level not only reduce the rate of students’ failure in primary stages but also be converted into teacher’s pedagogical support. In Pakistan predicting students’ performance at primary and secondary level have not been explored yet. Even though province of Punjab conducts yearly assessment of students which can be utilized to study students’ performance and behavior. This study proposes using educational data mining techniques on the primary and secondary level students’ data who attended Punjab Examination Commission assessment, to predict their performance. Dataset is created by collecting data from schools. Based on precision. accuracy and time taken to execute the model decision tree J48 outperforms other with accuracy of 99.3% with minimum time taken and factors which contributed in students’ downfall were low attendance and lack of understanding of certain subjects.

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How to Cite
Anwar, F., & Afzak, H. (2021). Prediction of Punjab Examination Commission (PEC) Student’s Performance Using Educational Data Mining. University of Wah Journal of Science and Technology (UWJST), 5(1), 63-71. Retrieved from


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